EMA Indicators with BUY sell SignalCombine 3 EMA indicators into 1. Buy and Sell signal is based on
- Buy signal based on 20 Days Highest High resistance
- Sell signal based on 10 Days Lowest Low support
Input :-
1 - Short EMA (20), Mid EMA (50) and Long EMA (200)
2 - Resistance (20) = 20 Days Highest High line
3 - Support (10) = 10 Days Lowest Low line
Search in scripts for "20蒙古币兑换人民币"
Enhanced Kitchen Sink Strategymulti-layered trading system designed for TradingView, targeting a minimum 75% win rate through precise entry signals and robust risk management. Built on classic EMA crossovers, it incorporates advanced filters for trend alignment, momentum confirmation, and market confluence to reduce false signals and maximize profitable trades. Ideal for swing traders on timeframes like 1H or 4H, it adapts to various assets (stocks, forex, crypto) while emphasizing conservative position sizing and dynamic stops. With customizable inputs and a real-time dashboard, it's user-friendly yet powerful for both beginners and pros aiming for consistent, high-probability setups. Core Entry Logic
At its heart, the strategy triggers long entries on bullish EMA crossovers (fast 12-period EMA crossing above slow 26-period EMA, with close above the slow EMA) and short entries on bearish crossunders. To ensure high-quality trades: Pullback Entries (Optional): Waits for price to retrace to a short-term EMA (default 8-period) before entering, capturing better risk-reward on dips in trends.
Signal Quality Scoring: A proprietary 0-100% score evaluates each setup across 6 categories (trend, EMAs, MACD, RSI, volume, trendlines/S&R). Trades only fire if the score exceeds your threshold (default 75%, adjustable to 0% for testing).
This results in fewer but higher-conviction trades, filtering out noise for superior edge. Advanced Filters for Confluence
No single indicator drives decisions—confluence is key: Trend Analysis: Master trend filter using a 200-period EMA and strength metric (default >0.5% deviation). Optional higher-timeframe (e.g., daily) confirmation via EMA and MACD alignment.
MACD Double Confirmation: Requires MACD line above/below signal (9-period) with optional histogram momentum buildup.
RSI + Divergence: Filters for neutral RSI zones (40-70 for longs, 30-60 for shorts) and detects bullish/bearish divergences over 20 bars.
Volume Profile: Demands above-average volume (1.5x 20-period SMA) with buying/selling pressure analysis.
Trendlines & S/R: Auto-detects dynamic trendlines from pivots (10-bar lookback) and support/resistance zones (100-bar lookback, 3+ touches), avoiding entries near key levels.
Session Filters: Trades only during London/NY sessions (UTC-based), skipping high-volatility news windows (e.g., 1:30-2:00 PM UTC).
All filters are toggleable, allowing you to dial in aggressiveness—disable for more signals during backtesting.Risk Management & Position Sizing
Safety first: Uses 100% equity per trade with 0.1% commission simulation. Stops & Targets: ATR-based (14-period) stop-loss (1x ATR) and take-profit (2.5x ATR) for 1:2.5 risk-reward.
Breakeven Moves: Auto-shifts stop to +0.1% entry after 1% profit.
Trailing Stops: Optional 1.5x ATR trail to lock in gains during runners.
No pyramiding—flat after each close for clean, low-drawdown performance.
Visualization & Insights On-Chart: Plots EMAs, pullback lines, S/R dashes, trend backgrounds (green/red), and entry labels/shapes.
Dashboard: Real-time table shows trend status, HTF bias, quality scores, MACD/RSI/volume readouts, session info, ATR, price, and position.
Customization: 20+ inputs grouped by category; max 500 labels for clean charts.
Performance Edge & Usage Tips
Backtested for 75%+ win rates in trending markets, this strategy shines in volatile assets like EURUSD or BTCUSD. Start with defaults on 1H charts, then tweak filters (e.g., lower quality to 50%) for ranging conditions. Always forward-test—past results aren't guarantees. Download, apply, and elevate your trading with confluence-driven precision!
8MA Compass — HTF map + GC/DC cues8MA Compass provides a clean trend context by combining strict 4-of-4 confluence (Current TF vs Higher TF) with SMA200 repainting on Golden/Death Cross (GC/DC).
What it shows
4-of-4 background (context): compares EMA10, EMA20, SMA50, SMA200 on the Current TF against the same four MAs on the Higher TF (HTF).
All 4 above their HTF values → bullish background.
All 4 below their HTF values → bearish background.
SMA200 color on GC/DC (Current TF):
Last signal is DC and price below SMA200 → SMA200 turns red.
Price above SMA200 but the last signal is DC (no GC afterward) → SMA200 stays base color.
Last signal is GC and price above SMA200 → SMA200 turns green #089981.
Why “8MA” ? The 4-of-4 logic uses 8 moving averages in total: 4 on the Current TF and 4 on the HTF (EMA10/20 and SMA50/200 on both frames). HTF EMAs are used in calculations but are not plotted by default—hence the name 8MA Compass.
Auto HTF mapping
Current 1H → HTF 4H
Current 4H → HTF 1D
Current 1D → HTF 1W
All other timeframes: HTF defaults to Current TF (4-of-4 will typically be neutral).
Manual mode: choose any HTF. If Manual HTF equals Current TF, HTF SMAs are hidden to avoid overlap.
Settings
1. Display
Show CURRENT TF — plot EMA10/20, SMA50/200 on Current TF.
Show HARD TF — plot SMA50/200 on HTF (hidden if HTF == Current TF).
HTF mode — Auto / Manual, with Hard TF (Manual) selector.
2. Filter
Show base background (4-of-4) — enable/disable confluence shading.
Epsilon (in ticks) — small tolerance in Cur vs HTF comparisons to reduce flicker.
3. Golden/Death
Color SMA200 on GC/DC (Cur TF) — repaint SMA200 on GC/DC per rules above (enabled by default).
Alerts
GC/DC (Current TF, SMA50/200): Golden Cross / Death Cross (on bar close).
EMA10/20 (Current TF): “Bull regime ON” / “Bear regime ON” on crossovers.
Optional HTF GC/DC alerts (SMA50/200 on chosen HTF).
Visual details
HTF SMA50/200 are drawn first; Current TF lines are drawn on top for clarity.
SMA200 (Current TF) is drawn last (and slightly thicker) to remain readable.
HTF EMAs are used in 4-of-4 logic but not plotted by design.
Usage
1. Use the 4-of-4 background as inter-timeframe momentum context.
2. Use SMA200 color to gauge long-term regime confirmation:
Prefer longs when last GC and price holds above SMA200 (#089981 line).
Avoid longs when last DC and price is below SMA200 (red line).
Disclaimer : For educational purposes only. Not financial advice. Trading involves risk.
Buzzara// © Buzzara
// =================================
// PLEASE SUPPORT THE TEAM
// =================================
//
// Telegram: t.me
a_trade// =================================
//@version=5
VERSION = ' Buzzara2.0'
strategy('ALGOX V6_1_24', shorttitle = '🚀〄 Buzzara2.0 〄🚀'+ VERSION, overlay = true, explicit_plot_zorder = true, pyramiding = 0, default_qty_type = strategy.percent_of_equity, initial_capital = 1000, default_qty_value = 1, calc_on_every_tick = false, process_orders_on_close = true)
G_SCRIPT01 = '■ ' + 'SAIYAN OCC'
//#region ———— <↓↓↓ G_SCRIPT01 ↓↓↓> {
// === INPUTS ===
res = input.timeframe('15', 'TIMEFRAME', group ="NON REPAINT")
useRes = input(true, 'Use Alternate Signals')
intRes = input(10, 'Multiplier for Alernate Signals')
basisType = input.string('ALMA', 'MA Type: ', options= )
basisLen = input.int(50, 'MA Period', minval=1)
offsetSigma = input.int(5, 'Offset for LSMA / Sigma for ALMA', minval=0)
offsetALMA = input.float(2, 'Offset for ALMA', minval=0, step=0.01)
scolor = input(false, 'Show coloured Bars to indicate Trend?')
delayOffset = input.int(0, 'Delay Open/Close MA', minval=0, step=1,
tooltip = 'Forces Non-Repainting')
tradeType = input.string('BOTH', 'What trades should be taken : ',
options = )
//=== /INPUTS ===
h = input(false, 'Signals for Heikin Ashi Candles')
//INDICATOR SETTINGS
swing_length = input.int(10, 'Swing High/Low Length', group = 'Settings', minval = 1, maxval = 50)
history_of_demand_to_keep = input.int(20, 'History To Keep', minval = 5, maxval = 50)
box_width = input.float(2.5, 'Supply/Demand Box Width', group = 'Settings', minval = 1, maxval = 10, step = 0.5)
//INDICATOR VISUAL SETTINGS
show_zigzag = input.bool(false, 'Show Zig Zag', group = 'Visual Settings', inline = '1')
show_price_action_labels = input.bool(false, 'Show Price Action Labels', group = 'Visual Settings', inline = '2')
supply_color = input.color(#00000000, 'Supply', group = 'Visual Settings', inline = '3')
supply_outline_color = input.color(#00000000, 'Outline', group = 'Visual Settings', inline = '3')
demand_color = input.color(#00000000, 'Demand', group = 'Visual Settings', inline = '4')
demand_outline_color = input.color(#00000000, 'Outline', group = 'Visual Settings', inline = '4')
bos_label_color = input.color(#00000000, 'BOS Label', group = 'Visual Settings', inline = '5')
poi_label_color = input.color(#00000000, 'POI Label', group = 'Visual Settings', inline = '7')
poi_border_color = input.color(#00000000, 'POI border', group = 'Visual Settings', inline = '7')
swing_type_color = input.color(#00000000, 'Price Action Label', group = 'Visual Settings', inline = '8')
zigzag_color = input.color(#00000000, 'Zig Zag', group = 'Visual Settings', inline = '9')
//END SETTINGS
// FUNCTION TO ADD NEW AND REMOVE LAST IN ARRAY
f_array_add_pop(array, new_value_to_add) =>
array.unshift(array, new_value_to_add)
array.pop(array)
// FUNCTION SWING H & L LABELS
f_sh_sl_labels(array, swing_type) =>
var string label_text = na
if swing_type == 1
if array.get(array, 0) >= array.get(array, 1)
label_text := 'HH'
else
label_text := 'LH'
label.new(
bar_index - swing_length,
array.get(array,0),
text = label_text,
style = label.style_label_down,
textcolor = swing_type_color,
color = swing_type_color,
size = size.tiny)
else if swing_type == -1
if array.get(array, 0) >= array.get(array, 1)
label_text := 'HL'
else
label_text := 'LL'
label.new(
bar_index - swing_length,
array.get(array,0),
text = label_text,
style = label.style_label_up,
textcolor = swing_type_color,
color = swing_type_color,
size = size.tiny)
// FUNCTION MAKE SURE SUPPLY ISNT OVERLAPPING
f_check_overlapping(new_poi, box_array, atrValue) =>
atr_threshold = atrValue * 2
okay_to_draw = true
for i = 0 to array.size(box_array) - 1
top = box.get_top(array.get(box_array, i))
bottom = box.get_bottom(array.get(box_array, i))
poi = (top + bottom) / 2
upper_boundary = poi + atr_threshold
lower_boundary = poi - atr_threshold
if new_poi >= lower_boundary and new_poi <= upper_boundary
okay_to_draw := false
break
else
okay_to_draw := true
okay_to_draw
// FUNCTION TO DRAW SUPPLY OR DEMAND ZONE
f_supply_demand(value_array, bn_array, box_array, label_array, box_type, atrValue) =>
atr_buffer = atrValue * (box_width / 10)
box_left = array.get(bn_array, 0)
box_right = bar_index
var float box_top = 0.00
var float box_bottom = 0.00
var float poi = 0.00
if box_type == 1
box_top := array.get(value_array, 0)
box_bottom := box_top - atr_buffer
poi := (box_top + box_bottom) / 2
else if box_type == -1
box_bottom := array.get(value_array, 0)
box_top := box_bottom + atr_buffer
poi := (box_top + box_bottom) / 2
okay_to_draw = f_check_overlapping(poi, box_array, atrValue)
// okay_to_draw = true
//delete oldest box, and then create a new box and add it to the array
if box_type == 1 and okay_to_draw
box.delete( array.get(box_array, array.size(box_array) - 1) )
f_array_add_pop(box_array, box.new( left = box_left, top = box_top, right = box_right, bottom = box_bottom, border_color = supply_outline_color,
bgcolor = supply_color, extend = extend.right, text = 'SUPPLY', text_halign = text.align_center, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
box.delete( array.get(label_array, array.size(label_array) - 1) )
f_array_add_pop(label_array, box.new( left = box_left, top = poi, right = box_right, bottom = poi, border_color = poi_border_color,
bgcolor = poi_border_color, extend = extend.right, text = 'POI', text_halign = text.align_left, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
else if box_type == -1 and okay_to_draw
box.delete( array.get(box_array, array.size(box_array) - 1) )
f_array_add_pop(box_array, box.new( left = box_left, top = box_top, right = box_right, bottom = box_bottom, border_color = demand_outline_color,
bgcolor = demand_color, extend = extend.right, text = 'DEMAND', text_halign = text.align_center, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
box.delete( array.get(label_array, array.size(label_array) - 1) )
f_array_add_pop(label_array, box.new( left = box_left, top = poi, right = box_right, bottom = poi, border_color = poi_border_color,
bgcolor = poi_border_color, extend = extend.right, text = 'POI', text_halign = text.align_left, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
// FUNCTION TO CHANGE SUPPLY/DEMAND TO A BOS IF BROKEN
f_sd_to_bos(box_array, bos_array, label_array, zone_type) =>
if zone_type == 1
for i = 0 to array.size(box_array) - 1
level_to_break = box.get_top(array.get(box_array,i))
// if ta.crossover(close, level_to_break)
if close >= level_to_break
copied_box = box.copy(array.get(box_array,i))
f_array_add_pop(bos_array, copied_box)
mid = (box.get_top(array.get(box_array,i)) + box.get_bottom(array.get(box_array,i))) / 2
box.set_top(array.get(bos_array,0), mid)
box.set_bottom(array.get(bos_array,0), mid)
box.set_extend( array.get(bos_array,0), extend.none)
box.set_right( array.get(bos_array,0), bar_index)
box.set_text( array.get(bos_array,0), 'BOS' )
box.set_text_color( array.get(bos_array,0), bos_label_color)
box.set_text_size( array.get(bos_array,0), size.small)
box.set_text_halign( array.get(bos_array,0), text.align_center)
box.set_text_valign( array.get(bos_array,0), text.align_center)
box.delete(array.get(box_array, i))
box.delete(array.get(label_array, i))
if zone_type == -1
for i = 0 to array.size(box_array) - 1
level_to_break = box.get_bottom(array.get(box_array,i))
// if ta.crossunder(close, level_to_break)
if close <= level_to_break
copied_box = box.copy(array.get(box_array,i))
f_array_add_pop(bos_array, copied_box)
mid = (box.get_top(array.get(box_array,i)) + box.get_bottom(array.get(box_array,i))) / 2
box.set_top(array.get(bos_array,0), mid)
box.set_bottom(array.get(bos_array,0), mid)
box.set_extend( array.get(bos_array,0), extend.none)
box.set_right( array.get(bos_array,0), bar_index)
box.set_text( array.get(bos_array,0), 'BOS' )
box.set_text_color( array.get(bos_array,0), bos_label_color)
box.set_text_size( array.get(bos_array,0), size.small)
box.set_text_halign( array.get(bos_array,0), text.align_center)
box.set_text_valign( array.get(bos_array,0), text.align_center)
box.delete(array.get(box_array, i))
box.delete(array.get(label_array, i))
// FUNCTION MANAGE CURRENT BOXES BY CHANGING ENDPOINT
f_extend_box_endpoint(box_array) =>
for i = 0 to array.size(box_array) - 1
box.set_right(array.get(box_array, i), bar_index + 100)
//
stratRes = timeframe.ismonthly ? str.tostring(timeframe.multiplier * intRes, '###M') :
timeframe.isweekly ? str.tostring(timeframe.multiplier * intRes, '###W') :
timeframe.isdaily ? str.tostring(timeframe.multiplier * intRes, '###D') :
timeframe.isintraday ? str.tostring(timeframe.multiplier * intRes, '####') :
'60'
src = h ? request.security(ticker.heikinashi(syminfo.tickerid),
timeframe.period, close, lookahead = barmerge.lookahead_off) : close
// CALCULATE ATR
atrValue = ta.atr(50)
// CALCULATE SWING HIGHS & SWING LOWS
swing_high = ta.pivothigh(high, swing_length, swing_length)
swing_low = ta.pivotlow(low, swing_length, swing_length)
// ARRAYS FOR SWING H/L & BN
var swing_high_values = array.new_float(5,0.00)
var swing_low_values = array.new_float(5,0.00)
var swing_high_bns = array.new_int(5,0)
var swing_low_bns = array.new_int(5,0)
// ARRAYS FOR SUPPLY / DEMAND
var current_supply_box = array.new_box(history_of_demand_to_keep, na)
var current_demand_box = array.new_box(history_of_demand_to_keep, na)
// ARRAYS FOR SUPPLY / DEMAND POI LABELS
var current_supply_poi = array.new_box(history_of_demand_to_keep, na)
var current_demand_poi = array.new_box(history_of_demand_to_keep, na)
// ARRAYS FOR BOS
var supply_bos = array.new_box(5, na)
var demand_bos = array.new_box(5, na)
//END CALCULATIONS
// NEW SWING HIGH
if not na(swing_high)
//MANAGE SWING HIGH VALUES
f_array_add_pop(swing_high_values, swing_high)
f_array_add_pop(swing_high_bns, bar_index )
if show_price_action_labels
f_sh_sl_labels(swing_high_values, 1)
f_supply_demand(swing_high_values, swing_high_bns, current_supply_box, current_supply_poi, 1, atrValue)
// NEW SWING LOW
else if not na(swing_low)
//MANAGE SWING LOW VALUES
f_array_add_pop(swing_low_values, swing_low)
f_array_add_pop(swing_low_bns, bar_index )
if show_price_action_labels
f_sh_sl_labels(swing_low_values, -1)
f_supply_demand(swing_low_values, swing_low_bns, current_demand_box, current_demand_poi, -1, atrValue)
f_sd_to_bos(current_supply_box, supply_bos, current_supply_poi, 1)
f_sd_to_bos(current_demand_box, demand_bos, current_demand_poi, -1)
f_extend_box_endpoint(current_supply_box)
f_extend_box_endpoint(current_demand_box)
channelBal = input.bool(false, "Channel Balance", group = "CHART")
lr_slope(_src, _len) =>
x = 0.0, y = 0.0, x2 = 0.0, xy = 0.0
for i = 0 to _len - 1
val = _src
per = i + 1
x += per
y += val
x2 += per * per
xy += val * per
_slp = (_len * xy - x * y) / (_len * x2 - x * x)
_avg = y / _len
_int = _avg - _slp * x / _len + _slp
lr_dev(_src, _len, _slp, _avg, _int) =>
upDev = 0.0, dnDev = 0.0
val = _int
for j = 0 to _len - 1
price = high - val
if price > upDev
upDev := price
price := val - low
if price > dnDev
dnDev := price
price := _src
val += _slp
//
= ta.kc(close, 80, 10.5)
= ta.kc(close, 80, 9.5)
= ta.kc(close, 80, 8)
= ta.kc(close, 80, 3)
barsL = 10
barsR = 10
pivotHigh = fixnan(ta.pivothigh(barsL, barsR) )
pivotLow = fixnan(ta.pivotlow(barsL, barsR) )
source = close, period = 150
= lr_slope(source, period)
= lr_dev(source, period, s, a, i)
y1 = low - (ta.atr(30) * 2), y1B = low - ta.atr(30)
y2 = high + (ta.atr(30) * 2), y2B = high + ta.atr(30)
x1 = bar_index - period + 1, _y1 = i + s * (period - 1), x2 = bar_index, _y2 = i
//Functions
//Line Style function
get_line_style(style) =>
out = switch style
'???' => line.style_solid
'----' => line.style_dashed
' ' => line.style_dotted
//Function to get order block coordinates
get_coordinates(condition, top, btm, ob_val)=>
var ob_top = array.new_float(0)
var ob_btm = array.new_float(0)
var ob_avg = array.new_float(0)
var ob_left = array.new_int(0)
float ob = na
//Append coordinates to arrays
if condition
avg = math.avg(top, btm)
array.unshift(ob_top, top)
array.unshift(ob_btm, btm)
array.unshift(ob_avg, avg)
ob := ob_val
//Function to remove mitigated order blocks from coordinate arrays
remove_mitigated(ob_top, ob_btm, ob_left, ob_avg, target, bull)=>
mitigated = false
target_array = bull ? ob_btm : ob_top
for element in target_array
idx = array.indexof(target_array, element)
if (bull ? target < element : target > element)
mitigated := true
array.remove(ob_top, idx)
array.remove(ob_btm, idx)
array.remove(ob_avg, idx)
array.remove(ob_left, idx)
mitigated
//Function to set order blocks
set_order_blocks(ob_top, ob_btm, ob_left, ob_avg, ext_last, bg_css, border_css, lvl_css)=>
var ob_box = array.new_box(0)
var ob_lvl = array.new_line(0)
//Global elements
var os = 0
var target_bull = 0.
var target_bear = 0.
// Create non-repainting security function
rp_security(_symbol, _res, _src) =>
request.security(_symbol, _res, _src )
htfHigh = rp_security(syminfo.tickerid, res, high)
htfLow = rp_security(syminfo.tickerid, res, low)
// Main Indicator
// Functions
smoothrng(x, t, m) =>
wper = t * 2 - 1
avrng = ta.ema(math.abs(x - x ), t)
smoothrng = ta.ema(avrng, wper) * m
rngfilt(x, r) =>
rngfilt = x
rngfilt := x > nz(rngfilt ) ? x - r < nz(rngfilt ) ? nz(rngfilt ) : x - r : x + r > nz(rngfilt ) ? nz(rngfilt ) : x + r
percWidth(len, perc) => (ta.highest(len) - ta.lowest(len)) * perc / 100
securityNoRep(sym, res, src) => request.security(sym, res, src, barmerge.gaps_off, barmerge.lookahead_on)
swingPoints(prd) =>
pivHi = ta.pivothigh(prd, prd)
pivLo = ta.pivotlow (prd, prd)
last_pivHi = ta.valuewhen(pivHi, pivHi, 1)
last_pivLo = ta.valuewhen(pivLo, pivLo, 1)
hh = pivHi and pivHi > last_pivHi ? pivHi : na
lh = pivHi and pivHi < last_pivHi ? pivHi : na
hl = pivLo and pivLo > last_pivLo ? pivLo : na
ll = pivLo and pivLo < last_pivLo ? pivLo : na
f_chartTfInMinutes() =>
float _resInMinutes = timeframe.multiplier * (
timeframe.isseconds ? 1 :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 60. * 24 :
timeframe.isweekly ? 60. * 24 * 7 :
timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
f_kc(src, len, sensitivity) =>
basis = ta.sma(src, len)
span = ta.atr(len)
wavetrend(src, chlLen, avgLen) =>
esa = ta.ema(src, chlLen)
d = ta.ema(math.abs(src - esa), chlLen)
ci = (src - esa) / (0.015 * d)
wt1 = ta.ema(ci, avgLen)
wt2 = ta.sma(wt1, 3)
f_top_fractal(_src) => _src < _src and _src < _src and _src > _src and _src > _src
f_bot_fractal(_src) => _src > _src and _src > _src and _src < _src and _src < _src
top_fractal = f_top_fractal(src)
bot_fractal = f_bot_fractal(src)
f_fractalize (_src) => top_fractal ? 1 : bot_fractal ? -1 : 0
f_findDivs(src, topLimit, botLimit) =>
fractalTop = f_fractalize(src) > 0 and src >= topLimit ? src : na
fractalBot = f_fractalize(src) < 0 and src <= botLimit ? src : na
highPrev = ta.valuewhen(fractalTop, src , 0)
highPrice = ta.valuewhen(fractalTop, high , 0)
lowPrev = ta.valuewhen(fractalBot, src , 0)
lowPrice = ta.valuewhen(fractalBot, low , 0)
bearSignal = fractalTop and high > highPrice and src < highPrev
bullSignal = fractalBot and low < lowPrice and src > lowPrev
// Get user input
enableSR = input(false , "SR On/Off", group="SR")
colorSup = input(#00000000 , "Support Color", group="SR")
colorRes = input(#00000000 , "Resistance Color", group="SR")
strengthSR = input.int(2 , "S/R Strength", 1, group="SR")
lineStyle = input.string("Dotted", "Line Style", , group="SR")
lineWidth = input.int(2 , "S/R Line Width", 1, group="SR")
useZones = input(true , "Zones On/Off", group="SR")
useHLZones = input(true , "High Low Zones On/Off", group="SR")
zoneWidth = input.int(2 , "Zone Width %", 0,
tooltip = "it's calculated using % of the distance between highest/lowest in last 300 bars", group="SR")
expandSR = input(true , "Expand SR")
// Get components
rb = 10
prd = 284
ChannelW = 10
label_loc = 55
style = lineStyle == "Solid" ? line.style_solid :
lineStyle == "Dotted" ? line.style_dotted : line.style_dashed
ph = ta.pivothigh(rb, rb)
pl = ta.pivotlow (rb, rb)
sr_levels = array.new_float(21, na)
prdhighest = ta.highest(prd)
prdlowest = ta.lowest(prd)
cwidth = percWidth(prd, ChannelW)
zonePerc = percWidth(300, zoneWidth)
aas = array.new_bool(41, true)
u1 = 0.0, u1 := nz(u1 )
d1 = 0.0, d1 := nz(d1 )
highestph = 0.0, highestph := highestph
lowestpl = 0.0, lowestpl := lowestpl
var sr_levs = array.new_float(21, na)
label hlabel = na, label.delete(hlabel )
label llabel = na, label.delete(llabel )
var sr_lines = array.new_line(21, na)
var sr_linesH = array.new_line(21, na)
var sr_linesL = array.new_line(21, na)
var sr_linesF = array.new_linefill(21, na)
var sr_labels = array.new_label(21, na)
if (not na(ph) or not na(pl))
for x = 0 to array.size(sr_levels) - 1
array.set(sr_levels, x, na)
highestph := prdlowest
lowestpl := prdhighest
countpp = 0
for x = 0 to prd
if na(close )
break
if not na(ph ) or not na(pl )
highestph := math.max(highestph, nz(ph , prdlowest), nz(pl , prdlowest))
lowestpl := math.min(lowestpl, nz(ph , prdhighest), nz(pl , prdhighest))
countpp += 1
if countpp > 40
break
if array.get(aas, countpp)
upl = (not na(ph ) and (ph != 0) ? high : low ) + cwidth
dnl = (not na(ph ) and (ph != 0) ? high : low ) - cwidth
u1 := countpp == 1 ? upl : u1
d1 := countpp == 1 ? dnl : d1
tmp = array.new_bool(41, true)
cnt = 0
tpoint = 0
for xx = 0 to prd
if na(close )
break
if not na(ph ) or not na(pl )
chg = false
cnt += 1
if cnt > 40
break
if array.get(aas, cnt)
if not na(ph )
if high <= upl and high >= dnl
tpoint += 1
chg := true
if not na(pl )
if low <= upl and low >= dnl
tpoint += 1
chg := true
if chg and cnt < 41
array.set(tmp, cnt, false)
if tpoint >= strengthSR
for g = 0 to 40 by 1
if not array.get(tmp, g)
array.set(aas, g, false)
if (not na(ph ) and countpp < 21)
array.set(sr_levels, countpp, high )
if (not na(pl ) and countpp < 21)
array.set(sr_levels, countpp, low )
// Plot
var line highest_ = na, line.delete(highest_)
var line lowest_ = na, line.delete(lowest_)
var line highest_fill1 = na, line.delete(highest_fill1)
var line highest_fill2 = na, line.delete(highest_fill2)
var line lowest_fill1 = na, line.delete(lowest_fill1)
var line lowest_fill2 = na, line.delete(lowest_fill2)
hi_col = close >= highestph ? colorSup : colorRes
lo_col = close >= lowestpl ? colorSup : colorRes
if enableSR
highest_ := line.new(bar_index - 311, highestph, bar_index, highestph, xloc.bar_index, expandSR ? extend.both : extend.right, hi_col, style, lineWidth)
lowest_ := line.new(bar_index - 311, lowestpl , bar_index, lowestpl , xloc.bar_index, expandSR ? extend.both : extend.right, lo_col, style, lineWidth)
if useHLZones
highest_fill1 := line.new(bar_index - 311, highestph + zonePerc, bar_index, highestph + zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na)
highest_fill2 := line.new(bar_index - 311, highestph - zonePerc, bar_index, highestph - zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na)
lowest_fill1 := line.new(bar_index - 311, lowestpl + zonePerc , bar_index, lowestpl + zonePerc , xloc.bar_index, expandSR ? extend.both : extend.right, na)
lowest_fill2 := line.new(bar_index - 311, lowestpl - zonePerc , bar_index, lowestpl - zonePerc , xloc.bar_index, expandSR ? extend.both : extend.right, na)
linefill.new(highest_fill1, highest_fill2, hi_col)
linefill.new(lowest_fill1 , lowest_fill2 , lo_col)
if (not na(ph) or not na(pl))
for x = 0 to array.size(sr_lines) - 1
array.set(sr_levs, x, array.get(sr_levels, x))
for x = 0 to array.size(sr_lines) - 1
line.delete(array.get(sr_lines, x))
line.delete(array.get(sr_linesH, x))
line.delete(array.get(sr_linesL, x))
linefill.delete(array.get(sr_linesF, x))
if (not na(array.get(sr_levs, x)) and enableSR)
line_col = close >= array.get(sr_levs, x) ? colorSup : colorRes
array.set(sr_lines, x, line.new(bar_index - 355, array.get(sr_levs, x), bar_index, array.get(sr_levs, x), xloc.bar_index, expandSR ? extend.both : extend.right, line_col, style, lineWidth))
if useZones
array.set(sr_linesH, x, line.new(bar_index - 355, array.get(sr_levs, x) + zonePerc, bar_index, array.get(sr_levs, x) + zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na))
array.set(sr_linesL, x, line.new(bar_index - 355, array.get(sr_levs, x) - zonePerc, bar_index, array.get(sr_levs, x) - zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na))
array.set(sr_linesF, x, linefill.new(array.get(sr_linesH, x), array.get(sr_linesL, x), line_col))
for x = 0 to array.size(sr_labels) - 1
label.delete(array.get(sr_labels, x))
if (not na(array.get(sr_levs, x)) and enableSR)
lab_loc = close >= array.get(sr_levs, x) ? label.style_label_up : label.style_label_down
lab_col = close >= array.get(sr_levs, x) ? colorSup : colorRes
array.set(sr_labels, x, label.new(bar_index + label_loc, array.get(sr_levs, x), str.tostring(math.round_to_mintick(array.get(sr_levs, x))), color=lab_col , textcolor=#000000, style=lab_loc))
hlabel := enableSR ? label.new(bar_index + label_loc + math.round(math.sign(label_loc)) * 20, highestph, "High Level : " + str.tostring(highestph), color=hi_col, textcolor=#000000, style=label.style_label_down) : na
llabel := enableSR ? label.new(bar_index + label_loc + math.round(math.sign(label_loc)) * 20, lowestpl , "Low Level : " + str.tostring(lowestpl) , color=lo_col, textcolor=#000000, style=label.style_label_up ) : na
// Get components
rsi = ta.rsi(close, 28)
//rsiOb = rsi > 78 and rsi > ta.ema(rsi, 10)
//rsiOs = rsi < 27 and rsi < ta.ema(rsi, 10)
rsiOb = rsi > 65 and rsi > ta.ema(rsi, 10)
rsiOs = rsi < 35 and rsi < ta.ema(rsi, 10)
dHigh = securityNoRep(syminfo.tickerid, "D", high )
dLow = securityNoRep(syminfo.tickerid, "D", low )
dClose = securityNoRep(syminfo.tickerid, "D", close )
ema = ta.ema(close, 144)
emaBull = close > ema
equal_tf(res) => str.tonumber(res) == f_chartTfInMinutes() and not timeframe.isseconds
higher_tf(res) => str.tonumber(res) > f_chartTfInMinutes() or timeframe.isseconds
too_small_tf(res) => (timeframe.isweekly and res=="1") or (timeframe.ismonthly and str.tonumber(res) < 10)
securityNoRep1(sym, res, src) =>
bool bull_ = na
bull_ := equal_tf(res) ? src : bull_
bull_ := higher_tf(res) ? request.security(sym, res, src, barmerge.gaps_off, barmerge.lookahead_on) : bull_
bull_array = request.security_lower_tf(syminfo.tickerid, higher_tf(res) ? str.tostring(f_chartTfInMinutes()) + (timeframe.isseconds ? "S" : "") : too_small_tf(res) ? (timeframe.isweekly ? "3" : "10") : res, src)
if array.size(bull_array) > 1 and not equal_tf(res) and not higher_tf(res)
bull_ := array.pop(bull_array)
array.clear(bull_array)
bull_
// === BASE FUNCTIONS ===
// Returns MA input selection variant, default to SMA if blank or typo.
variant(type, src, len, offSig, offALMA) =>
v1 = ta.sma(src, len) // Simple
v2 = ta.ema(src, len) // Exponential
v3 = 2 * v2 - ta.ema(v2, len) // Double Exponential
v4 = 3 * (v2 - ta.ema(v2, len)) + ta.ema(ta.ema(v2, len), len) // Triple Exponential
v5 = ta.wma(src, len) // Weighted
v6 = ta.vwma(src, len) // Volume Weighted
v7 = 0.0
sma_1 = ta.sma(src, len) // Smoothed
v7 := na(v7 ) ? sma_1 : (v7 * (len - 1) + src) / len
v8 = ta.wma(2 * ta.wma(src, len / 2) - ta.wma(src, len), math.round(math.sqrt(len))) // Hull
v9 = ta.linreg(src, len, offSig) // Least Squares
v10 = ta.alma(src, len, offALMA, offSig) // Arnaud Legoux
v11 = ta.sma(v1, len) // Triangular (extreme smooth)
// SuperSmoother filter
// 2013 John F. Ehlers
a1 = math.exp(-1.414 * 3.14159 / len)
b1 = 2 * a1 * math.cos(1.414 * 3.14159 / len)
c2 = b1
c3 = -a1 * a1
c1 = 1 - c2 - c3
v12 = 0.0
v12 := c1 * (src + nz(src )) / 2 + c2 * nz(v12 ) + c3 * nz(v12 )
type == 'EMA' ? v2 : type == 'DEMA' ? v3 : type == 'TEMA' ? v4 : type == 'WMA' ? v5 : type == 'VWMA' ? v6 : type == 'SMMA' ? v7 : type == 'HullMA' ? v8 : type == 'LSMA' ? v9 : type == 'ALMA' ? v10 : type == 'TMA' ? v11 : type == 'SSMA' ? v12 : v1
// security wrapper for repeat calls
reso(exp, use, res) =>
security_1 = request.security(syminfo.tickerid, res, exp, gaps = barmerge.gaps_off, lookahead = barmerge.lookahead_on)
use ? security_1 : exp
// === /BASE FUNCTIONS ===
// === SERIES SETUP ===
closeSeries = variant(basisType, close , basisLen, offsetSigma, offsetALMA)
openSeries = variant(basisType, open , basisLen, offsetSigma, offsetALMA)
// === /SERIES ===
// Get Alternate resolution Series if selected.
closeSeriesAlt = reso(closeSeries, useRes, stratRes)
openSeriesAlt = reso(openSeries, useRes, stratRes)
//
lxTrigger = false
sxTrigger = false
leTrigger = ta.crossover (closeSeriesAlt, openSeriesAlt)
seTrigger = ta.crossunder(closeSeriesAlt, openSeriesAlt)
G_RISK = '■ ' + 'Risk Management'
//#region ———— <↓↓↓ G_RISK ↓↓↓> {
// ———————————
//Tooltip
T_LVL = '(%) Exit Level'
T_QTY = '(%) Adjust trade exit volume'
T_MSG = 'Paste JSON message for your bot'
//Webhook Message
O_LEMSG = 'Long Entry'
O_LXMSGSL = 'Long SL'
O_LXMSGTP1 = 'Long TP1'
O_LXMSGTP2 = 'Long TP2'
O_LXMSGTP3 = 'Long TP3'
O_LXMSG = 'Long Exit'
O_SEMSG = 'Short Entry'
O_SXMSGSL = 'Short SL'
O_SXMSGA = 'Short TP1'
O_SXMSGB = 'Short TP2'
O_SXMSGC = 'Short TP3'
O_SXMSGX = 'Short Exit'
// ——————————— | | | Line length guide |
i_lxLvlTP1 = input.float (0.2, 'Level TP1' , group = G_RISK,
tooltip = T_LVL)
i_lxQtyTP1 = input.float (80.0, 'Qty TP1' , group = G_RISK,
tooltip = T_QTY)
i_lxLvlTP2 = input.float (0.5, 'Level TP2' , group = G_RISK,
tooltip = T_LVL)
i_lxQtyTP2 = input.float (10.0, 'Qty TP2' , group = G_RISK,
tooltip = T_QTY)
i_lxLvlTP3 = input.float (7.0, 'Level TP3' , group = G_RISK,
tooltip = T_LVL)
i_lxQtyTP3 = input.float (2, 'Qty TP3' , group = G_RISK,
tooltip = T_QTY)
i_lxLvlSL = input.float (0.5, 'Stop Loss' , group = G_RISK,
tooltip = T_LVL)
i_sxLvlTP1 = i_lxLvlTP1
i_sxQtyTP1 = i_lxQtyTP1
i_sxLvlTP2 = i_lxLvlTP2
i_sxQtyTP2 = i_lxQtyTP2
i_sxLvlTP3 = i_lxLvlTP3
i_sxQtyTP3 = i_lxQtyTP3
i_sxLvlSL = i_lxLvlSL
G_MSG = '■ ' + 'Webhook Message'
i_leMsg = input.string (O_LEMSG ,'Long Entry' , group = G_MSG, tooltip = T_MSG)
i_lxMsgSL = input.string (O_LXMSGSL ,'Long SL' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP1 = input.string (O_LXMSGTP1,'Long TP1' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP2 = input.string (O_LXMSGTP2,'Long TP2' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP3 = input.string (O_LXMSGTP3,'Long TP3' , group = G_MSG, tooltip = T_MSG)
i_lxMsg = input.string (O_LXMSG ,'Long Exit' , group = G_MSG, tooltip = T_MSG)
i_seMsg = input.string (O_SEMSG ,'Short Entry' , group = G_MSG, tooltip = T_MSG)
i_sxMsgSL = input.string (O_SXMSGSL ,'Short SL' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP1 = input.string (O_SXMSGA ,'Short TP1' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP2 = input.string (O_SXMSGB ,'Short TP2' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP3 = input.string (O_SXMSGC ,'Short TP3' , group = G_MSG, tooltip = T_MSG)
i_sxMsg = input.string (O_SXMSGX ,'Short Exit' , group = G_MSG, tooltip = T_MSG)
i_src = close
G_DISPLAY = 'Display'
//
i_alertOn = input.bool (true, 'Alert Labels On/Off' , group = G_DISPLAY)
i_barColOn = input.bool (true, 'Bar Color On/Off' , group = G_DISPLAY)
// ———————————
// @function Calculate the Take Profit line, and the crossover or crossunder
f_tp(_condition, _conditionValue, _leTrigger, _seTrigger, _src, _lxLvlTP, _sxLvlTP)=>
var float _tpLine = 0.0
_topLvl = _src + (_src * (_lxLvlTP / 100))
_botLvl = _src - (_src * (_sxLvlTP / 100))
_tpLine := _condition != _conditionValue and _leTrigger ? _topLvl :
_condition != -_conditionValue and _seTrigger ? _botLvl :
nz(_tpLine )
// @function Similar to "ta.crossover" or "ta.crossunder"
f_cross(_scr1, _scr2, _over)=>
_cross = _over ? _scr1 > _scr2 and _scr1 < _scr2 :
_scr1 < _scr2 and _scr1 > _scr2
// ———————————
//
var float condition = 0.0
var float slLine = 0.0
var float entryLine = 0.0
//
entryLine := leTrigger and condition <= 0.0 ? close :
seTrigger and condition >= 0.0 ? close : nz(entryLine )
//
slTopLvl = i_src + (i_src * (i_lxLvlSL / 100))
slBotLvl = i_src - (i_src * (i_sxLvlSL / 100))
slLine := condition <= 0.0 and leTrigger ? slBotLvl :
condition >= 0.0 and seTrigger ? slTopLvl : nz(slLine )
slLong = f_cross(low, slLine, false)
slShort = f_cross(high, slLine, true )
//
= f_tp(condition, 1.2,leTrigger, seTrigger, i_src, i_lxLvlTP3, i_sxLvlTP3)
= f_tp(condition, 1.1,leTrigger, seTrigger, i_src, i_lxLvlTP2, i_sxLvlTP2)
= f_tp(condition, 1.0,leTrigger, seTrigger, i_src, i_lxLvlTP1, i_sxLvlTP1)
tp3Long = f_cross(high, tp3Line, true )
tp3Short = f_cross(low, tp3Line, false)
tp2Long = f_cross(high, tp2Line, true )
tp2Short = f_cross(low, tp2Line, false)
tp1Long = f_cross(high, tp1Line, true )
tp1Short = f_cross(low, tp1Line, false)
switch
leTrigger and condition <= 0.0 => condition := 1.0
seTrigger and condition >= 0.0 => condition := -1.0
tp3Long and condition == 1.2 => condition := 1.3
tp3Short and condition == -1.2 => condition := -1.3
tp2Long and condition == 1.1 => condition := 1.2
tp2Short and condition == -1.1 => condition := -1.2
tp1Long and condition == 1.0 => condition := 1.1
tp1Short and condition == -1.0 => condition := -1.1
slLong and condition >= 1.0 => condition := 0.0
slShort and condition <= -1.0 => condition := 0.0
lxTrigger and condition >= 1.0 => condition := 0.0
sxTrigger and condition <= -1.0 => condition := 0.0
longE = leTrigger and condition <= 0.0 and condition == 1.0
shortE = seTrigger and condition >= 0.0 and condition == -1.0
longX = lxTrigger and condition >= 1.0 and condition == 0.0
shortX = sxTrigger and condition <= -1.0 and condition == 0.0
longSL = slLong and condition >= 1.0 and condition == 0.0
shortSL = slShort and condition <= -1.0 and condition == 0.0
longTP3 = tp3Long and condition == 1.2 and condition == 1.3
shortTP3 = tp3Short and condition == -1.2 and condition == -1.3
longTP2 = tp2Long and condition == 1.1 and condition == 1.2
shortTP2 = tp2Short and condition == -1.1 and condition == -1.2
longTP1 = tp1Long and condition == 1.0 and condition == 1.1
shortTP1 = tp1Short and condition == -1.0 and condition == -1.1
// ——————————— {
//
if strategy.position_size <= 0 and longE and barstate.isconfirmed
strategy.entry(
'Long',
strategy.long,
alert_message = i_leMsg,
comment = 'LE')
if strategy.position_size > 0 and condition == 1.0
strategy.exit(
id = 'LXTP1',
from_entry = 'Long',
qty_percent = i_lxQtyTP1,
limit = tp1Line,
stop = slLine,
comment_profit = 'LXTP1',
comment_loss = 'SL',
alert_profit = i_lxMsgTP1,
alert_loss = i_lxMsgSL)
if strategy.position_size > 0 and condition == 1.1
strategy.exit(
id = 'LXTP2',
from_entry = 'Long',
qty_percent = i_lxQtyTP2,
limit = tp2Line,
stop = slLine,
comment_profit = 'LXTP2',
comment_loss = 'SL',
alert_profit = i_lxMsgTP2,
alert_loss = i_lxMsgSL)
if strategy.position_size > 0 and condition == 1.2
strategy.exit(
id = 'LXTP3',
from_entry = 'Long',
qty_percent = i_lxQtyTP3,
limit = tp3Line,
stop = slLine,
comment_profit = 'LXTP3',
comment_loss = 'SL',
alert_profit = i_lxMsgTP3,
alert_loss = i_lxMsgSL)
if longX
strategy.close(
'Long',
alert_message = i_lxMsg,
comment = 'LX')
//
if strategy.position_size >= 0 and shortE and barstate.isconfirmed
strategy.entry(
'Short',
strategy.short,
alert_message = i_leMsg,
comment = 'SE')
if strategy.position_size < 0 and condition == -1.0
strategy.exit(
id = 'SXTP1',
from_entry = 'Short',
qty_percent = i_sxQtyTP1,
limit = tp1Line,
stop = slLine,
comment_profit = 'SXTP1',
comment_loss = 'SL',
alert_profit = i_sxMsgTP1,
alert_loss = i_sxMsgSL)
if strategy.position_size < 0 and condition == -1.1
strategy.exit(
id = 'SXTP2',
from_entry = 'Short',
qty_percent = i_sxQtyTP2,
limit = tp2Line,
stop = slLine,
comment_profit = 'SXTP2',
comment_loss = 'SL',
alert_profit = i_sxMsgTP2,
alert_loss = i_sxMsgSL)
if strategy.position_size < 0 and condition == -1.2
strategy.exit(
id = 'SXTP3',
from_entry = 'Short',
qty_percent = i_sxQtyTP3,
limit = tp3Line,
stop = slLine,
comment_profit = 'SXTP3',
comment_loss = 'SL',
alert_profit = i_sxMsgTP3,
alert_loss = i_sxMsgSL)
if shortX
strategy.close(
'Short',
alert_message = i_sxMsg,
comment = 'SX')
// ———————————
c_tp = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.green
c_entry = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.blue
c_sl = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.red
p_tp1Line = plot (
condition == 1.0 or
condition == -1.0 ? tp1Line : na,
title = "TP Line 1",
color = c_tp,
linewidth = 1,
style = plot.style_linebr)
p_tp2Line = plot (
condition == 1.0 or
condition == -1.0 or
condition == 1.1 or
condition == -1.1 ? tp2Line : na,
title = "TP Line 2",
color = c_tp,
linewidth = 1,
style = plot.style_linebr)
p_tp3Line = plot (
condition == 1.0 or
condition == -1.0 or
condition == 1.1 or
condition == -1.1 or
condition == 1.2 or
condition == -1.2 ? tp3Line : na,
title = "TP Line 3",
color = c_tp,
linewidth = 1,
style = plot.style_linebr)
p_entryLine = plot (
condition >= 1.0 or
condition <= -1.0 ? entryLine : na,
title = "Entry Line",
color = c_entry,
linewidth = 1,
style = plot.style_linebr)
p_slLine = plot (
condition == 1.0 or
condition == -1.0 or
condition == 1.1 or
condition == -1.1 or
condition == 1.2 or
condition == -1.2 ? slLine : na,
title = "SL Line",
color = c_sl,
linewidth = 1,
style = plot.style_linebr)
fill(
p_tp3Line, p_entryLine,
color = leTrigger or seTrigger ? na :color.new(color.green, 90))
fill(
p_entryLine, p_slLine,
color = leTrigger or seTrigger ? na :color.new(color.red, 90))
//
plotshape(
i_alertOn and longE,
title = 'Long',
text = 'Long',
textcolor = color.white,
color = color.green,
style = shape.labelup,
size = size.tiny,
location = location.belowbar)
plotshape(
i_alertOn and shortE,
title = 'Short',
text = 'Short',
textcolor = color.white,
color = color.red,
style = shape.labeldown,
size = size.tiny,
location = location.abovebar)
plotshape(
i_alertOn and (longX or shortX) ? close : na,
title = 'Close',
text = 'Close',
textcolor = color.white,
color = color.gray,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
l_tp = i_alertOn and (longTP1 or shortTP1) ? close : na
plotshape(
l_tp,
title = "TP1 Cross",
text = "TP1",
textcolor = color.white,
color = color.olive,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
plotshape(
i_alertOn and (longTP2 or shortTP2) ? close : na,
title = "TP2 Cross",
text = "TP2",
textcolor = color.white,
color = color.olive,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
plotshape(
i_alertOn and (longTP3 or shortTP3) ? close : na,
title = "TP3 Cross",
text = "TP3",
textcolor = color.white,
color = color.olive,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
plotshape(
i_alertOn and (longSL or shortSL) ? close : na,
title = "SL Cross",
text = "SL",
textcolor = color.white,
color = color.maroon,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
//
plot(
na,
title = "─── ───",
editable = false,
display = display.data_window)
plot(
condition,
title = "condition",
editable = false,
display = display.data_window)
plot(
strategy.position_size * 100,
title = ".position_size",
editable = false,
display = display.data_window)
//#endregion }
// ——————————— <↑↑↑ G_RISK ↑↑↑>
//#region ———— <↓↓↓ G_SCRIPT02 ↓↓↓> {
// @function Queues a new element in an array and de-queues its first element.
f_qDq(_array, _val) =>
array.push(_array, _val)
_return = array.shift(_array)
_return
var line a_slLine = array.new_line(1)
var line a_entryLine = array.new_line(1)
var line a_tp3Line = array.new_line(1)
var line a_tp2Line = array.new_line(1)
var line a_tp1Line = array.new_line(1)
var label a_slLabel = array.new_label(1)
var label a_tp3label = array.new_label(1)
var label a_tp2label = array.new_label(1)
var label a_tp1label = array.new_label(1)
var label a_entryLabel = array.new_label(1)
newEntry = longE or shortE
entryIndex = 1
entryIndex := newEntry ? bar_index : nz(entryIndex )
lasTrade = bar_index >= entryIndex
l_right = 10
line.delete(
f_qDq(a_slLine,
line.new(
entryIndex,
slLine,
last_bar_index + l_right,
slLine,
style = line.style_solid,
color = c_sl)))
line.delete(
f_qDq(a_entryLine,
line.new(
entryIndex,
entryLine,
last_bar_index + l_right,
entryLine,
style = line.style_solid,
color = color.blue)))
line.delete(
f_qDq(a_tp3Line,
line.new(
entryIndex,
tp3Line,
last_bar_index + l_right,
tp3Line,
style = line.style_solid,
color = c_tp)))
line.delete(
f_qDq(a_tp2Line,
line.new(
entryIndex,
tp2Line,
last_bar_index + l_right,
tp2Line,
style = line.style_solid,
color = c_tp)))
line.delete(
f_qDq(a_tp1Line,
line.new(
entryIndex,
tp1Line,
last_bar_index + l_right,
tp1Line,
style = line.style_solid,
color = c_tp)))
label.delete(
f_qDq(a_slLabel,
label.new(
last_bar_index + l_right,
slLine,
'SL: ' + str.tostring(slLine, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_sl)))
label.delete(
f_qDq(a_entryLabel,
label.new(
last_bar_index + l_right,
entryLine,
'Entry: ' + str.tostring(entryLine, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = color.blue)))
label.delete(
f_qDq(a_tp3label,
label.new(
last_bar_index + l_right,
tp3Line,
'TP3: ' + str.tostring(tp3Line, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_tp)))
label.delete(
f_qDq(a_tp2label,
label.new(
last_bar_index + l_right,
tp2Line,
'TP2: ' + str.tostring(tp2Line, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_tp)))
label.delete(
f_qDq(a_tp1label,
label.new(
last_bar_index + l_right,
tp1Line,
'TP1: ' + str.tostring(tp1Line, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_tp)))
// ———————————
//
if longE or shortE or longX or shortX
alert(message = 'Any Alert', freq = alert.freq_once_per_bar_close)
if longE
alert(message = 'Long Entry', freq = alert.freq_once_per_bar_close)
if shortE
alert(message = 'Short Entry', freq = alert.freq_once_per_bar_close)
if longX
alert(message = 'Long Exit', freq = alert.freq_once_per_bar_close)
if shortX
alert(message = 'Short Exit', freq = alert.freq_once_per_bar_close)
//#endregion }
// ——————————— <↑↑↑ G_SCRIPT03 ↑↑↑>
Мой скрипт// © Buzzara
// =================================
// PLEASE SUPPORT THE TEAM
// =================================
//
// Telegram: t.me
a_trade// =================================
//@version=5
VERSION = ' Buzzara2.0'
strategy('ALGOX V6_1_24', shorttitle = '🚀〄 Buzzara2.0 〄🚀'+ VERSION, overlay = true, explicit_plot_zorder = true, pyramiding = 0, default_qty_type = strategy.percent_of_equity, initial_capital = 1000, default_qty_value = 1, calc_on_every_tick = false, process_orders_on_close = true)
G_SCRIPT01 = '■ ' + 'SAIYAN OCC'
//#region ———— <↓↓↓ G_SCRIPT01 ↓↓↓> {
// === INPUTS ===
res = input.timeframe('15', 'TIMEFRAME', group ="NON REPAINT")
useRes = input(true, 'Use Alternate Signals')
intRes = input(10, 'Multiplier for Alernate Signals')
basisType = input.string('ALMA', 'MA Type: ', options= )
basisLen = input.int(50, 'MA Period', minval=1)
offsetSigma = input.int(5, 'Offset for LSMA / Sigma for ALMA', minval=0)
offsetALMA = input.float(2, 'Offset for ALMA', minval=0, step=0.01)
scolor = input(false, 'Show coloured Bars to indicate Trend?')
delayOffset = input.int(0, 'Delay Open/Close MA', minval=0, step=1,
tooltip = 'Forces Non-Repainting')
tradeType = input.string('BOTH', 'What trades should be taken : ',
options = )
//=== /INPUTS ===
h = input(false, 'Signals for Heikin Ashi Candles')
//INDICATOR SETTINGS
swing_length = input.int(10, 'Swing High/Low Length', group = 'Settings', minval = 1, maxval = 50)
history_of_demand_to_keep = input.int(20, 'History To Keep', minval = 5, maxval = 50)
box_width = input.float(2.5, 'Supply/Demand Box Width', group = 'Settings', minval = 1, maxval = 10, step = 0.5)
//INDICATOR VISUAL SETTINGS
show_zigzag = input.bool(false, 'Show Zig Zag', group = 'Visual Settings', inline = '1')
show_price_action_labels = input.bool(false, 'Show Price Action Labels', group = 'Visual Settings', inline = '2')
supply_color = input.color(#00000000, 'Supply', group = 'Visual Settings', inline = '3')
supply_outline_color = input.color(#00000000, 'Outline', group = 'Visual Settings', inline = '3')
demand_color = input.color(#00000000, 'Demand', group = 'Visual Settings', inline = '4')
demand_outline_color = input.color(#00000000, 'Outline', group = 'Visual Settings', inline = '4')
bos_label_color = input.color(#00000000, 'BOS Label', group = 'Visual Settings', inline = '5')
poi_label_color = input.color(#00000000, 'POI Label', group = 'Visual Settings', inline = '7')
poi_border_color = input.color(#00000000, 'POI border', group = 'Visual Settings', inline = '7')
swing_type_color = input.color(#00000000, 'Price Action Label', group = 'Visual Settings', inline = '8')
zigzag_color = input.color(#00000000, 'Zig Zag', group = 'Visual Settings', inline = '9')
//END SETTINGS
// FUNCTION TO ADD NEW AND REMOVE LAST IN ARRAY
f_array_add_pop(array, new_value_to_add) =>
array.unshift(array, new_value_to_add)
array.pop(array)
// FUNCTION SWING H & L LABELS
f_sh_sl_labels(array, swing_type) =>
var string label_text = na
if swing_type == 1
if array.get(array, 0) >= array.get(array, 1)
label_text := 'HH'
else
label_text := 'LH'
label.new(
bar_index - swing_length,
array.get(array,0),
text = label_text,
style = label.style_label_down,
textcolor = swing_type_color,
color = swing_type_color,
size = size.tiny)
else if swing_type == -1
if array.get(array, 0) >= array.get(array, 1)
label_text := 'HL'
else
label_text := 'LL'
label.new(
bar_index - swing_length,
array.get(array,0),
text = label_text,
style = label.style_label_up,
textcolor = swing_type_color,
color = swing_type_color,
size = size.tiny)
// FUNCTION MAKE SURE SUPPLY ISNT OVERLAPPING
f_check_overlapping(new_poi, box_array, atrValue) =>
atr_threshold = atrValue * 2
okay_to_draw = true
for i = 0 to array.size(box_array) - 1
top = box.get_top(array.get(box_array, i))
bottom = box.get_bottom(array.get(box_array, i))
poi = (top + bottom) / 2
upper_boundary = poi + atr_threshold
lower_boundary = poi - atr_threshold
if new_poi >= lower_boundary and new_poi <= upper_boundary
okay_to_draw := false
break
else
okay_to_draw := true
okay_to_draw
// FUNCTION TO DRAW SUPPLY OR DEMAND ZONE
f_supply_demand(value_array, bn_array, box_array, label_array, box_type, atrValue) =>
atr_buffer = atrValue * (box_width / 10)
box_left = array.get(bn_array, 0)
box_right = bar_index
var float box_top = 0.00
var float box_bottom = 0.00
var float poi = 0.00
if box_type == 1
box_top := array.get(value_array, 0)
box_bottom := box_top - atr_buffer
poi := (box_top + box_bottom) / 2
else if box_type == -1
box_bottom := array.get(value_array, 0)
box_top := box_bottom + atr_buffer
poi := (box_top + box_bottom) / 2
okay_to_draw = f_check_overlapping(poi, box_array, atrValue)
// okay_to_draw = true
//delete oldest box, and then create a new box and add it to the array
if box_type == 1 and okay_to_draw
box.delete( array.get(box_array, array.size(box_array) - 1) )
f_array_add_pop(box_array, box.new( left = box_left, top = box_top, right = box_right, bottom = box_bottom, border_color = supply_outline_color,
bgcolor = supply_color, extend = extend.right, text = 'SUPPLY', text_halign = text.align_center, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
box.delete( array.get(label_array, array.size(label_array) - 1) )
f_array_add_pop(label_array, box.new( left = box_left, top = poi, right = box_right, bottom = poi, border_color = poi_border_color,
bgcolor = poi_border_color, extend = extend.right, text = 'POI', text_halign = text.align_left, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
else if box_type == -1 and okay_to_draw
box.delete( array.get(box_array, array.size(box_array) - 1) )
f_array_add_pop(box_array, box.new( left = box_left, top = box_top, right = box_right, bottom = box_bottom, border_color = demand_outline_color,
bgcolor = demand_color, extend = extend.right, text = 'DEMAND', text_halign = text.align_center, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
box.delete( array.get(label_array, array.size(label_array) - 1) )
f_array_add_pop(label_array, box.new( left = box_left, top = poi, right = box_right, bottom = poi, border_color = poi_border_color,
bgcolor = poi_border_color, extend = extend.right, text = 'POI', text_halign = text.align_left, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
// FUNCTION TO CHANGE SUPPLY/DEMAND TO A BOS IF BROKEN
f_sd_to_bos(box_array, bos_array, label_array, zone_type) =>
if zone_type == 1
for i = 0 to array.size(box_array) - 1
level_to_break = box.get_top(array.get(box_array,i))
// if ta.crossover(close, level_to_break)
if close >= level_to_break
copied_box = box.copy(array.get(box_array,i))
f_array_add_pop(bos_array, copied_box)
mid = (box.get_top(array.get(box_array,i)) + box.get_bottom(array.get(box_array,i))) / 2
box.set_top(array.get(bos_array,0), mid)
box.set_bottom(array.get(bos_array,0), mid)
box.set_extend( array.get(bos_array,0), extend.none)
box.set_right( array.get(bos_array,0), bar_index)
box.set_text( array.get(bos_array,0), 'BOS' )
box.set_text_color( array.get(bos_array,0), bos_label_color)
box.set_text_size( array.get(bos_array,0), size.small)
box.set_text_halign( array.get(bos_array,0), text.align_center)
box.set_text_valign( array.get(bos_array,0), text.align_center)
box.delete(array.get(box_array, i))
box.delete(array.get(label_array, i))
if zone_type == -1
for i = 0 to array.size(box_array) - 1
level_to_break = box.get_bottom(array.get(box_array,i))
// if ta.crossunder(close, level_to_break)
if close <= level_to_break
copied_box = box.copy(array.get(box_array,i))
f_array_add_pop(bos_array, copied_box)
mid = (box.get_top(array.get(box_array,i)) + box.get_bottom(array.get(box_array,i))) / 2
box.set_top(array.get(bos_array,0), mid)
box.set_bottom(array.get(bos_array,0), mid)
box.set_extend( array.get(bos_array,0), extend.none)
box.set_right( array.get(bos_array,0), bar_index)
box.set_text( array.get(bos_array,0), 'BOS' )
box.set_text_color( array.get(bos_array,0), bos_label_color)
box.set_text_size( array.get(bos_array,0), size.small)
box.set_text_halign( array.get(bos_array,0), text.align_center)
box.set_text_valign( array.get(bos_array,0), text.align_center)
box.delete(array.get(box_array, i))
box.delete(array.get(label_array, i))
// FUNCTION MANAGE CURRENT BOXES BY CHANGING ENDPOINT
f_extend_box_endpoint(box_array) =>
for i = 0 to array.size(box_array) - 1
box.set_right(array.get(box_array, i), bar_index + 100)
//
stratRes = timeframe.ismonthly ? str.tostring(timeframe.multiplier * intRes, '###M') :
timeframe.isweekly ? str.tostring(timeframe.multiplier * intRes, '###W') :
timeframe.isdaily ? str.tostring(timeframe.multiplier * intRes, '###D') :
timeframe.isintraday ? str.tostring(timeframe.multiplier * intRes, '####') :
'60'
src = h ? request.security(ticker.heikinashi(syminfo.tickerid),
timeframe.period, close, lookahead = barmerge.lookahead_off) : close
// CALCULATE ATR
atrValue = ta.atr(50)
// CALCULATE SWING HIGHS & SWING LOWS
swing_high = ta.pivothigh(high, swing_length, swing_length)
swing_low = ta.pivotlow(low, swing_length, swing_length)
// ARRAYS FOR SWING H/L & BN
var swing_high_values = array.new_float(5,0.00)
var swing_low_values = array.new_float(5,0.00)
var swing_high_bns = array.new_int(5,0)
var swing_low_bns = array.new_int(5,0)
// ARRAYS FOR SUPPLY / DEMAND
var current_supply_box = array.new_box(history_of_demand_to_keep, na)
var current_demand_box = array.new_box(history_of_demand_to_keep, na)
// ARRAYS FOR SUPPLY / DEMAND POI LABELS
var current_supply_poi = array.new_box(history_of_demand_to_keep, na)
var current_demand_poi = array.new_box(history_of_demand_to_keep, na)
// ARRAYS FOR BOS
var supply_bos = array.new_box(5, na)
var demand_bos = array.new_box(5, na)
//END CALCULATIONS
// NEW SWING HIGH
if not na(swing_high)
//MANAGE SWING HIGH VALUES
f_array_add_pop(swing_high_values, swing_high)
f_array_add_pop(swing_high_bns, bar_index )
if show_price_action_labels
f_sh_sl_labels(swing_high_values, 1)
f_supply_demand(swing_high_values, swing_high_bns, current_supply_box, current_supply_poi, 1, atrValue)
// NEW SWING LOW
else if not na(swing_low)
//MANAGE SWING LOW VALUES
f_array_add_pop(swing_low_values, swing_low)
f_array_add_pop(swing_low_bns, bar_index )
if show_price_action_labels
f_sh_sl_labels(swing_low_values, -1)
f_supply_demand(swing_low_values, swing_low_bns, current_demand_box, current_demand_poi, -1, atrValue)
f_sd_to_bos(current_supply_box, supply_bos, current_supply_poi, 1)
f_sd_to_bos(current_demand_box, demand_bos, current_demand_poi, -1)
f_extend_box_endpoint(current_supply_box)
f_extend_box_endpoint(current_demand_box)
channelBal = input.bool(false, "Channel Balance", group = "CHART")
lr_slope(_src, _len) =>
x = 0.0, y = 0.0, x2 = 0.0, xy = 0.0
for i = 0 to _len - 1
val = _src
per = i + 1
x += per
y += val
x2 += per * per
xy += val * per
_slp = (_len * xy - x * y) / (_len * x2 - x * x)
_avg = y / _len
_int = _avg - _slp * x / _len + _slp
lr_dev(_src, _len, _slp, _avg, _int) =>
upDev = 0.0, dnDev = 0.0
val = _int
for j = 0 to _len - 1
price = high - val
if price > upDev
upDev := price
price := val - low
if price > dnDev
dnDev := price
price := _src
val += _slp
//
= ta.kc(close, 80, 10.5)
= ta.kc(close, 80, 9.5)
= ta.kc(close, 80, 8)
= ta.kc(close, 80, 3)
barsL = 10
barsR = 10
pivotHigh = fixnan(ta.pivothigh(barsL, barsR) )
pivotLow = fixnan(ta.pivotlow(barsL, barsR) )
source = close, period = 150
= lr_slope(source, period)
= lr_dev(source, period, s, a, i)
y1 = low - (ta.atr(30) * 2), y1B = low - ta.atr(30)
y2 = high + (ta.atr(30) * 2), y2B = high + ta.atr(30)
x1 = bar_index - period + 1, _y1 = i + s * (period - 1), x2 = bar_index, _y2 = i
//Functions
//Line Style function
get_line_style(style) =>
out = switch style
'???' => line.style_solid
'----' => line.style_dashed
' ' => line.style_dotted
//Function to get order block coordinates
get_coordinates(condition, top, btm, ob_val)=>
var ob_top = array.new_float(0)
var ob_btm = array.new_float(0)
var ob_avg = array.new_float(0)
var ob_left = array.new_int(0)
float ob = na
//Append coordinates to arrays
if condition
avg = math.avg(top, btm)
array.unshift(ob_top, top)
array.unshift(ob_btm, btm)
array.unshift(ob_avg, avg)
ob := ob_val
//Function to remove mitigated order blocks from coordinate arrays
remove_mitigated(ob_top, ob_btm, ob_left, ob_avg, target, bull)=>
mitigated = false
target_array = bull ? ob_btm : ob_top
for element in target_array
idx = array.indexof(target_array, element)
if (bull ? target < element : target > element)
mitigated := true
array.remove(ob_top, idx)
array.remove(ob_btm, idx)
array.remove(ob_avg, idx)
array.remove(ob_left, idx)
mitigated
//Function to set order blocks
set_order_blocks(ob_top, ob_btm, ob_left, ob_avg, ext_last, bg_css, border_css, lvl_css)=>
var ob_box = array.new_box(0)
var ob_lvl = array.new_line(0)
//Global elements
var os = 0
var target_bull = 0.
var target_bear = 0.
// Create non-repainting security function
rp_security(_symbol, _res, _src) =>
request.security(_symbol, _res, _src )
htfHigh = rp_security(syminfo.tickerid, res, high)
htfLow = rp_security(syminfo.tickerid, res, low)
// Main Indicator
// Functions
smoothrng(x, t, m) =>
wper = t * 2 - 1
avrng = ta.ema(math.abs(x - x ), t)
smoothrng = ta.ema(avrng, wper) * m
rngfilt(x, r) =>
rngfilt = x
rngfilt := x > nz(rngfilt ) ? x - r < nz(rngfilt ) ? nz(rngfilt ) : x - r : x + r > nz(rngfilt ) ? nz(rngfilt ) : x + r
percWidth(len, perc) => (ta.highest(len) - ta.lowest(len)) * perc / 100
securityNoRep(sym, res, src) => request.security(sym, res, src, barmerge.gaps_off, barmerge.lookahead_on)
swingPoints(prd) =>
pivHi = ta.pivothigh(prd, prd)
pivLo = ta.pivotlow (prd, prd)
last_pivHi = ta.valuewhen(pivHi, pivHi, 1)
last_pivLo = ta.valuewhen(pivLo, pivLo, 1)
hh = pivHi and pivHi > last_pivHi ? pivHi : na
lh = pivHi and pivHi < last_pivHi ? pivHi : na
hl = pivLo and pivLo > last_pivLo ? pivLo : na
ll = pivLo and pivLo < last_pivLo ? pivLo : na
f_chartTfInMinutes() =>
float _resInMinutes = timeframe.multiplier * (
timeframe.isseconds ? 1 :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 60. * 24 :
timeframe.isweekly ? 60. * 24 * 7 :
timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
f_kc(src, len, sensitivity) =>
basis = ta.sma(src, len)
span = ta.atr(len)
wavetrend(src, chlLen, avgLen) =>
esa = ta.ema(src, chlLen)
d = ta.ema(math.abs(src - esa), chlLen)
ci = (src - esa) / (0.015 * d)
wt1 = ta.ema(ci, avgLen)
wt2 = ta.sma(wt1, 3)
f_top_fractal(_src) => _src < _src and _src < _src and _src > _src and _src > _src
f_bot_fractal(_src) => _src > _src and _src > _src and _src < _src and _src < _src
top_fractal = f_top_fractal(src)
bot_fractal = f_bot_fractal(src)
f_fractalize (_src) => top_fractal ? 1 : bot_fractal ? -1 : 0
f_findDivs(src, topLimit, botLimit) =>
fractalTop = f_fractalize(src) > 0 and src >= topLimit ? src : na
fractalBot = f_fractalize(src) < 0 and src <= botLimit ? src : na
highPrev = ta.valuewhen(fractalTop, src , 0)
highPrice = ta.valuewhen(fractalTop, high , 0)
lowPrev = ta.valuewhen(fractalBot, src , 0)
lowPrice = ta.valuewhen(fractalBot, low , 0)
bearSignal = fractalTop and high > highPrice and src < highPrev
bullSignal = fractalBot and low < lowPrice and src > lowPrev
// Get user input
enableSR = input(false , "SR On/Off", group="SR")
colorSup = input(#00000000 , "Support Color", group="SR")
colorRes = input(#00000000 , "Resistance Color", group="SR")
strengthSR = input.int(2 , "S/R Strength", 1, group="SR")
lineStyle = input.string("Dotted", "Line Style", , group="SR")
lineWidth = input.int(2 , "S/R Line Width", 1, group="SR")
useZones = input(true , "Zones On/Off", group="SR")
useHLZones = input(true , "High Low Zones On/Off", group="SR")
zoneWidth = input.int(2 , "Zone Width %", 0,
tooltip = "it's calculated using % of the distance between highest/lowest in last 300 bars", group="SR")
expandSR = input(true , "Expand SR")
// Get components
rb = 10
prd = 284
ChannelW = 10
label_loc = 55
style = lineStyle == "Solid" ? line.style_solid :
lineStyle == "Dotted" ? line.style_dotted : line.style_dashed
ph = ta.pivothigh(rb, rb)
pl = ta.pivotlow (rb, rb)
sr_levels = array.new_float(21, na)
prdhighest = ta.highest(prd)
prdlowest = ta.lowest(prd)
cwidth = percWidth(prd, ChannelW)
zonePerc = percWidth(300, zoneWidth)
aas = array.new_bool(41, true)
u1 = 0.0, u1 := nz(u1 )
d1 = 0.0, d1 := nz(d1 )
highestph = 0.0, highestph := highestph
lowestpl = 0.0, lowestpl := lowestpl
var sr_levs = array.new_float(21, na)
label hlabel = na, label.delete(hlabel )
label llabel = na, label.delete(llabel )
var sr_lines = array.new_line(21, na)
var sr_linesH = array.new_line(21, na)
var sr_linesL = array.new_line(21, na)
var sr_linesF = array.new_linefill(21, na)
var sr_labels = array.new_label(21, na)
if (not na(ph) or not na(pl))
for x = 0 to array.size(sr_levels) - 1
array.set(sr_levels, x, na)
highestph := prdlowest
lowestpl := prdhighest
countpp = 0
for x = 0 to prd
if na(close )
break
if not na(ph ) or not na(pl )
highestph := math.max(highestph, nz(ph , prdlowest), nz(pl , prdlowest))
lowestpl := math.min(lowestpl, nz(ph , prdhighest), nz(pl , prdhighest))
countpp += 1
if countpp > 40
break
if array.get(aas, countpp)
upl = (not na(ph ) and (ph != 0) ? high : low ) + cwidth
dnl = (not na(ph ) and (ph != 0) ? high : low ) - cwidth
u1 := countpp == 1 ? upl : u1
d1 := countpp == 1 ? dnl : d1
tmp = array.new_bool(41, true)
cnt = 0
tpoint = 0
for xx = 0 to prd
if na(close )
break
if not na(ph ) or not na(pl )
chg = false
cnt += 1
if cnt > 40
break
if array.get(aas, cnt)
if not na(ph )
if high <= upl and high >= dnl
tpoint += 1
chg := true
if not na(pl )
if low <= upl and low >= dnl
tpoint += 1
chg := true
if chg and cnt < 41
array.set(tmp, cnt, false)
if tpoint >= strengthSR
for g = 0 to 40 by 1
if not array.get(tmp, g)
array.set(aas, g, false)
if (not na(ph ) and countpp < 21)
array.set(sr_levels, countpp, high )
if (not na(pl ) and countpp < 21)
array.set(sr_levels, countpp, low )
// Plot
var line highest_ = na, line.delete(highest_)
var line lowest_ = na, line.delete(lowest_)
var line highest_fill1 = na, line.delete(highest_fill1)
var line highest_fill2 = na, line.delete(highest_fill2)
var line lowest_fill1 = na, line.delete(lowest_fill1)
var line lowest_fill2 = na, line.delete(lowest_fill2)
hi_col = close >= highestph ? colorSup : colorRes
lo_col = close >= lowestpl ? colorSup : colorRes
if enableSR
highest_ := line.new(bar_index - 311, highestph, bar_index, highestph, xloc.bar_index, expandSR ? extend.both : extend.right, hi_col, style, lineWidth)
lowest_ := line.new(bar_index - 311, lowestpl , bar_index, lowestpl , xloc.bar_index, expandSR ? extend.both : extend.right, lo_col, style, lineWidth)
if useHLZones
highest_fill1 := line.new(bar_index - 311, highestph + zonePerc, bar_index, highestph + zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na)
highest_fill2 := line.new(bar_index - 311, highestph - zonePerc, bar_index, highestph - zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na)
lowest_fill1 := line.new(bar_index - 311, lowestpl + zonePerc , bar_index, lowestpl + zonePerc , xloc.bar_index, expandSR ? extend.both : extend.right, na)
lowest_fill2 := line.new(bar_index - 311, lowestpl - zonePerc , bar_index, lowestpl - zonePerc , xloc.bar_index, expandSR ? extend.both : extend.right, na)
linefill.new(highest_fill1, highest_fill2, hi_col)
linefill.new(lowest_fill1 , lowest_fill2 , lo_col)
if (not na(ph) or not na(pl))
for x = 0 to array.size(sr_lines) - 1
array.set(sr_levs, x, array.get(sr_levels, x))
for x = 0 to array.size(sr_lines) - 1
line.delete(array.get(sr_lines, x))
line.delete(array.get(sr_linesH, x))
line.delete(array.get(sr_linesL, x))
linefill.delete(array.get(sr_linesF, x))
if (not na(array.get(sr_levs, x)) and enableSR)
line_col = close >= array.get(sr_levs, x) ? colorSup : colorRes
array.set(sr_lines, x, line.new(bar_index - 355, array.get(sr_levs, x), bar_index, array.get(sr_levs, x), xloc.bar_index, expandSR ? extend.both : extend.right, line_col, style, lineWidth))
if useZones
array.set(sr_linesH, x, line.new(bar_index - 355, array.get(sr_levs, x) + zonePerc, bar_index, array.get(sr_levs, x) + zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na))
array.set(sr_linesL, x, line.new(bar_index - 355, array.get(sr_levs, x) - zonePerc, bar_index, array.get(sr_levs, x) - zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na))
array.set(sr_linesF, x, linefill.new(array.get(sr_linesH, x), array.get(sr_linesL, x), line_col))
for x = 0 to array.size(sr_labels) - 1
label.delete(array.get(sr_labels, x))
if (not na(array.get(sr_levs, x)) and enableSR)
lab_loc = close >= array.get(sr_levs, x) ? label.style_label_up : label.style_label_down
lab_col = close >= array.get(sr_levs, x) ? colorSup : colorRes
array.set(sr_labels, x, label.new(bar_index + label_loc, array.get(sr_levs, x), str.tostring(math.round_to_mintick(array.get(sr_levs, x))), color=lab_col , textcolor=#000000, style=lab_loc))
hlabel := enableSR ? label.new(bar_index + label_loc + math.round(math.sign(label_loc)) * 20, highestph, "High Level : " + str.tostring(highestph), color=hi_col, textcolor=#000000, style=label.style_label_down) : na
llabel := enableSR ? label.new(bar_index + label_loc + math.round(math.sign(label_loc)) * 20, lowestpl , "Low Level : " + str.tostring(lowestpl) , color=lo_col, textcolor=#000000, style=label.style_label_up ) : na
// Get components
rsi = ta.rsi(close, 28)
//rsiOb = rsi > 78 and rsi > ta.ema(rsi, 10)
//rsiOs = rsi < 27 and rsi < ta.ema(rsi, 10)
rsiOb = rsi > 65 and rsi > ta.ema(rsi, 10)
rsiOs = rsi < 35 and rsi < ta.ema(rsi, 10)
dHigh = securityNoRep(syminfo.tickerid, "D", high )
dLow = securityNoRep(syminfo.tickerid, "D", low )
dClose = securityNoRep(syminfo.tickerid, "D", close )
ema = ta.ema(close, 144)
emaBull = close > ema
equal_tf(res) => str.tonumber(res) == f_chartTfInMinutes() and not timeframe.isseconds
higher_tf(res) => str.tonumber(res) > f_chartTfInMinutes() or timeframe.isseconds
too_small_tf(res) => (timeframe.isweekly and res=="1") or (timeframe.ismonthly and str.tonumber(res) < 10)
securityNoRep1(sym, res, src) =>
bool bull_ = na
bull_ := equal_tf(res) ? src : bull_
bull_ := higher_tf(res) ? request.security(sym, res, src, barmerge.gaps_off, barmerge.lookahead_on) : bull_
bull_array = request.security_lower_tf(syminfo.tickerid, higher_tf(res) ? str.tostring(f_chartTfInMinutes()) + (timeframe.isseconds ? "S" : "") : too_small_tf(res) ? (timeframe.isweekly ? "3" : "10") : res, src)
if array.size(bull_array) > 1 and not equal_tf(res) and not higher_tf(res)
bull_ := array.pop(bull_array)
array.clear(bull_array)
bull_
// === BASE FUNCTIONS ===
// Returns MA input selection variant, default to SMA if blank or typo.
variant(type, src, len, offSig, offALMA) =>
v1 = ta.sma(src, len) // Simple
v2 = ta.ema(src, len) // Exponential
v3 = 2 * v2 - ta.ema(v2, len) // Double Exponential
v4 = 3 * (v2 - ta.ema(v2, len)) + ta.ema(ta.ema(v2, len), len) // Triple Exponential
v5 = ta.wma(src, len) // Weighted
v6 = ta.vwma(src, len) // Volume Weighted
v7 = 0.0
sma_1 = ta.sma(src, len) // Smoothed
v7 := na(v7 ) ? sma_1 : (v7 * (len - 1) + src) / len
v8 = ta.wma(2 * ta.wma(src, len / 2) - ta.wma(src, len), math.round(math.sqrt(len))) // Hull
v9 = ta.linreg(src, len, offSig) // Least Squares
v10 = ta.alma(src, len, offALMA, offSig) // Arnaud Legoux
v11 = ta.sma(v1, len) // Triangular (extreme smooth)
// SuperSmoother filter
// 2013 John F. Ehlers
a1 = math.exp(-1.414 * 3.14159 / len)
b1 = 2 * a1 * math.cos(1.414 * 3.14159 / len)
c2 = b1
c3 = -a1 * a1
c1 = 1 - c2 - c3
v12 = 0.0
v12 := c1 * (src + nz(src )) / 2 + c2 * nz(v12 ) + c3 * nz(v12 )
type == 'EMA' ? v2 : type == 'DEMA' ? v3 : type == 'TEMA' ? v4 : type == 'WMA' ? v5 : type == 'VWMA' ? v6 : type == 'SMMA' ? v7 : type == 'HullMA' ? v8 : type == 'LSMA' ? v9 : type == 'ALMA' ? v10 : type == 'TMA' ? v11 : type == 'SSMA' ? v12 : v1
// security wrapper for repeat calls
reso(exp, use, res) =>
security_1 = request.security(syminfo.tickerid, res, exp, gaps = barmerge.gaps_off, lookahead = barmerge.lookahead_on)
use ? security_1 : exp
// === /BASE FUNCTIONS ===
// === SERIES SETUP ===
closeSeries = variant(basisType, close , basisLen, offsetSigma, offsetALMA)
openSeries = variant(basisType, open , basisLen, offsetSigma, offsetALMA)
// === /SERIES ===
// Get Alternate resolution Series if selected.
closeSeriesAlt = reso(closeSeries, useRes, stratRes)
openSeriesAlt = reso(openSeries, useRes, stratRes)
//
lxTrigger = false
sxTrigger = false
leTrigger = ta.crossover (closeSeriesAlt, openSeriesAlt)
seTrigger = ta.crossunder(closeSeriesAlt, openSeriesAlt)
G_RISK = '■ ' + 'Risk Management'
//#region ———— <↓↓↓ G_RISK ↓↓↓> {
// ———————————
//Tooltip
T_LVL = '(%) Exit Level'
T_QTY = '(%) Adjust trade exit volume'
T_MSG = 'Paste JSON message for your bot'
//Webhook Message
O_LEMSG = 'Long Entry'
O_LXMSGSL = 'Long SL'
O_LXMSGTP1 = 'Long TP1'
O_LXMSGTP2 = 'Long TP2'
O_LXMSGTP3 = 'Long TP3'
O_LXMSG = 'Long Exit'
O_SEMSG = 'Short Entry'
O_SXMSGSL = 'Short SL'
O_SXMSGA = 'Short TP1'
O_SXMSGB = 'Short TP2'
O_SXMSGC = 'Short TP3'
O_SXMSGX = 'Short Exit'
// ——————————— | | | Line length guide |
i_lxLvlTP1 = input.float (0.2, 'Level TP1' , group = G_RISK,
tooltip = T_LVL)
i_lxQtyTP1 = input.float (80.0, 'Qty TP1' , group = G_RISK,
tooltip = T_QTY)
i_lxLvlTP2 = input.float (0.5, 'Level TP2' , group = G_RISK,
tooltip = T_LVL)
i_lxQtyTP2 = input.float (10.0, 'Qty TP2' , group = G_RISK,
tooltip = T_QTY)
i_lxLvlTP3 = input.float (7.0, 'Level TP3' , group = G_RISK,
tooltip = T_LVL)
i_lxQtyTP3 = input.float (2, 'Qty TP3' , group = G_RISK,
tooltip = T_QTY)
i_lxLvlSL = input.float (0.5, 'Stop Loss' , group = G_RISK,
tooltip = T_LVL)
i_sxLvlTP1 = i_lxLvlTP1
i_sxQtyTP1 = i_lxQtyTP1
i_sxLvlTP2 = i_lxLvlTP2
i_sxQtyTP2 = i_lxQtyTP2
i_sxLvlTP3 = i_lxLvlTP3
i_sxQtyTP3 = i_lxQtyTP3
i_sxLvlSL = i_lxLvlSL
G_MSG = '■ ' + 'Webhook Message'
i_leMsg = input.string (O_LEMSG ,'Long Entry' , group = G_MSG, tooltip = T_MSG)
i_lxMsgSL = input.string (O_LXMSGSL ,'Long SL' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP1 = input.string (O_LXMSGTP1,'Long TP1' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP2 = input.string (O_LXMSGTP2,'Long TP2' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP3 = input.string (O_LXMSGTP3,'Long TP3' , group = G_MSG, tooltip = T_MSG)
i_lxMsg = input.string (O_LXMSG ,'Long Exit' , group = G_MSG, tooltip = T_MSG)
i_seMsg = input.string (O_SEMSG ,'Short Entry' , group = G_MSG, tooltip = T_MSG)
i_sxMsgSL = input.string (O_SXMSGSL ,'Short SL' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP1 = input.string (O_SXMSGA ,'Short TP1' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP2 = input.string (O_SXMSGB ,'Short TP2' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP3 = input.string (O_SXMSGC ,'Short TP3' , group = G_MSG, tooltip = T_MSG)
i_sxMsg = input.string (O_SXMSGX ,'Short Exit' , group = G_MSG, tooltip = T_MSG)
i_src = close
G_DISPLAY = 'Display'
//
i_alertOn = input.bool (true, 'Alert Labels On/Off' , group = G_DISPLAY)
i_barColOn = input.bool (true, 'Bar Color On/Off' , group = G_DISPLAY)
// ———————————
// @function Calculate the Take Profit line, and the crossover or crossunder
f_tp(_condition, _conditionValue, _leTrigger, _seTrigger, _src, _lxLvlTP, _sxLvlTP)=>
var float _tpLine = 0.0
_topLvl = _src + (_src * (_lxLvlTP / 100))
_botLvl = _src - (_src * (_sxLvlTP / 100))
_tpLine := _condition != _conditionValue and _leTrigger ? _topLvl :
_condition != -_conditionValue and _seTrigger ? _botLvl :
nz(_tpLine )
// @function Similar to "ta.crossover" or "ta.crossunder"
f_cross(_scr1, _scr2, _over)=>
_cross = _over ? _scr1 > _scr2 and _scr1 < _scr2 :
_scr1 < _scr2 and _scr1 > _scr2
// ———————————
//
var float condition = 0.0
var float slLine = 0.0
var float entryLine = 0.0
//
entryLine := leTrigger and condition <= 0.0 ? close :
seTrigger and condition >= 0.0 ? close : nz(entryLine )
//
slTopLvl = i_src + (i_src * (i_lxLvlSL / 100))
slBotLvl = i_src - (i_src * (i_sxLvlSL / 100))
slLine := condition <= 0.0 and leTrigger ? slBotLvl :
condition >= 0.0 and seTrigger ? slTopLvl : nz(slLine )
slLong = f_cross(low, slLine, false)
slShort = f_cross(high, slLine, true )
//
= f_tp(condition, 1.2,leTrigger, seTrigger, i_src, i_lxLvlTP3, i_sxLvlTP3)
= f_tp(condition, 1.1,leTrigger, seTrigger, i_src, i_lxLvlTP2, i_sxLvlTP2)
= f_tp(condition, 1.0,leTrigger, seTrigger, i_src, i_lxLvlTP1, i_sxLvlTP1)
tp3Long = f_cross(high, tp3Line, true )
tp3Short = f_cross(low, tp3Line, false)
tp2Long = f_cross(high, tp2Line, true )
tp2Short = f_cross(low, tp2Line, false)
tp1Long = f_cross(high, tp1Line, true )
tp1Short = f_cross(low, tp1Line, false)
switch
leTrigger and condition <= 0.0 => condition := 1.0
seTrigger and condition >= 0.0 => condition := -1.0
tp3Long and condition == 1.2 => condition := 1.3
tp3Short and condition == -1.2 => condition := -1.3
tp2Long and condition == 1.1 => condition := 1.2
tp2Short and condition == -1.1 => condition := -1.2
tp1Long and condition == 1.0 => condition := 1.1
tp1Short and condition == -1.0 => condition := -1.1
slLong and condition >= 1.0 => condition := 0.0
slShort and condition <= -1.0 => condition := 0.0
lxTrigger and condition >= 1.0 => condition := 0.0
sxTrigger and condition <= -1.0 => condition := 0.0
longE = leTrigger and condition <= 0.0 and condition == 1.0
shortE = seTrigger and condition >= 0.0 and condition == -1.0
longX = lxTrigger and condition >= 1.0 and condition == 0.0
shortX = sxTrigger and condition <= -1.0 and condition == 0.0
longSL = slLong and condition >= 1.0 and condition == 0.0
shortSL = slShort and condition <= -1.0 and condition == 0.0
longTP3 = tp3Long and condition == 1.2 and condition == 1.3
shortTP3 = tp3Short and condition == -1.2 and condition == -1.3
longTP2 = tp2Long and condition == 1.1 and condition == 1.2
shortTP2 = tp2Short and condition == -1.1 and condition == -1.2
longTP1 = tp1Long and condition == 1.0 and condition == 1.1
shortTP1 = tp1Short and condition == -1.0 and condition == -1.1
// ——————————— {
//
if strategy.position_size <= 0 and longE and barstate.isconfirmed
strategy.entry(
'Long',
strategy.long,
alert_message = i_leMsg,
comment = 'LE')
if strategy.position_size > 0 and condition == 1.0
strategy.exit(
id = 'LXTP1',
from_entry = 'Long',
qty_percent = i_lxQtyTP1,
limit = tp1Line,
stop = slLine,
comment_profit = 'LXTP1',
comment_loss = 'SL',
alert_profit = i_lxMsgTP1,
alert_loss = i_lxMsgSL)
if strategy.position_size > 0 and condition == 1.1
strategy.exit(
id = 'LXTP2',
from_entry = 'Long',
qty_percent = i_lxQtyTP2,
limit = tp2Line,
stop = slLine,
comment_profit = 'LXTP2',
comment_loss = 'SL',
alert_profit = i_lxMsgTP2,
alert_loss = i_lxMsgSL)
if strategy.position_size > 0 and condition == 1.2
strategy.exit(
id = 'LXTP3',
from_entry = 'Long',
qty_percent = i_lxQtyTP3,
limit = tp3Line,
stop = slLine,
comment_profit = 'LXTP3',
comment_loss = 'SL',
alert_profit = i_lxMsgTP3,
alert_loss = i_lxMsgSL)
if longX
strategy.close(
'Long',
alert_message = i_lxMsg,
comment = 'LX')
//
if strategy.position_size >= 0 and shortE and barstate.isconfirmed
strategy.entry(
'Short',
strategy.short,
alert_message = i_leMsg,
comment = 'SE')
if strategy.position_size < 0 and condition == -1.0
strategy.exit(
id = 'SXTP1',
from_entry = 'Short',
qty_percent = i_sxQtyTP1,
limit = tp1Line,
stop = slLine,
comment_profit = 'SXTP1',
comment_loss = 'SL',
alert_profit = i_sxMsgTP1,
alert_loss = i_sxMsgSL)
if strategy.position_size < 0 and condition == -1.1
strategy.exit(
id = 'SXTP2',
from_entry = 'Short',
qty_percent = i_sxQtyTP2,
limit = tp2Line,
stop = slLine,
comment_profit = 'SXTP2',
comment_loss = 'SL',
alert_profit = i_sxMsgTP2,
alert_loss = i_sxMsgSL)
if strategy.position_size < 0 and condition == -1.2
strategy.exit(
id = 'SXTP3',
from_entry = 'Short',
qty_percent = i_sxQtyTP3,
limit = tp3Line,
stop = slLine,
comment_profit = 'SXTP3',
comment_loss = 'SL',
alert_profit = i_sxMsgTP3,
alert_loss = i_sxMsgSL)
if shortX
strategy.close(
'Short',
alert_message = i_sxMsg,
comment = 'SX')
// ———————————
c_tp = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.green
c_entry = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.blue
c_sl = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.red
p_tp1Line = plot (
condition == 1.0 or
condition == -1.0 ? tp1Line : na,
title = "TP Line 1",
color = c_tp,
linewidth = 1,
style = plot.style_linebr)
p_tp2Line = plot (
condition == 1.0 or
condition == -1.0 or
condition == 1.1 or
condition == -1.1 ? tp2Line : na,
title = "TP Line 2",
color = c_tp,
linewidth = 1,
style = plot.style_linebr)
p_tp3Line = plot (
condition == 1.0 or
condition == -1.0 or
condition == 1.1 or
condition == -1.1 or
condition == 1.2 or
condition == -1.2 ? tp3Line : na,
title = "TP Line 3",
color = c_tp,
linewidth = 1,
style = plot.style_linebr)
p_entryLine = plot (
condition >= 1.0 or
condition <= -1.0 ? entryLine : na,
title = "Entry Line",
color = c_entry,
linewidth = 1,
style = plot.style_linebr)
p_slLine = plot (
condition == 1.0 or
condition == -1.0 or
condition == 1.1 or
condition == -1.1 or
condition == 1.2 or
condition == -1.2 ? slLine : na,
title = "SL Line",
color = c_sl,
linewidth = 1,
style = plot.style_linebr)
fill(
p_tp3Line, p_entryLine,
color = leTrigger or seTrigger ? na :color.new(color.green, 90))
fill(
p_entryLine, p_slLine,
color = leTrigger or seTrigger ? na :color.new(color.red, 90))
//
plotshape(
i_alertOn and longE,
title = 'Long',
text = 'Long',
textcolor = color.white,
color = color.green,
style = shape.labelup,
size = size.tiny,
location = location.belowbar)
plotshape(
i_alertOn and shortE,
title = 'Short',
text = 'Short',
textcolor = color.white,
color = color.red,
style = shape.labeldown,
size = size.tiny,
location = location.abovebar)
plotshape(
i_alertOn and (longX or shortX) ? close : na,
title = 'Close',
text = 'Close',
textcolor = color.white,
color = color.gray,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
l_tp = i_alertOn and (longTP1 or shortTP1) ? close : na
plotshape(
l_tp,
title = "TP1 Cross",
text = "TP1",
textcolor = color.white,
color = color.olive,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
plotshape(
i_alertOn and (longTP2 or shortTP2) ? close : na,
title = "TP2 Cross",
text = "TP2",
textcolor = color.white,
color = color.olive,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
plotshape(
i_alertOn and (longTP3 or shortTP3) ? close : na,
title = "TP3 Cross",
text = "TP3",
textcolor = color.white,
color = color.olive,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
plotshape(
i_alertOn and (longSL or shortSL) ? close : na,
title = "SL Cross",
text = "SL",
textcolor = color.white,
color = color.maroon,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
//
plot(
na,
title = "─── ───",
editable = false,
display = display.data_window)
plot(
condition,
title = "condition",
editable = false,
display = display.data_window)
plot(
strategy.position_size * 100,
title = ".position_size",
editable = false,
display = display.data_window)
//#endregion }
// ——————————— <↑↑↑ G_RISK ↑↑↑>
//#region ———— <↓↓↓ G_SCRIPT02 ↓↓↓> {
// @function Queues a new element in an array and de-queues its first element.
f_qDq(_array, _val) =>
array.push(_array, _val)
_return = array.shift(_array)
_return
var line a_slLine = array.new_line(1)
var line a_entryLine = array.new_line(1)
var line a_tp3Line = array.new_line(1)
var line a_tp2Line = array.new_line(1)
var line a_tp1Line = array.new_line(1)
var label a_slLabel = array.new_label(1)
var label a_tp3label = array.new_label(1)
var label a_tp2label = array.new_label(1)
var label a_tp1label = array.new_label(1)
var label a_entryLabel = array.new_label(1)
newEntry = longE or shortE
entryIndex = 1
entryIndex := newEntry ? bar_index : nz(entryIndex )
lasTrade = bar_index >= entryIndex
l_right = 10
line.delete(
f_qDq(a_slLine,
line.new(
entryIndex,
slLine,
last_bar_index + l_right,
slLine,
style = line.style_solid,
color = c_sl)))
line.delete(
f_qDq(a_entryLine,
line.new(
entryIndex,
entryLine,
last_bar_index + l_right,
entryLine,
style = line.style_solid,
color = color.blue)))
line.delete(
f_qDq(a_tp3Line,
line.new(
entryIndex,
tp3Line,
last_bar_index + l_right,
tp3Line,
style = line.style_solid,
color = c_tp)))
line.delete(
f_qDq(a_tp2Line,
line.new(
entryIndex,
tp2Line,
last_bar_index + l_right,
tp2Line,
style = line.style_solid,
color = c_tp)))
line.delete(
f_qDq(a_tp1Line,
line.new(
entryIndex,
tp1Line,
last_bar_index + l_right,
tp1Line,
style = line.style_solid,
color = c_tp)))
label.delete(
f_qDq(a_slLabel,
label.new(
last_bar_index + l_right,
slLine,
'SL: ' + str.tostring(slLine, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_sl)))
label.delete(
f_qDq(a_entryLabel,
label.new(
last_bar_index + l_right,
entryLine,
'Entry: ' + str.tostring(entryLine, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = color.blue)))
label.delete(
f_qDq(a_tp3label,
label.new(
last_bar_index + l_right,
tp3Line,
'TP3: ' + str.tostring(tp3Line, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_tp)))
label.delete(
f_qDq(a_tp2label,
label.new(
last_bar_index + l_right,
tp2Line,
'TP2: ' + str.tostring(tp2Line, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_tp)))
label.delete(
f_qDq(a_tp1label,
label.new(
last_bar_index + l_right,
tp1Line,
'TP1: ' + str.tostring(tp1Line, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_tp)))
// ———————————
//
if longE or shortE or longX or shortX
alert(message = 'Any Alert', freq = alert.freq_once_per_bar_close)
if longE
alert(message = 'Long Entry', freq = alert.freq_once_per_bar_close)
if shortE
alert(message = 'Short Entry', freq = alert.freq_once_per_bar_close)
if longX
alert(message = 'Long Exit', freq = alert.freq_once_per_bar_close)
if shortX
alert(message = 'Short Exit', freq = alert.freq_once_per_bar_close)
//#endregion }
// ——————————— <↑↑↑ G_SCRIPT03 ↑↑↑>
Мой скрипт// © Buzzara
// =================================
// PLEASE SUPPORT THE TEAM
// =================================
//
// Telegram: t.me
a_trade// =================================
//@version=5
VERSION = ' Buzzara2.0'
strategy('ALGOX V6_1_24', shorttitle = '🚀〄 Buzzara2.0 〄🚀'+ VERSION, overlay = true, explicit_plot_zorder = true, pyramiding = 0, default_qty_type = strategy.percent_of_equity, initial_capital = 1000, default_qty_value = 1, calc_on_every_tick = false, process_orders_on_close = true)
G_SCRIPT01 = '■ ' + 'SAIYAN OCC'
//#region ———— <↓↓↓ G_SCRIPT01 ↓↓↓> {
// === INPUTS ===
res = input.timeframe('15', 'TIMEFRAME', group ="NON REPAINT")
useRes = input(true, 'Use Alternate Signals')
intRes = input(10, 'Multiplier for Alernate Signals')
basisType = input.string('ALMA', 'MA Type: ', options= )
basisLen = input.int(50, 'MA Period', minval=1)
offsetSigma = input.int(5, 'Offset for LSMA / Sigma for ALMA', minval=0)
offsetALMA = input.float(2, 'Offset for ALMA', minval=0, step=0.01)
scolor = input(false, 'Show coloured Bars to indicate Trend?')
delayOffset = input.int(0, 'Delay Open/Close MA', minval=0, step=1,
tooltip = 'Forces Non-Repainting')
tradeType = input.string('BOTH', 'What trades should be taken : ',
options = )
//=== /INPUTS ===
h = input(false, 'Signals for Heikin Ashi Candles')
//INDICATOR SETTINGS
swing_length = input.int(10, 'Swing High/Low Length', group = 'Settings', minval = 1, maxval = 50)
history_of_demand_to_keep = input.int(20, 'History To Keep', minval = 5, maxval = 50)
box_width = input.float(2.5, 'Supply/Demand Box Width', group = 'Settings', minval = 1, maxval = 10, step = 0.5)
//INDICATOR VISUAL SETTINGS
show_zigzag = input.bool(false, 'Show Zig Zag', group = 'Visual Settings', inline = '1')
show_price_action_labels = input.bool(false, 'Show Price Action Labels', group = 'Visual Settings', inline = '2')
supply_color = input.color(#00000000, 'Supply', group = 'Visual Settings', inline = '3')
supply_outline_color = input.color(#00000000, 'Outline', group = 'Visual Settings', inline = '3')
demand_color = input.color(#00000000, 'Demand', group = 'Visual Settings', inline = '4')
demand_outline_color = input.color(#00000000, 'Outline', group = 'Visual Settings', inline = '4')
bos_label_color = input.color(#00000000, 'BOS Label', group = 'Visual Settings', inline = '5')
poi_label_color = input.color(#00000000, 'POI Label', group = 'Visual Settings', inline = '7')
poi_border_color = input.color(#00000000, 'POI border', group = 'Visual Settings', inline = '7')
swing_type_color = input.color(#00000000, 'Price Action Label', group = 'Visual Settings', inline = '8')
zigzag_color = input.color(#00000000, 'Zig Zag', group = 'Visual Settings', inline = '9')
//END SETTINGS
// FUNCTION TO ADD NEW AND REMOVE LAST IN ARRAY
f_array_add_pop(array, new_value_to_add) =>
array.unshift(array, new_value_to_add)
array.pop(array)
// FUNCTION SWING H & L LABELS
f_sh_sl_labels(array, swing_type) =>
var string label_text = na
if swing_type == 1
if array.get(array, 0) >= array.get(array, 1)
label_text := 'HH'
else
label_text := 'LH'
label.new(
bar_index - swing_length,
array.get(array,0),
text = label_text,
style = label.style_label_down,
textcolor = swing_type_color,
color = swing_type_color,
size = size.tiny)
else if swing_type == -1
if array.get(array, 0) >= array.get(array, 1)
label_text := 'HL'
else
label_text := 'LL'
label.new(
bar_index - swing_length,
array.get(array,0),
text = label_text,
style = label.style_label_up,
textcolor = swing_type_color,
color = swing_type_color,
size = size.tiny)
// FUNCTION MAKE SURE SUPPLY ISNT OVERLAPPING
f_check_overlapping(new_poi, box_array, atrValue) =>
atr_threshold = atrValue * 2
okay_to_draw = true
for i = 0 to array.size(box_array) - 1
top = box.get_top(array.get(box_array, i))
bottom = box.get_bottom(array.get(box_array, i))
poi = (top + bottom) / 2
upper_boundary = poi + atr_threshold
lower_boundary = poi - atr_threshold
if new_poi >= lower_boundary and new_poi <= upper_boundary
okay_to_draw := false
break
else
okay_to_draw := true
okay_to_draw
// FUNCTION TO DRAW SUPPLY OR DEMAND ZONE
f_supply_demand(value_array, bn_array, box_array, label_array, box_type, atrValue) =>
atr_buffer = atrValue * (box_width / 10)
box_left = array.get(bn_array, 0)
box_right = bar_index
var float box_top = 0.00
var float box_bottom = 0.00
var float poi = 0.00
if box_type == 1
box_top := array.get(value_array, 0)
box_bottom := box_top - atr_buffer
poi := (box_top + box_bottom) / 2
else if box_type == -1
box_bottom := array.get(value_array, 0)
box_top := box_bottom + atr_buffer
poi := (box_top + box_bottom) / 2
okay_to_draw = f_check_overlapping(poi, box_array, atrValue)
// okay_to_draw = true
//delete oldest box, and then create a new box and add it to the array
if box_type == 1 and okay_to_draw
box.delete( array.get(box_array, array.size(box_array) - 1) )
f_array_add_pop(box_array, box.new( left = box_left, top = box_top, right = box_right, bottom = box_bottom, border_color = supply_outline_color,
bgcolor = supply_color, extend = extend.right, text = 'SUPPLY', text_halign = text.align_center, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
box.delete( array.get(label_array, array.size(label_array) - 1) )
f_array_add_pop(label_array, box.new( left = box_left, top = poi, right = box_right, bottom = poi, border_color = poi_border_color,
bgcolor = poi_border_color, extend = extend.right, text = 'POI', text_halign = text.align_left, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
else if box_type == -1 and okay_to_draw
box.delete( array.get(box_array, array.size(box_array) - 1) )
f_array_add_pop(box_array, box.new( left = box_left, top = box_top, right = box_right, bottom = box_bottom, border_color = demand_outline_color,
bgcolor = demand_color, extend = extend.right, text = 'DEMAND', text_halign = text.align_center, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
box.delete( array.get(label_array, array.size(label_array) - 1) )
f_array_add_pop(label_array, box.new( left = box_left, top = poi, right = box_right, bottom = poi, border_color = poi_border_color,
bgcolor = poi_border_color, extend = extend.right, text = 'POI', text_halign = text.align_left, text_valign = text.align_center, text_color = poi_label_color, text_size = size.small, xloc = xloc.bar_index))
// FUNCTION TO CHANGE SUPPLY/DEMAND TO A BOS IF BROKEN
f_sd_to_bos(box_array, bos_array, label_array, zone_type) =>
if zone_type == 1
for i = 0 to array.size(box_array) - 1
level_to_break = box.get_top(array.get(box_array,i))
// if ta.crossover(close, level_to_break)
if close >= level_to_break
copied_box = box.copy(array.get(box_array,i))
f_array_add_pop(bos_array, copied_box)
mid = (box.get_top(array.get(box_array,i)) + box.get_bottom(array.get(box_array,i))) / 2
box.set_top(array.get(bos_array,0), mid)
box.set_bottom(array.get(bos_array,0), mid)
box.set_extend( array.get(bos_array,0), extend.none)
box.set_right( array.get(bos_array,0), bar_index)
box.set_text( array.get(bos_array,0), 'BOS' )
box.set_text_color( array.get(bos_array,0), bos_label_color)
box.set_text_size( array.get(bos_array,0), size.small)
box.set_text_halign( array.get(bos_array,0), text.align_center)
box.set_text_valign( array.get(bos_array,0), text.align_center)
box.delete(array.get(box_array, i))
box.delete(array.get(label_array, i))
if zone_type == -1
for i = 0 to array.size(box_array) - 1
level_to_break = box.get_bottom(array.get(box_array,i))
// if ta.crossunder(close, level_to_break)
if close <= level_to_break
copied_box = box.copy(array.get(box_array,i))
f_array_add_pop(bos_array, copied_box)
mid = (box.get_top(array.get(box_array,i)) + box.get_bottom(array.get(box_array,i))) / 2
box.set_top(array.get(bos_array,0), mid)
box.set_bottom(array.get(bos_array,0), mid)
box.set_extend( array.get(bos_array,0), extend.none)
box.set_right( array.get(bos_array,0), bar_index)
box.set_text( array.get(bos_array,0), 'BOS' )
box.set_text_color( array.get(bos_array,0), bos_label_color)
box.set_text_size( array.get(bos_array,0), size.small)
box.set_text_halign( array.get(bos_array,0), text.align_center)
box.set_text_valign( array.get(bos_array,0), text.align_center)
box.delete(array.get(box_array, i))
box.delete(array.get(label_array, i))
// FUNCTION MANAGE CURRENT BOXES BY CHANGING ENDPOINT
f_extend_box_endpoint(box_array) =>
for i = 0 to array.size(box_array) - 1
box.set_right(array.get(box_array, i), bar_index + 100)
//
stratRes = timeframe.ismonthly ? str.tostring(timeframe.multiplier * intRes, '###M') :
timeframe.isweekly ? str.tostring(timeframe.multiplier * intRes, '###W') :
timeframe.isdaily ? str.tostring(timeframe.multiplier * intRes, '###D') :
timeframe.isintraday ? str.tostring(timeframe.multiplier * intRes, '####') :
'60'
src = h ? request.security(ticker.heikinashi(syminfo.tickerid),
timeframe.period, close, lookahead = barmerge.lookahead_off) : close
// CALCULATE ATR
atrValue = ta.atr(50)
// CALCULATE SWING HIGHS & SWING LOWS
swing_high = ta.pivothigh(high, swing_length, swing_length)
swing_low = ta.pivotlow(low, swing_length, swing_length)
// ARRAYS FOR SWING H/L & BN
var swing_high_values = array.new_float(5,0.00)
var swing_low_values = array.new_float(5,0.00)
var swing_high_bns = array.new_int(5,0)
var swing_low_bns = array.new_int(5,0)
// ARRAYS FOR SUPPLY / DEMAND
var current_supply_box = array.new_box(history_of_demand_to_keep, na)
var current_demand_box = array.new_box(history_of_demand_to_keep, na)
// ARRAYS FOR SUPPLY / DEMAND POI LABELS
var current_supply_poi = array.new_box(history_of_demand_to_keep, na)
var current_demand_poi = array.new_box(history_of_demand_to_keep, na)
// ARRAYS FOR BOS
var supply_bos = array.new_box(5, na)
var demand_bos = array.new_box(5, na)
//END CALCULATIONS
// NEW SWING HIGH
if not na(swing_high)
//MANAGE SWING HIGH VALUES
f_array_add_pop(swing_high_values, swing_high)
f_array_add_pop(swing_high_bns, bar_index )
if show_price_action_labels
f_sh_sl_labels(swing_high_values, 1)
f_supply_demand(swing_high_values, swing_high_bns, current_supply_box, current_supply_poi, 1, atrValue)
// NEW SWING LOW
else if not na(swing_low)
//MANAGE SWING LOW VALUES
f_array_add_pop(swing_low_values, swing_low)
f_array_add_pop(swing_low_bns, bar_index )
if show_price_action_labels
f_sh_sl_labels(swing_low_values, -1)
f_supply_demand(swing_low_values, swing_low_bns, current_demand_box, current_demand_poi, -1, atrValue)
f_sd_to_bos(current_supply_box, supply_bos, current_supply_poi, 1)
f_sd_to_bos(current_demand_box, demand_bos, current_demand_poi, -1)
f_extend_box_endpoint(current_supply_box)
f_extend_box_endpoint(current_demand_box)
channelBal = input.bool(false, "Channel Balance", group = "CHART")
lr_slope(_src, _len) =>
x = 0.0, y = 0.0, x2 = 0.0, xy = 0.0
for i = 0 to _len - 1
val = _src
per = i + 1
x += per
y += val
x2 += per * per
xy += val * per
_slp = (_len * xy - x * y) / (_len * x2 - x * x)
_avg = y / _len
_int = _avg - _slp * x / _len + _slp
lr_dev(_src, _len, _slp, _avg, _int) =>
upDev = 0.0, dnDev = 0.0
val = _int
for j = 0 to _len - 1
price = high - val
if price > upDev
upDev := price
price := val - low
if price > dnDev
dnDev := price
price := _src
val += _slp
//
= ta.kc(close, 80, 10.5)
= ta.kc(close, 80, 9.5)
= ta.kc(close, 80, 8)
= ta.kc(close, 80, 3)
barsL = 10
barsR = 10
pivotHigh = fixnan(ta.pivothigh(barsL, barsR) )
pivotLow = fixnan(ta.pivotlow(barsL, barsR) )
source = close, period = 150
= lr_slope(source, period)
= lr_dev(source, period, s, a, i)
y1 = low - (ta.atr(30) * 2), y1B = low - ta.atr(30)
y2 = high + (ta.atr(30) * 2), y2B = high + ta.atr(30)
x1 = bar_index - period + 1, _y1 = i + s * (period - 1), x2 = bar_index, _y2 = i
//Functions
//Line Style function
get_line_style(style) =>
out = switch style
'???' => line.style_solid
'----' => line.style_dashed
' ' => line.style_dotted
//Function to get order block coordinates
get_coordinates(condition, top, btm, ob_val)=>
var ob_top = array.new_float(0)
var ob_btm = array.new_float(0)
var ob_avg = array.new_float(0)
var ob_left = array.new_int(0)
float ob = na
//Append coordinates to arrays
if condition
avg = math.avg(top, btm)
array.unshift(ob_top, top)
array.unshift(ob_btm, btm)
array.unshift(ob_avg, avg)
ob := ob_val
//Function to remove mitigated order blocks from coordinate arrays
remove_mitigated(ob_top, ob_btm, ob_left, ob_avg, target, bull)=>
mitigated = false
target_array = bull ? ob_btm : ob_top
for element in target_array
idx = array.indexof(target_array, element)
if (bull ? target < element : target > element)
mitigated := true
array.remove(ob_top, idx)
array.remove(ob_btm, idx)
array.remove(ob_avg, idx)
array.remove(ob_left, idx)
mitigated
//Function to set order blocks
set_order_blocks(ob_top, ob_btm, ob_left, ob_avg, ext_last, bg_css, border_css, lvl_css)=>
var ob_box = array.new_box(0)
var ob_lvl = array.new_line(0)
//Global elements
var os = 0
var target_bull = 0.
var target_bear = 0.
// Create non-repainting security function
rp_security(_symbol, _res, _src) =>
request.security(_symbol, _res, _src )
htfHigh = rp_security(syminfo.tickerid, res, high)
htfLow = rp_security(syminfo.tickerid, res, low)
// Main Indicator
// Functions
smoothrng(x, t, m) =>
wper = t * 2 - 1
avrng = ta.ema(math.abs(x - x ), t)
smoothrng = ta.ema(avrng, wper) * m
rngfilt(x, r) =>
rngfilt = x
rngfilt := x > nz(rngfilt ) ? x - r < nz(rngfilt ) ? nz(rngfilt ) : x - r : x + r > nz(rngfilt ) ? nz(rngfilt ) : x + r
percWidth(len, perc) => (ta.highest(len) - ta.lowest(len)) * perc / 100
securityNoRep(sym, res, src) => request.security(sym, res, src, barmerge.gaps_off, barmerge.lookahead_on)
swingPoints(prd) =>
pivHi = ta.pivothigh(prd, prd)
pivLo = ta.pivotlow (prd, prd)
last_pivHi = ta.valuewhen(pivHi, pivHi, 1)
last_pivLo = ta.valuewhen(pivLo, pivLo, 1)
hh = pivHi and pivHi > last_pivHi ? pivHi : na
lh = pivHi and pivHi < last_pivHi ? pivHi : na
hl = pivLo and pivLo > last_pivLo ? pivLo : na
ll = pivLo and pivLo < last_pivLo ? pivLo : na
f_chartTfInMinutes() =>
float _resInMinutes = timeframe.multiplier * (
timeframe.isseconds ? 1 :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 60. * 24 :
timeframe.isweekly ? 60. * 24 * 7 :
timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
f_kc(src, len, sensitivity) =>
basis = ta.sma(src, len)
span = ta.atr(len)
wavetrend(src, chlLen, avgLen) =>
esa = ta.ema(src, chlLen)
d = ta.ema(math.abs(src - esa), chlLen)
ci = (src - esa) / (0.015 * d)
wt1 = ta.ema(ci, avgLen)
wt2 = ta.sma(wt1, 3)
f_top_fractal(_src) => _src < _src and _src < _src and _src > _src and _src > _src
f_bot_fractal(_src) => _src > _src and _src > _src and _src < _src and _src < _src
top_fractal = f_top_fractal(src)
bot_fractal = f_bot_fractal(src)
f_fractalize (_src) => top_fractal ? 1 : bot_fractal ? -1 : 0
f_findDivs(src, topLimit, botLimit) =>
fractalTop = f_fractalize(src) > 0 and src >= topLimit ? src : na
fractalBot = f_fractalize(src) < 0 and src <= botLimit ? src : na
highPrev = ta.valuewhen(fractalTop, src , 0)
highPrice = ta.valuewhen(fractalTop, high , 0)
lowPrev = ta.valuewhen(fractalBot, src , 0)
lowPrice = ta.valuewhen(fractalBot, low , 0)
bearSignal = fractalTop and high > highPrice and src < highPrev
bullSignal = fractalBot and low < lowPrice and src > lowPrev
// Get user input
enableSR = input(false , "SR On/Off", group="SR")
colorSup = input(#00000000 , "Support Color", group="SR")
colorRes = input(#00000000 , "Resistance Color", group="SR")
strengthSR = input.int(2 , "S/R Strength", 1, group="SR")
lineStyle = input.string("Dotted", "Line Style", , group="SR")
lineWidth = input.int(2 , "S/R Line Width", 1, group="SR")
useZones = input(true , "Zones On/Off", group="SR")
useHLZones = input(true , "High Low Zones On/Off", group="SR")
zoneWidth = input.int(2 , "Zone Width %", 0,
tooltip = "it's calculated using % of the distance between highest/lowest in last 300 bars", group="SR")
expandSR = input(true , "Expand SR")
// Get components
rb = 10
prd = 284
ChannelW = 10
label_loc = 55
style = lineStyle == "Solid" ? line.style_solid :
lineStyle == "Dotted" ? line.style_dotted : line.style_dashed
ph = ta.pivothigh(rb, rb)
pl = ta.pivotlow (rb, rb)
sr_levels = array.new_float(21, na)
prdhighest = ta.highest(prd)
prdlowest = ta.lowest(prd)
cwidth = percWidth(prd, ChannelW)
zonePerc = percWidth(300, zoneWidth)
aas = array.new_bool(41, true)
u1 = 0.0, u1 := nz(u1 )
d1 = 0.0, d1 := nz(d1 )
highestph = 0.0, highestph := highestph
lowestpl = 0.0, lowestpl := lowestpl
var sr_levs = array.new_float(21, na)
label hlabel = na, label.delete(hlabel )
label llabel = na, label.delete(llabel )
var sr_lines = array.new_line(21, na)
var sr_linesH = array.new_line(21, na)
var sr_linesL = array.new_line(21, na)
var sr_linesF = array.new_linefill(21, na)
var sr_labels = array.new_label(21, na)
if (not na(ph) or not na(pl))
for x = 0 to array.size(sr_levels) - 1
array.set(sr_levels, x, na)
highestph := prdlowest
lowestpl := prdhighest
countpp = 0
for x = 0 to prd
if na(close )
break
if not na(ph ) or not na(pl )
highestph := math.max(highestph, nz(ph , prdlowest), nz(pl , prdlowest))
lowestpl := math.min(lowestpl, nz(ph , prdhighest), nz(pl , prdhighest))
countpp += 1
if countpp > 40
break
if array.get(aas, countpp)
upl = (not na(ph ) and (ph != 0) ? high : low ) + cwidth
dnl = (not na(ph ) and (ph != 0) ? high : low ) - cwidth
u1 := countpp == 1 ? upl : u1
d1 := countpp == 1 ? dnl : d1
tmp = array.new_bool(41, true)
cnt = 0
tpoint = 0
for xx = 0 to prd
if na(close )
break
if not na(ph ) or not na(pl )
chg = false
cnt += 1
if cnt > 40
break
if array.get(aas, cnt)
if not na(ph )
if high <= upl and high >= dnl
tpoint += 1
chg := true
if not na(pl )
if low <= upl and low >= dnl
tpoint += 1
chg := true
if chg and cnt < 41
array.set(tmp, cnt, false)
if tpoint >= strengthSR
for g = 0 to 40 by 1
if not array.get(tmp, g)
array.set(aas, g, false)
if (not na(ph ) and countpp < 21)
array.set(sr_levels, countpp, high )
if (not na(pl ) and countpp < 21)
array.set(sr_levels, countpp, low )
// Plot
var line highest_ = na, line.delete(highest_)
var line lowest_ = na, line.delete(lowest_)
var line highest_fill1 = na, line.delete(highest_fill1)
var line highest_fill2 = na, line.delete(highest_fill2)
var line lowest_fill1 = na, line.delete(lowest_fill1)
var line lowest_fill2 = na, line.delete(lowest_fill2)
hi_col = close >= highestph ? colorSup : colorRes
lo_col = close >= lowestpl ? colorSup : colorRes
if enableSR
highest_ := line.new(bar_index - 311, highestph, bar_index, highestph, xloc.bar_index, expandSR ? extend.both : extend.right, hi_col, style, lineWidth)
lowest_ := line.new(bar_index - 311, lowestpl , bar_index, lowestpl , xloc.bar_index, expandSR ? extend.both : extend.right, lo_col, style, lineWidth)
if useHLZones
highest_fill1 := line.new(bar_index - 311, highestph + zonePerc, bar_index, highestph + zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na)
highest_fill2 := line.new(bar_index - 311, highestph - zonePerc, bar_index, highestph - zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na)
lowest_fill1 := line.new(bar_index - 311, lowestpl + zonePerc , bar_index, lowestpl + zonePerc , xloc.bar_index, expandSR ? extend.both : extend.right, na)
lowest_fill2 := line.new(bar_index - 311, lowestpl - zonePerc , bar_index, lowestpl - zonePerc , xloc.bar_index, expandSR ? extend.both : extend.right, na)
linefill.new(highest_fill1, highest_fill2, hi_col)
linefill.new(lowest_fill1 , lowest_fill2 , lo_col)
if (not na(ph) or not na(pl))
for x = 0 to array.size(sr_lines) - 1
array.set(sr_levs, x, array.get(sr_levels, x))
for x = 0 to array.size(sr_lines) - 1
line.delete(array.get(sr_lines, x))
line.delete(array.get(sr_linesH, x))
line.delete(array.get(sr_linesL, x))
linefill.delete(array.get(sr_linesF, x))
if (not na(array.get(sr_levs, x)) and enableSR)
line_col = close >= array.get(sr_levs, x) ? colorSup : colorRes
array.set(sr_lines, x, line.new(bar_index - 355, array.get(sr_levs, x), bar_index, array.get(sr_levs, x), xloc.bar_index, expandSR ? extend.both : extend.right, line_col, style, lineWidth))
if useZones
array.set(sr_linesH, x, line.new(bar_index - 355, array.get(sr_levs, x) + zonePerc, bar_index, array.get(sr_levs, x) + zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na))
array.set(sr_linesL, x, line.new(bar_index - 355, array.get(sr_levs, x) - zonePerc, bar_index, array.get(sr_levs, x) - zonePerc, xloc.bar_index, expandSR ? extend.both : extend.right, na))
array.set(sr_linesF, x, linefill.new(array.get(sr_linesH, x), array.get(sr_linesL, x), line_col))
for x = 0 to array.size(sr_labels) - 1
label.delete(array.get(sr_labels, x))
if (not na(array.get(sr_levs, x)) and enableSR)
lab_loc = close >= array.get(sr_levs, x) ? label.style_label_up : label.style_label_down
lab_col = close >= array.get(sr_levs, x) ? colorSup : colorRes
array.set(sr_labels, x, label.new(bar_index + label_loc, array.get(sr_levs, x), str.tostring(math.round_to_mintick(array.get(sr_levs, x))), color=lab_col , textcolor=#000000, style=lab_loc))
hlabel := enableSR ? label.new(bar_index + label_loc + math.round(math.sign(label_loc)) * 20, highestph, "High Level : " + str.tostring(highestph), color=hi_col, textcolor=#000000, style=label.style_label_down) : na
llabel := enableSR ? label.new(bar_index + label_loc + math.round(math.sign(label_loc)) * 20, lowestpl , "Low Level : " + str.tostring(lowestpl) , color=lo_col, textcolor=#000000, style=label.style_label_up ) : na
// Get components
rsi = ta.rsi(close, 28)
//rsiOb = rsi > 78 and rsi > ta.ema(rsi, 10)
//rsiOs = rsi < 27 and rsi < ta.ema(rsi, 10)
rsiOb = rsi > 65 and rsi > ta.ema(rsi, 10)
rsiOs = rsi < 35 and rsi < ta.ema(rsi, 10)
dHigh = securityNoRep(syminfo.tickerid, "D", high )
dLow = securityNoRep(syminfo.tickerid, "D", low )
dClose = securityNoRep(syminfo.tickerid, "D", close )
ema = ta.ema(close, 144)
emaBull = close > ema
equal_tf(res) => str.tonumber(res) == f_chartTfInMinutes() and not timeframe.isseconds
higher_tf(res) => str.tonumber(res) > f_chartTfInMinutes() or timeframe.isseconds
too_small_tf(res) => (timeframe.isweekly and res=="1") or (timeframe.ismonthly and str.tonumber(res) < 10)
securityNoRep1(sym, res, src) =>
bool bull_ = na
bull_ := equal_tf(res) ? src : bull_
bull_ := higher_tf(res) ? request.security(sym, res, src, barmerge.gaps_off, barmerge.lookahead_on) : bull_
bull_array = request.security_lower_tf(syminfo.tickerid, higher_tf(res) ? str.tostring(f_chartTfInMinutes()) + (timeframe.isseconds ? "S" : "") : too_small_tf(res) ? (timeframe.isweekly ? "3" : "10") : res, src)
if array.size(bull_array) > 1 and not equal_tf(res) and not higher_tf(res)
bull_ := array.pop(bull_array)
array.clear(bull_array)
bull_
// === BASE FUNCTIONS ===
// Returns MA input selection variant, default to SMA if blank or typo.
variant(type, src, len, offSig, offALMA) =>
v1 = ta.sma(src, len) // Simple
v2 = ta.ema(src, len) // Exponential
v3 = 2 * v2 - ta.ema(v2, len) // Double Exponential
v4 = 3 * (v2 - ta.ema(v2, len)) + ta.ema(ta.ema(v2, len), len) // Triple Exponential
v5 = ta.wma(src, len) // Weighted
v6 = ta.vwma(src, len) // Volume Weighted
v7 = 0.0
sma_1 = ta.sma(src, len) // Smoothed
v7 := na(v7 ) ? sma_1 : (v7 * (len - 1) + src) / len
v8 = ta.wma(2 * ta.wma(src, len / 2) - ta.wma(src, len), math.round(math.sqrt(len))) // Hull
v9 = ta.linreg(src, len, offSig) // Least Squares
v10 = ta.alma(src, len, offALMA, offSig) // Arnaud Legoux
v11 = ta.sma(v1, len) // Triangular (extreme smooth)
// SuperSmoother filter
// 2013 John F. Ehlers
a1 = math.exp(-1.414 * 3.14159 / len)
b1 = 2 * a1 * math.cos(1.414 * 3.14159 / len)
c2 = b1
c3 = -a1 * a1
c1 = 1 - c2 - c3
v12 = 0.0
v12 := c1 * (src + nz(src )) / 2 + c2 * nz(v12 ) + c3 * nz(v12 )
type == 'EMA' ? v2 : type == 'DEMA' ? v3 : type == 'TEMA' ? v4 : type == 'WMA' ? v5 : type == 'VWMA' ? v6 : type == 'SMMA' ? v7 : type == 'HullMA' ? v8 : type == 'LSMA' ? v9 : type == 'ALMA' ? v10 : type == 'TMA' ? v11 : type == 'SSMA' ? v12 : v1
// security wrapper for repeat calls
reso(exp, use, res) =>
security_1 = request.security(syminfo.tickerid, res, exp, gaps = barmerge.gaps_off, lookahead = barmerge.lookahead_on)
use ? security_1 : exp
// === /BASE FUNCTIONS ===
// === SERIES SETUP ===
closeSeries = variant(basisType, close , basisLen, offsetSigma, offsetALMA)
openSeries = variant(basisType, open , basisLen, offsetSigma, offsetALMA)
// === /SERIES ===
// Get Alternate resolution Series if selected.
closeSeriesAlt = reso(closeSeries, useRes, stratRes)
openSeriesAlt = reso(openSeries, useRes, stratRes)
//
lxTrigger = false
sxTrigger = false
leTrigger = ta.crossover (closeSeriesAlt, openSeriesAlt)
seTrigger = ta.crossunder(closeSeriesAlt, openSeriesAlt)
G_RISK = '■ ' + 'Risk Management'
//#region ———— <↓↓↓ G_RISK ↓↓↓> {
// ———————————
//Tooltip
T_LVL = '(%) Exit Level'
T_QTY = '(%) Adjust trade exit volume'
T_MSG = 'Paste JSON message for your bot'
//Webhook Message
O_LEMSG = 'Long Entry'
O_LXMSGSL = 'Long SL'
O_LXMSGTP1 = 'Long TP1'
O_LXMSGTP2 = 'Long TP2'
O_LXMSGTP3 = 'Long TP3'
O_LXMSG = 'Long Exit'
O_SEMSG = 'Short Entry'
O_SXMSGSL = 'Short SL'
O_SXMSGA = 'Short TP1'
O_SXMSGB = 'Short TP2'
O_SXMSGC = 'Short TP3'
O_SXMSGX = 'Short Exit'
// ——————————— | | | Line length guide |
i_lxLvlTP1 = input.float (0.2, 'Level TP1' , group = G_RISK,
tooltip = T_LVL)
i_lxQtyTP1 = input.float (80.0, 'Qty TP1' , group = G_RISK,
tooltip = T_QTY)
i_lxLvlTP2 = input.float (0.5, 'Level TP2' , group = G_RISK,
tooltip = T_LVL)
i_lxQtyTP2 = input.float (10.0, 'Qty TP2' , group = G_RISK,
tooltip = T_QTY)
i_lxLvlTP3 = input.float (7.0, 'Level TP3' , group = G_RISK,
tooltip = T_LVL)
i_lxQtyTP3 = input.float (2, 'Qty TP3' , group = G_RISK,
tooltip = T_QTY)
i_lxLvlSL = input.float (0.5, 'Stop Loss' , group = G_RISK,
tooltip = T_LVL)
i_sxLvlTP1 = i_lxLvlTP1
i_sxQtyTP1 = i_lxQtyTP1
i_sxLvlTP2 = i_lxLvlTP2
i_sxQtyTP2 = i_lxQtyTP2
i_sxLvlTP3 = i_lxLvlTP3
i_sxQtyTP3 = i_lxQtyTP3
i_sxLvlSL = i_lxLvlSL
G_MSG = '■ ' + 'Webhook Message'
i_leMsg = input.string (O_LEMSG ,'Long Entry' , group = G_MSG, tooltip = T_MSG)
i_lxMsgSL = input.string (O_LXMSGSL ,'Long SL' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP1 = input.string (O_LXMSGTP1,'Long TP1' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP2 = input.string (O_LXMSGTP2,'Long TP2' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP3 = input.string (O_LXMSGTP3,'Long TP3' , group = G_MSG, tooltip = T_MSG)
i_lxMsg = input.string (O_LXMSG ,'Long Exit' , group = G_MSG, tooltip = T_MSG)
i_seMsg = input.string (O_SEMSG ,'Short Entry' , group = G_MSG, tooltip = T_MSG)
i_sxMsgSL = input.string (O_SXMSGSL ,'Short SL' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP1 = input.string (O_SXMSGA ,'Short TP1' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP2 = input.string (O_SXMSGB ,'Short TP2' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP3 = input.string (O_SXMSGC ,'Short TP3' , group = G_MSG, tooltip = T_MSG)
i_sxMsg = input.string (O_SXMSGX ,'Short Exit' , group = G_MSG, tooltip = T_MSG)
i_src = close
G_DISPLAY = 'Display'
//
i_alertOn = input.bool (true, 'Alert Labels On/Off' , group = G_DISPLAY)
i_barColOn = input.bool (true, 'Bar Color On/Off' , group = G_DISPLAY)
// ———————————
// @function Calculate the Take Profit line, and the crossover or crossunder
f_tp(_condition, _conditionValue, _leTrigger, _seTrigger, _src, _lxLvlTP, _sxLvlTP)=>
var float _tpLine = 0.0
_topLvl = _src + (_src * (_lxLvlTP / 100))
_botLvl = _src - (_src * (_sxLvlTP / 100))
_tpLine := _condition != _conditionValue and _leTrigger ? _topLvl :
_condition != -_conditionValue and _seTrigger ? _botLvl :
nz(_tpLine )
// @function Similar to "ta.crossover" or "ta.crossunder"
f_cross(_scr1, _scr2, _over)=>
_cross = _over ? _scr1 > _scr2 and _scr1 < _scr2 :
_scr1 < _scr2 and _scr1 > _scr2
// ———————————
//
var float condition = 0.0
var float slLine = 0.0
var float entryLine = 0.0
//
entryLine := leTrigger and condition <= 0.0 ? close :
seTrigger and condition >= 0.0 ? close : nz(entryLine )
//
slTopLvl = i_src + (i_src * (i_lxLvlSL / 100))
slBotLvl = i_src - (i_src * (i_sxLvlSL / 100))
slLine := condition <= 0.0 and leTrigger ? slBotLvl :
condition >= 0.0 and seTrigger ? slTopLvl : nz(slLine )
slLong = f_cross(low, slLine, false)
slShort = f_cross(high, slLine, true )
//
= f_tp(condition, 1.2,leTrigger, seTrigger, i_src, i_lxLvlTP3, i_sxLvlTP3)
= f_tp(condition, 1.1,leTrigger, seTrigger, i_src, i_lxLvlTP2, i_sxLvlTP2)
= f_tp(condition, 1.0,leTrigger, seTrigger, i_src, i_lxLvlTP1, i_sxLvlTP1)
tp3Long = f_cross(high, tp3Line, true )
tp3Short = f_cross(low, tp3Line, false)
tp2Long = f_cross(high, tp2Line, true )
tp2Short = f_cross(low, tp2Line, false)
tp1Long = f_cross(high, tp1Line, true )
tp1Short = f_cross(low, tp1Line, false)
switch
leTrigger and condition <= 0.0 => condition := 1.0
seTrigger and condition >= 0.0 => condition := -1.0
tp3Long and condition == 1.2 => condition := 1.3
tp3Short and condition == -1.2 => condition := -1.3
tp2Long and condition == 1.1 => condition := 1.2
tp2Short and condition == -1.1 => condition := -1.2
tp1Long and condition == 1.0 => condition := 1.1
tp1Short and condition == -1.0 => condition := -1.1
slLong and condition >= 1.0 => condition := 0.0
slShort and condition <= -1.0 => condition := 0.0
lxTrigger and condition >= 1.0 => condition := 0.0
sxTrigger and condition <= -1.0 => condition := 0.0
longE = leTrigger and condition <= 0.0 and condition == 1.0
shortE = seTrigger and condition >= 0.0 and condition == -1.0
longX = lxTrigger and condition >= 1.0 and condition == 0.0
shortX = sxTrigger and condition <= -1.0 and condition == 0.0
longSL = slLong and condition >= 1.0 and condition == 0.0
shortSL = slShort and condition <= -1.0 and condition == 0.0
longTP3 = tp3Long and condition == 1.2 and condition == 1.3
shortTP3 = tp3Short and condition == -1.2 and condition == -1.3
longTP2 = tp2Long and condition == 1.1 and condition == 1.2
shortTP2 = tp2Short and condition == -1.1 and condition == -1.2
longTP1 = tp1Long and condition == 1.0 and condition == 1.1
shortTP1 = tp1Short and condition == -1.0 and condition == -1.1
// ——————————— {
//
if strategy.position_size <= 0 and longE and barstate.isconfirmed
strategy.entry(
'Long',
strategy.long,
alert_message = i_leMsg,
comment = 'LE')
if strategy.position_size > 0 and condition == 1.0
strategy.exit(
id = 'LXTP1',
from_entry = 'Long',
qty_percent = i_lxQtyTP1,
limit = tp1Line,
stop = slLine,
comment_profit = 'LXTP1',
comment_loss = 'SL',
alert_profit = i_lxMsgTP1,
alert_loss = i_lxMsgSL)
if strategy.position_size > 0 and condition == 1.1
strategy.exit(
id = 'LXTP2',
from_entry = 'Long',
qty_percent = i_lxQtyTP2,
limit = tp2Line,
stop = slLine,
comment_profit = 'LXTP2',
comment_loss = 'SL',
alert_profit = i_lxMsgTP2,
alert_loss = i_lxMsgSL)
if strategy.position_size > 0 and condition == 1.2
strategy.exit(
id = 'LXTP3',
from_entry = 'Long',
qty_percent = i_lxQtyTP3,
limit = tp3Line,
stop = slLine,
comment_profit = 'LXTP3',
comment_loss = 'SL',
alert_profit = i_lxMsgTP3,
alert_loss = i_lxMsgSL)
if longX
strategy.close(
'Long',
alert_message = i_lxMsg,
comment = 'LX')
//
if strategy.position_size >= 0 and shortE and barstate.isconfirmed
strategy.entry(
'Short',
strategy.short,
alert_message = i_leMsg,
comment = 'SE')
if strategy.position_size < 0 and condition == -1.0
strategy.exit(
id = 'SXTP1',
from_entry = 'Short',
qty_percent = i_sxQtyTP1,
limit = tp1Line,
stop = slLine,
comment_profit = 'SXTP1',
comment_loss = 'SL',
alert_profit = i_sxMsgTP1,
alert_loss = i_sxMsgSL)
if strategy.position_size < 0 and condition == -1.1
strategy.exit(
id = 'SXTP2',
from_entry = 'Short',
qty_percent = i_sxQtyTP2,
limit = tp2Line,
stop = slLine,
comment_profit = 'SXTP2',
comment_loss = 'SL',
alert_profit = i_sxMsgTP2,
alert_loss = i_sxMsgSL)
if strategy.position_size < 0 and condition == -1.2
strategy.exit(
id = 'SXTP3',
from_entry = 'Short',
qty_percent = i_sxQtyTP3,
limit = tp3Line,
stop = slLine,
comment_profit = 'SXTP3',
comment_loss = 'SL',
alert_profit = i_sxMsgTP3,
alert_loss = i_sxMsgSL)
if shortX
strategy.close(
'Short',
alert_message = i_sxMsg,
comment = 'SX')
// ———————————
c_tp = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.green
c_entry = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.blue
c_sl = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.red
p_tp1Line = plot (
condition == 1.0 or
condition == -1.0 ? tp1Line : na,
title = "TP Line 1",
color = c_tp,
linewidth = 1,
style = plot.style_linebr)
p_tp2Line = plot (
condition == 1.0 or
condition == -1.0 or
condition == 1.1 or
condition == -1.1 ? tp2Line : na,
title = "TP Line 2",
color = c_tp,
linewidth = 1,
style = plot.style_linebr)
p_tp3Line = plot (
condition == 1.0 or
condition == -1.0 or
condition == 1.1 or
condition == -1.1 or
condition == 1.2 or
condition == -1.2 ? tp3Line : na,
title = "TP Line 3",
color = c_tp,
linewidth = 1,
style = plot.style_linebr)
p_entryLine = plot (
condition >= 1.0 or
condition <= -1.0 ? entryLine : na,
title = "Entry Line",
color = c_entry,
linewidth = 1,
style = plot.style_linebr)
p_slLine = plot (
condition == 1.0 or
condition == -1.0 or
condition == 1.1 or
condition == -1.1 or
condition == 1.2 or
condition == -1.2 ? slLine : na,
title = "SL Line",
color = c_sl,
linewidth = 1,
style = plot.style_linebr)
fill(
p_tp3Line, p_entryLine,
color = leTrigger or seTrigger ? na :color.new(color.green, 90))
fill(
p_entryLine, p_slLine,
color = leTrigger or seTrigger ? na :color.new(color.red, 90))
//
plotshape(
i_alertOn and longE,
title = 'Long',
text = 'Long',
textcolor = color.white,
color = color.green,
style = shape.labelup,
size = size.tiny,
location = location.belowbar)
plotshape(
i_alertOn and shortE,
title = 'Short',
text = 'Short',
textcolor = color.white,
color = color.red,
style = shape.labeldown,
size = size.tiny,
location = location.abovebar)
plotshape(
i_alertOn and (longX or shortX) ? close : na,
title = 'Close',
text = 'Close',
textcolor = color.white,
color = color.gray,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
l_tp = i_alertOn and (longTP1 or shortTP1) ? close : na
plotshape(
l_tp,
title = "TP1 Cross",
text = "TP1",
textcolor = color.white,
color = color.olive,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
plotshape(
i_alertOn and (longTP2 or shortTP2) ? close : na,
title = "TP2 Cross",
text = "TP2",
textcolor = color.white,
color = color.olive,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
plotshape(
i_alertOn and (longTP3 or shortTP3) ? close : na,
title = "TP3 Cross",
text = "TP3",
textcolor = color.white,
color = color.olive,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
plotshape(
i_alertOn and (longSL or shortSL) ? close : na,
title = "SL Cross",
text = "SL",
textcolor = color.white,
color = color.maroon,
style = shape.labelup,
size = size.tiny,
location = location.absolute)
//
plot(
na,
title = "─── ───",
editable = false,
display = display.data_window)
plot(
condition,
title = "condition",
editable = false,
display = display.data_window)
plot(
strategy.position_size * 100,
title = ".position_size",
editable = false,
display = display.data_window)
//#endregion }
// ——————————— <↑↑↑ G_RISK ↑↑↑>
//#region ———— <↓↓↓ G_SCRIPT02 ↓↓↓> {
// @function Queues a new element in an array and de-queues its first element.
f_qDq(_array, _val) =>
array.push(_array, _val)
_return = array.shift(_array)
_return
var line a_slLine = array.new_line(1)
var line a_entryLine = array.new_line(1)
var line a_tp3Line = array.new_line(1)
var line a_tp2Line = array.new_line(1)
var line a_tp1Line = array.new_line(1)
var label a_slLabel = array.new_label(1)
var label a_tp3label = array.new_label(1)
var label a_tp2label = array.new_label(1)
var label a_tp1label = array.new_label(1)
var label a_entryLabel = array.new_label(1)
newEntry = longE or shortE
entryIndex = 1
entryIndex := newEntry ? bar_index : nz(entryIndex )
lasTrade = bar_index >= entryIndex
l_right = 10
line.delete(
f_qDq(a_slLine,
line.new(
entryIndex,
slLine,
last_bar_index + l_right,
slLine,
style = line.style_solid,
color = c_sl)))
line.delete(
f_qDq(a_entryLine,
line.new(
entryIndex,
entryLine,
last_bar_index + l_right,
entryLine,
style = line.style_solid,
color = color.blue)))
line.delete(
f_qDq(a_tp3Line,
line.new(
entryIndex,
tp3Line,
last_bar_index + l_right,
tp3Line,
style = line.style_solid,
color = c_tp)))
line.delete(
f_qDq(a_tp2Line,
line.new(
entryIndex,
tp2Line,
last_bar_index + l_right,
tp2Line,
style = line.style_solid,
color = c_tp)))
line.delete(
f_qDq(a_tp1Line,
line.new(
entryIndex,
tp1Line,
last_bar_index + l_right,
tp1Line,
style = line.style_solid,
color = c_tp)))
label.delete(
f_qDq(a_slLabel,
label.new(
last_bar_index + l_right,
slLine,
'SL: ' + str.tostring(slLine, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_sl)))
label.delete(
f_qDq(a_entryLabel,
label.new(
last_bar_index + l_right,
entryLine,
'Entry: ' + str.tostring(entryLine, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = color.blue)))
label.delete(
f_qDq(a_tp3label,
label.new(
last_bar_index + l_right,
tp3Line,
'TP3: ' + str.tostring(tp3Line, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_tp)))
label.delete(
f_qDq(a_tp2label,
label.new(
last_bar_index + l_right,
tp2Line,
'TP2: ' + str.tostring(tp2Line, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_tp)))
label.delete(
f_qDq(a_tp1label,
label.new(
last_bar_index + l_right,
tp1Line,
'TP1: ' + str.tostring(tp1Line, '##.###'),
style = label.style_label_left,
textcolor = color.white,
color = c_tp)))
// ———————————
//
if longE or shortE or longX or shortX
alert(message = 'Any Alert', freq = alert.freq_once_per_bar_close)
if longE
alert(message = 'Long Entry', freq = alert.freq_once_per_bar_close)
if shortE
alert(message = 'Short Entry', freq = alert.freq_once_per_bar_close)
if longX
alert(message = 'Long Exit', freq = alert.freq_once_per_bar_close)
if shortX
alert(message = 'Short Exit', freq = alert.freq_once_per_bar_close)
//#endregion }
// ——————————— <↑↑↑ G_SCRIPT03 ↑↑↑>
MCDX Plus - Leading Banker with RSIUnderstanding the Indicator
Core Components:
Red Bars (Banker): Represent institutional momentum, turning red when RSI_Banker ≥ BankerMA. Early build (blue background) signals accumulation.
Yellow Bars (Hot Money): Speculative activity, secondary confirmation.
Green Bars (Retailer): Inverse top layer, high values (>15) with lime background indicate retail overextension—sell signal.
Blue Line (Banker MA), Orange Line (Hot Money MA), Green Line (Retailer MA): Hull Moving Averages (20-period) for smoothed trends.
White Dashed Line (Forecast RSI): Projects Banker RSI 3-5 bars ahead.
Labels: "Bull Div - Early Buy" (divergence), "Oversold - Watch for Entry" (Stochastic RSI <20 crossover).
Leading Features:
RSI Divergence: Hidden bullish divergence flags early reversals.
Stochastic RSI: Oversold (<20) with crossover predicts pre-run entries.
Forecast Line: Guides ahead-of-curve entries.
Filters: MTF (set to "D" or "W"), priceEMA (200-period) confirms trend.
Trading Strategy
1. Pre-Market Setup (Daily Chart)
Timeframe: Use daily for swing (1-4 weeks), weekly for positional (months).
MTF Setting: Set mtfTimeframe to "W" on daily chart for weekly trend confirmation—ensures signals align with broader moves.
Chart Prep: Overlay priceEMA (200) and volume—buy above EMA, confirm with volume spikes.
Review: Check past runs to calibrate expectations.
2. Entry Timing (Catch the Big Run Early)
Signal:
"Bull Div - Early Buy" label + oversoldSignal ("Oversold - Watch for Entry") + forecastRsi >5.
Confirm with Golden Cross (Banker MA > Retailer MA) + price > priceEMA + volume > volMA.
Pro Action:
Enter 25% position on divergence/oversold signal, add 25% on Golden Cross, 50% if red bars hit 10.
Example: If divergence appears at 12.0 with forecast >5, buy; add on cross to 12.5.
Stop-Loss: 2-3% below recent low or priceEMA, tightened after 5% gain.
Target: 15-20% or red bars >15, exit partial at 10% gain.
3. Exit Timing (Lock Profits)
Signal:
Dead Cross (Banker MA < Retailer MA) + green bars >15 + price < priceEMA + oversoldSignal (lagging).
Pro Action:
Exit 25% on Dead Cross, 50% if green bars >15, full exit on price < priceEMA.
Trail stop at priceEMA or 1% below recent high.
Example: If Dead Cross hits at 14.0 with green >15, sell incrementally, locking 10-15% gains.
Re-Entry: Watch for new "Bull Div" on pullbacks.
4. Leverage Leading Signals
Divergence: Enter on "Bull Div" during downtrends—catches 70-80% of reversals per backtests.
Oversold: Use as pre-entry alert, buy on crossover confirmation.
Forecast: Buy if forecast Rsi crosses 5 upward—anticipates red bar growth 3-5 bars out.
5. Risk Management (Pro-Level)
Position Sizing: Risk 0.5-1% per trade, scale in/out based on red bar levels (5-15).
Stop-Loss: Dynamic—below swing low or trailing 2% below priceEMA.
Take-Profit: Scale out at 5%, 10%, 15% gains or when forecastRsi drops below 5.
Risk-Reward: Aim for 1:3, validated by backtesting
6. Volume and Context
Volume Spike: Enter only if volume > volMA during divergence/Golden Cross—signals institutional intent.
Market Trend: In bull markets, prioritize entries; in bear, use Dead Cross exits.
Confluence Engine Confluence Engine is a practical, non-repainting decision aid that scores market conditions from −100…+100 by combining six proven modules: Trend, Momentum, Volatility, Volume, Structure, and an HTF confirmation. It’s designed for crypto, forex, indices, and stocks, and it fires entries only on confirmed bar closes.
What’s inside
Trend: EMA 20/50/200 alignment plus a Supertrend/KAMA toggle (you choose the baseline).
Momentum: RSI + MACD with confirmed-pivot divergence detection.
Volatility: ATR% and Bollinger Band width vs its average to favor expansion over chop.
Volume: OBV-style cumulative flow slope + volume surge vs SMA×multiplier.
Market Structure: Confirmed pivots, BOS (break of structure) and CHOCH (change of character).
HTF Filter: Closed higher-timeframe context via request.security(..., barmerge.gaps_on, barmerge.lookahead_off).
Why it does not repaint
Signals are computed and plotted on closed bars only.
Pivots/divergences use confirmed pivot points (no forward look).
HTF series are fetched with lookahead_off and use the last closed HTF bar in realtime.
No future bar references are used for entries or alerts.
How to use (3 steps)
Pick a timeframe pair: use a 4–6× HTF multiplier (5m→30m, 15m→1h, 1h→4h, 4h→1D, 1D→1W).
Trade with the HTF: take longs only when the HTF filter is bullish; shorts only when bearish.
Prefer expansion: act when BB width > its average and ATR% is elevated; skip most signals in compression.
Suggested presets (start here)
Crypto (BTC/ETH): 15m→1h, 1h→4h. stLen=10, stMult=3.0, bbLen=20, surgeMul=1.8–2.2, thresholds +40 / −40 (intraday can try +35 / −35).
Forex majors: 15m→1h, 1h→4h. stLen=10–14, stMult=2.5–3.0, surgeMul=1.5–1.8, thresholds +35 / −35 (swing: +45 / −45).
US equities (liquid): 5m→30m/1h, 15m→1h/2h. stMult=3.0–3.5, surgeMul=1.6–2.0, thresholds +45 / −45 to reduce chop.
Indices (ES/NQ): 5m→30m, 15m→1h. Defaults are fine; start at +40 / −40.
Gold/Oil: 15m→1h, 1h→4h. Thresholds +35 / −35, surgeMul=1.6–1.9.
Inputs (plain English)
Use Supertrend (off = KAMA): choose the trend baseline.
EMA Fast/Mid/Slow: 20/50/200 by default for classic stack.
RSI/MACD + divergence pivots: momentum and exhaustion context.
ATR Length & BB Length: volatility regime detection.
Volume SMA & Surge Multiplier: defines “meaningful” volume spikes.
Pivot left/right & “Confirm BOS/CHOCH on Close”: structure strictness.
Enable HTF & Higher Timeframe: confirms the lower timeframe direction.
Thresholds (+long / −short): when the score crosses these, you get signals.
Signals & alerts (IDs preserved)
Entry shapes plot at bar close when the score crosses thresholds.
Alerts you can enable:
CONFLUENCE LONG — long entry signal
CONFLUENCE SHORT — short entry signal
BULLISH BIAS — score turned positive
BEARISH BIAS — score turned negative
Best practices
Focus on signals with HTF agreement and volatility expansion; require volume participation (surge or rising OBV slope) for higher quality.
Raise thresholds (+45/−45 or +50/−50) to reduce whipsaws in choppy sessions.
Lower thresholds (+35/−35) only if you also require volatility/volume filters.
Performance & scope
Works across crypto/FX/equities/indices; no broker data or special feeds required.
No repainting by design; signals/alerts are computed on closed bars.
As with any tool, results vary by regime; always combine with risk management.
Disclosure
This script is for educational purposes only and is not financial advice. Trading involves risk. Test on historical data and paper trade before using live.
Hilly's Advanced Crypto Scalping Strategy - 5 Min ChartTo determine the "best" input parameters for the Advanced Crypto Scalping Strategy on a 5-minute chart, we need to consider the goals of optimizing for profitability, minimizing false signals, and adapting to the volatile nature of cryptocurrencies. The default parameters in the script are a starting point, but the optimal values depend on the specific cryptocurrency pair, market conditions, and your risk tolerance. Below, I'll provide recommended input values based on common practices in crypto scalping, along with reasoning for each parameter. I’ll also suggest how to fine-tune them using TradingView’s backtesting and optimization tools.
Recommended Input Parameters
These values are tailored for a 5-minute chart for liquid cryptocurrencies like BTC/USD or ETH/USD on exchanges like Binance or Coinbase. They aim to balance signal frequency and accuracy for day trading.
Fast EMA Length (emaFastLen): 9
Reasoning: A 9-period EMA is commonly used in scalping to capture short-term price movements while remaining sensitive to recent price action. It reacts faster than the default 10, aligning with the 5-minute timeframe.
Slow EMA Length (emaSlowLen): 21
Reasoning: A 21-period EMA provides a good balance for identifying the broader trend on a 5-minute chart. It’s slightly longer than the default 20 to reduce noise while confirming the trend direction.
RSI Length (rsiLen): 14
Reasoning: The default 14-period RSI is a standard choice for momentum analysis. It works well for detecting overbought/oversold conditions without being too sensitive on short timeframes.
RSI Overbought (rsiOverbought): 75
Reasoning: Raising the overbought threshold to 75 (from 70) reduces false sell signals in strong bullish trends, which are common in crypto markets.
RSI Oversold (rsiOversold): 25
Reasoning: Lowering the oversold threshold to 25 (from 30) filters out weaker buy signals, ensuring entries occur during stronger reversals.
MACD Fast Length (macdFast): 12
Reasoning: The default 12-period fast EMA for MACD is effective for capturing short-term momentum shifts in crypto, aligning with scalping goals.
MACD Slow Length (macdSlow): 26
Reasoning: The default 26-period slow EMA is a standard setting that works well for confirming momentum trends without lagging too much.
MACD Signal Smoothing (macdSignal): 9
Reasoning: The default 9-period signal line is widely used and provides a good balance for smoothing MACD crossovers on a 5-minute chart.
Bollinger Bands Length (bbLen): 20
Reasoning: The default 20-period Bollinger Bands are effective for identifying volatility breakouts, which are key for scalping in crypto markets.
Bollinger Bands Multiplier (bbMult): 2.0
Reasoning: A 2.0 multiplier is standard and captures most price action within the bands. Increasing it to 2.5 could reduce signals but improve accuracy in highly volatile markets.
Stop Loss % (slPerc): 0.8%
Reasoning: A tighter stop loss of 0.8% (from 1.0%) suits the high volatility of crypto, helping to limit losses on false breakouts while keeping risk manageable.
Take Profit % (tpPerc): 1.5%
Reasoning: A 1.5% take-profit target (from 2.0%) aligns with scalping’s goal of capturing small, frequent gains. Crypto markets often see quick reversals, so a smaller target increases the likelihood of hitting profits.
Use Candlestick Patterns (useCandlePatterns): True
Reasoning: Enabling candlestick patterns (e.g., engulfing, hammer) adds confirmation to signals, reducing false entries in choppy markets.
Use Volume Filter (useVolumeFilter): True
Reasoning: The volume filter ensures signals occur during high-volume breakouts, which are more likely to sustain in crypto markets.
Signal Arrow Size (signalSize): 2.0
Reasoning: Increasing the arrow size to 2.0 (from 1.5) makes buy/sell signals more visible on the chart, especially on smaller screens or volatile price action.
Background Highlight Transparency (bgTransparency): 85
Reasoning: A slightly higher transparency (85 from 80) keeps the background highlights subtle but visible, avoiding chart clutter.
How to Apply These Parameters
Copy the Script: Use the Pine Script provided in the previous response.
Paste in TradingView: Open TradingView, go to the Pine Editor, paste the code, and click "Add to Chart."
Set Parameters: In the strategy settings, manually input the recommended values above or adjust them via the input fields.
Test on a 5-Minute Chart: Apply the strategy to a liquid crypto pair (e.g., BTC/USDT, ETH/USDT) on a 5-minute chart.
Fine-Tuning for Optimal Performance
To find the absolute best parameters for your specific trading pair and market conditions, use TradingView’s Strategy Tester and optimization features:
Backtesting:
Run the strategy on historical data for your chosen pair (e.g., BTC/USDT on Binance).
Check metrics like Net Profit, Profit Factor, Win Rate, and Max Drawdown in the Strategy Tester.
Focus on a sample period of at least 1–3 months to capture various market conditions (bull, bear, sideways).
Parameter Optimization:
In the Strategy Tester, click the settings gear next to the strategy name.
Enable optimization for key inputs like emaFastLen (test range: 7–12), emaSlowLen (15–25), slPerc (0.5–1.5), and tpPerc (1.0–3.0).
Run the optimization to find the combination with the highest net profit or best Sharpe ratio, but avoid over-optimization (curve-fitting) by testing on out-of-sample data.
Market-Specific Adjustments:
Volatile Pairs (e.g., DOGE/USDT): Use tighter stop losses (e.g., 0.5–0.7%) and smaller take-profit targets (e.g., 1.0–1.2%) to account for rapid price swings.
Stable Pairs (e.g., BTC/USDT): Slightly wider stop losses (e.g., 1.0–1.2%) and take-profit targets (e.g., 1.8–2.5%) may work better.
Trending Markets: Increase emaSlowLen (e.g., to 25–30) to follow stronger trends.
Choppy Markets: Tighten bbMult (e.g., to 1.8) and lower rsiOverbought/rsiOversold (e.g., to 70/30) to filter noise.
Forward Testing:
After backtesting, run the strategy in real-time on a demo account for 1–2 weeks to validate performance under current market conditions.
Important Notes
No Universal "Best" Numbers: Optimal parameters vary by crypto pair, exchange, and market conditions (e.g., bull vs. bear market). The suggested values are a starting point based on common scalping practices.
Risk Management: Never risk more than 1–2% of your account per trade. Adjust position sizing in TradingView’s strategy settings to align with your risk tolerance.
Market Volatility: Crypto markets are highly volatile. Test the strategy on your specific pair and adjust parameters if signals are too frequent or too rare.
Not Financial Advice: This is an educational tool. Backtest thoroughly and use a demo account before trading with real funds.
If you want me to generate a chart showing backtest performance for specific parameters or to tweak the script further (e.g., adding more indicators or adjusting signal logic), let me know!can you add clear buy ans sell signs above the candles in this codeTo add clear buy and sell signals above the candles in the provided Pine Script, I'll modify the existing code to include prominent text labels directly above (for sell signals) and below (for buy signals) the candles. These labels will be larger, color-coded, and positioned to avoid clutter, ensuring they are easily visible on the chart. The core strategy logic (EMA, RSI, MACD, Bollinger Bands, candlestick patterns, and volume filter) will remain unchanged, and I'll reuse the same artifact_id since this is an update to the previous script.AdvancedCryptoScalpingStrategy.pinex-pine
2ATR / Close %Certainly. Here is the English version of the indicator description you requested.
---
### **2ATR Stop-Loss Ratio**
This indicator provides a straightforward calculation of **what percentage a 2ATR (Average True Range) move represents relative to the current price**. It's a specialized tool designed to help traders set dynamic, volatility-based stop-loss levels.
---
### **Purpose of the Indicator**
Many traders use a **2ATR** as their standard for setting a stop-loss, believing it's a good measure of a stock's typical movement. However, it can be difficult to quickly determine the exact percentage a 2ATR drop represents from the current price. This indicator solves that problem by giving you a clear, single number that shows the **anticipated percentage loss before you even enter a position**.
---
### **How It Works**
The indicator is calculated using a simple formula:
**(2 * ATR(20) / Current Price) * 100**
* `ATR(20)`: The Average True Range over the last 20 periods. This period can be customized in the indicator's settings.
* `Current Price`: The closing price at the time of calculation.
---
### **How to Use It**
* **Assess Risk**: A higher number on the indicator means greater volatility, indicating a wider stop-loss range.
* **Set a Stop-Loss**: If the indicator shows **3%**, it means a 2ATR move is roughly a 3% change from the current price. This gives you a clear understanding of the potential loss.
* **Adjust Position Size**: If the potential percentage loss is larger than you're comfortable with, you can use this information to reduce your position size, effectively managing your risk.
This tool is especially useful for trading highly volatile stocks, as it helps you establish a clear and effective risk management strategy.
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator
Purpose
This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns.
What a martingale is
A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged:
Lose one leg → increase next position size
Lose again → increase again
Win → reset to the base size
The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops.
What it plots
Equity – simulated portfolio equity including compounding
Buy & Hold – equity from holding the chart symbol for context
Optional helpers – last trade outcome, current streak length, current allocation fraction
Optional diagnostics – daily portfolio return, rolling drawdown, metrics table
Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands
Model assumptions
Bar-close execution with no slippage or commissions
Shorting allowed and frictionless
No margin interest, borrow fees, or position limits
No intrabar moves or gaps within a bar (returns are close-to-close)
Sizing applies to equity fraction only and is capped by your setting
All results are hypothetical and for education only.
How the simulator applies it
1) Directional signal
You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts.
2) Sizing after losses and wins
Position size is a fraction of equity:
Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity
Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double
Reset after win – return to the initial allocation
Max allocation cap – hard ceiling to prevent runaway growth
At a high level the size after k consecutive losses is
alloc(k) = min( cap , base × factor^k ) .
In practice the simulator changes size only when a leg ends and its PnL is known.
3) Equity update
Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds:
eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) .
This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled.
Why traders experiment with martingale sizing
Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn
Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests
Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live
Why martingale is dangerous
Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic:
Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N.
Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible.
No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels.
Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest.
Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs.
Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected.
The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty.
Interpreting losing streaks with numbers
A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check:
If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare.
If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap.
This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions
Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests..
Using the simulator productively
Parameter studies
Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond.
Initial allocation – lower base reduces volatility and drawdowns across the board
Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive
Max cap – the most important brake; many users keep it between 20 and 50 percent
Signal selection
Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each.
Diagnostics to watch
Use the built-in metrics to quantify risk:
Max Drawdown – worst peak-to-trough equity loss
Sharpe and Sortino – volatility and downside-adjusted return
VaR 95 percent and CVaR – tail risk measures from the realized distribution
Alpha and Beta – relationship to your chosen benchmark
If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see
Monte Carlo exploration
When enabled, the forecast draws many synthetic paths from your realized daily returns:
Choose a horizon and a number of runs
Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path
Use the table to read the expected return over the horizon and the tail outcomes
Remember it is a sketch based on your recent distribution, not a predictor
Concrete examples
Example A: Modest martingale
Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing.
Example B: Aggressive martingale
Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk.
Strengths
Bar-by-bar, transparent computation of equity from stance and size
Explicit handling of wins, losses, streaks, and caps
Portable signal inputs so you can A–B test ideas quickly
Risk diagnostics and forward uncertainty visualization in one place
Example, Rolling Max Drawdown
Limitations and important notes
Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs.
No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled.
Signals are evaluated on closes. Real execution and fills will differ.
Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes.
All results are hypothetical. Use this as an educational tool, not a production risk engine.
Practical tips
Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples.
Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg.
Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear.
Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off.
If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop.
Settings recap
Backtest start date and initial capital
Initial allocation, increase-after-loss factor, max allocation cap
Signal source selector
Trading days per year and risk-free rate
Benchmark symbol for Alpha and Beta
UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown
Monte Carlo controls for enable, runs, horizon, and result table
Final thoughts
A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
Yelober - Market Internal direction+ Key levelsYelober – Market Internals + Key Levels is a focused intraday trading tool that helps you spot high-probability price direction by anchoring decisions to structure that matters: yesterday’s RTH High/Low, today’s pre-market High/Low, and a fast Value Area/POC from the prior session. Paired with a compact market internals dashboard (NYSE/NASDAQ UVOL vs. DVOL ratios, VOLD slopes, TICK/TICKQ momentum, and optional VIX trend), it gives you a real-time read on breadth so you can choose which direction to trade, when to enter (breaks, retests, or fades at PMH/PML/VAH/VAL/POC), and how to plan exits as internals confirm or deteriorate. On top of these intraday decision benefits, it also allows traders—in a very subtle but powerful way—to keep an eye on the VIX and immediately recognize significant spikes or sharp decreases that should be factored in before entering a trade, or used as a quick signal to modify an existing position. In short: clear levels for the chart, live internals for the context, and a smarter, rules-based path to execution.
# Yelober – Market Internals + Key Levels
*A TradingView indicator for session key levels + real‑time market internals (NYSE/NASDAQ TICK, UVOL/DVOL/VOLD, and VIX).*
**Script name in Pine:** `Yelober - Market Internal direction+ Key levels` (Pine v6)
---
## 1) What this indicator does
**Purpose:** Help intraday traders quickly find high‑probability reaction zones and read market internals momentum without switching charts. It overlays yesterday/today’s **automatic price levels** on your active chart and shows a **market breadth table** that summarizes NYSE/NASDAQ buying pressure and TICK direction, with an optional VIX trend read.
### Key features at a glance
* **Automatic Price Levels (overlay on chart)**
* Yesterday’s High/Low of Day (**yHoD**, **yLoD**)
* Extended Hours High/Low (**yEHH**, **yEHL**) across yesterday AH + today pre‑market
* Today’s Pre‑Market High/Low (**PMH**, **PML**)
* Yesterday’s **Value Area High/Low** (**VAH/VAL**) and **Point of Control (POC)** computed from a volume profile of yesterday’s **regular session**
* Smart de‑duplication:
* Shows **only the higher** of (yEHH vs PMH) and **only the lower** of (yEHL vs PML) to avoid redundant bands
* **Market Breadth Table (on‑chart table)**
* **NYSE ratio** = UVOL/DVOL (signed) with **VOLD slope** from session open
* **NASDAQ ratio** = UVOLQ/DVOLQ (signed) with **VOLDQ slope** from session open
* **TICK** and **TICKQ**: live cumulative ratio and short‑term slope
* **VIX** (optional): current value + slope over a configurable lookback/timeframe
* Color‑coded trends with sensible thresholds and optional normalization
---
## 2) How to use it (trader workflow)
1. **Mark your reaction zones**
* Watch **yHoD/yLoD**, **PMH/PML**, and **VAH/VAL/POC** for first touches, break/retest, and failure tests.
* Expect increased responsiveness when multiple levels cluster (e.g., PMH ≈ VAH ≈ daily pivot).
2. **Read the breadth panel for context**
* **NYSE/NASDAQ ratio** (>1 = more up‑volume than down‑volume; <−1 = down‑dominant). Strong green across both favors long setups; red favors short setups.
* **VOLD slopes** (NYSE & NASDAQ): positive and accelerating → broadening participation; negative → persistent pressure.
* **TICK/TICKQ**: cumulative ratio and **slope arrows** (↗ / ↘ / →). Use the slope to gauge **near‑term thrust or fade**.
* **VIX slope**: rising VIX (red) often coincides with risk‑off; falling VIX (green) with risk‑on.
3. **Confluence = higher confidence**
* Example: Price reclaims **PMH** while **NYSE/NASDAQ ratios** print green and **TICK slopes** point ↗ — consider break‑and‑go; if VIX slope is ↘, that adds risk‑on confidence.
* Example: Price rejects **VAH** while **VOLD slopes** roll negative and VIX ↗ — consider fade/reversal.
4. **Risk management**
* Place stops just beyond key levels tested; if breadth flips, tighten or exit.
> **Timeframes:** Works best on 1–15m charts for intraday. Value Area is computed from **yesterday’s RTH**; choose a smaller calculation timeframe (e.g., 5–15m) for stable profiles.
---
## 3) Inputs & settings (what each option controls)
### Global Style
* **Enable all automatic price levels**: master toggle for yHoD/yLoD, yEHH/yEHL, PMH/PML, VAH/VAL/POC.
* **Line style/width**: applies to all drawn levels.
* **Label size/style** and **label color linking**: use the same color as the line or override with a global label color.
* **Maximum bars lookback**: how far the script scans to build yesterday metrics (performance‑sensitive).
### Value Area / Volume Profile
* **Enable Value Area calculations** *(on by default)*: computes yesterday’s **POC**, **VAH**, **VAL** from a simplified intraday volume profile built from yesterday’s **regular session bars**.
* **Max Volume Profile Points** *(default 50)*: lower values = faster; higher = more precise.
* **Value Area Calculation Timeframe** *(default 15)*: the security timeframe used when collecting yesterday’s highs/lows/volumes.
### Individual Level Toggles & Colors
* **yHoD / yLoD** (yesterday high/low)
* **yEHH / yEHL** (yesterday AH + today pre‑market extremes)
* **PMH / PML** (today pre‑market extremes)
* **VAH / VAL / POC** (yesterday RTH value area + point of control)
### Market Breadth Panel
* **Show NYSE / NASDAQ / VIX**: choose which series to display in the table.
* **Table Position / Size / Background Color**: UI placement and legibility.
* **Slope Averaging Periods** *(default 5)*: number of recent TICK/TICKQ ratio points used in slope calculation.
* **Candles for Rate** *(default 10)* & **Normalize Rate**: VIX slope calculation as % change between `now` and `n` candles ago; normalize divides by `n`.
* **VIX Timeframe**: optionally compute VIX on a higher TF (e.g., 15, 30, 60) for a smoother regime read.
* **Volume Normalization** (NYSE & NASDAQ): display VOLD slopes scaled to `tens/thousands/millions/10th millions` for readable magnitudes; color thresholds adapt to your choice.
---
## 4) Data sources & definitions
* **UVOL/VOLD (NYSE)** and **UVOLQ/DVOLQ/VOLDQ (NASDAQ)** via `request.security()`
* **Ratio** = `UVOL/DVOL` (signed; negative when down‑volume dominates)
* **VOLD slope** ≈ `(VOLD_now − VOLD_open) / bars_since_open`, then normalized per your setting
* **TICK/TICKQ**: cumulative sum of prints this session with **positives vs negatives ratio**, plus a simple linear regression **slope** of the last `N` ratio values
* **VIX**: value and slope across a user‑selected timeframe and lookback
* **Sessions (EST/EDT)**
* **Regular:** 09:30–16:00
* **Pre‑Market:** 04:00–09:30
* **After Hours:** 16:00–20:00
* **Extended‑hours extremes** combine **yesterday AH** + **today PM**
> **Note:** All session checks are done with TradingView’s `time(…,"America/New_York")` context. If your broker’s RTH differs (e.g., futures), adjust expectations accordingly.
---
## 5) How the algorithms work (plain English)
### A) Key Levels
* **Yesterday’s RTH High/Low**: scans yesterday’s bars within 09:30–16:00 and records the extremes + bar indices.
* **Extended Hours**: scans yesterday AH and today PM to get **yEHH/yEHL**. Script shows **either yEHH or PMH** (whichever is **higher**) and **either yEHL or PML** (whichever is **lower**) to avoid duplicate bands stacked together.
* **Value Area & POC (RTH only)**
* Build a coarse volume profile with `Max Volume Profile Points` buckets across the price range formed by yesterday’s RTH bars.
* Distribute each bar’s volume uniformly across the buckets it spans (fast approximation to keep Pine within execution limits).
* **POC** = bucket with max volume. **VA** expands from POC outward until **70%** of cumulative volume is enclosed → yields **VAH/VAL**.
### B) Market Breadth Table
* **NYSE/NASDAQ Ratio**: signed UVOL/DVOL with basic coloring.
* **VOLD Slopes**: from session open to current, normalized to human‑readable units; colors flip green/red based on thresholds that map to your normalization setting (e.g., ±2M for NYSE, ±3.5×10M for NASDAQ).
* **TICK/TICKQ Slope**: linear regression over the last `N` ratio points → **↗ / → / ↘** with the rounded slope value.
* **VIX Slope**: % change between now and `n` candles ago (optionally divided by `n`). Red when rising beyond threshold; green when falling.
---
## 6) Recommended presets
* **Stocks (liquid, intraday)**
* Value Area **ON**, `Max Volume Points` = **40–60**, **Timeframe** = **5–15**
* Breadth: show **NYSE & NASDAQ & VIX**, `Slope periods` = **5–8**, `Candles for rate` = **10–20**, **Normalize VIX** = **ON**
* **Index futures / very high‑volume symbols**
* If you see Pine timeouts, set `Max Volume Points` = **20–40** or temporarily **disable Value Area**.
* Keep breadth panel **ON** (it’s light). Consider **VIX timeframe = 15/30** for regime clarity.
---
## 7) Tips, edge cases & performance
* **Performance:** The volume profile is capped (`maxBarsToProcess ≤ 500` and bucketed) to keep it responsive. If you experience slowdowns, reduce `Max Volume Points`, `Maximum bars lookback`, or disable Value Area.
* **Redundant lines:** The script **intentionally suppresses** PMH/PML when yEHH/yEHL are more extreme, and vice‑versa.
* **Label visibility:** Use `Label style = none` if you only want clean lines and read values from the right‑end labels.
* **Futures/RTH differences:** Value Area is from **yesterday’s RTH** only; for 24h instruments the RTH period may not reflect overnight structure.
* **Session transitions:** PMH/PML tracking stops as soon as RTH starts; values persist as static levels for the session.
---
## 8) Known limitations
* Uses public TradingView symbols: `UVOL`, `VOLD`, `UVOLQ`, `DVOLQ`, `VOLDQ`, `TICK`, `TICKQ`, `VIX`. If your data plan or region limits any symbol, the corresponding table rows may show `na`.
* The VA/POC approximation assumes uniform distribution of each bar’s volume across its high–low. That’s fast but not a tick‑level profile.
* Works best on US equities with standard NY session; alternative sessions may need code changes.
---
## 9) Troubleshooting
* **“Script is too slow / timed out”** → Lower `Max Volume Points`, lower `Maximum bars lookback`, or toggle **OFF** `Enable Value Area calculations` for that instrument.
* **Missing breadth values** → Ensure the symbols above load on your account; try reloading chart or switching timeframes once.
* **Overlapping labels** → Set `Label style = none` or reduce label size.
---
## 10) Version / license / contribution
* **Version:** Initial public release (Pine v6).
* **Author:** © yelober
* **License:** Free for community use and enhancement. Please keep author credit.
* **Contributing:** Open PRs/ideas: presets, alert conditions, multi‑day VA composites, optional mid‑value (`(VAH+VAL)/2`), session filter for futures, and alertable state machine for breadth regime transitions.
---
## 11) Quick start (TL;DR)
1. Add the indicator and **keep default settings**.
2. Trade **reactions** at yHoD/yLoD/PMH/PML/VAH/VAL/POC.
3. Use the **breadth table**: look for **green ratios + ↗ slopes** (risk‑on) or **red ratios + ↘ slopes** (risk‑off). Check **VIX** slope for confirmation.
4. Manage risk around levels; when breadth flips against you, tighten or exit.
---
### Changelog (public)
* **v1.0:** First community release with automatic RTH levels, VA/POC approximation, breadth dashboard (NYSE/NASDAQ/TICK/TICKQ/VIX) with normalization and adaptive color thresholds.
Pump/Dump Detector [Modular]//@version=5
indicator("Pump/Dump Detector ", overlay=true)
// ————— Inputs —————
risk_pct = input.float(1.0, "Risk %", minval=0.1)
capital = input.float(100000, "Capital")
stop_multiplier = input.float(1.5, "Stop Multiplier")
target_multiplier = input.float(2.0, "Target Multiplier")
volume_mult = input.float(2.0, "Volume Spike Multiplier")
rsi_low_thresh = input.int(15, "RSI Oversold Threshold")
rsi_high_thresh = input.int(85, "RSI Overbought Threshold")
rsi_len = input.int(2, "RSI Length")
bb_len = input.int(20, "BB Length")
bb_mult = input.float(2.0, "BB Multiplier")
atr_len = input.int(14, "ATR Length")
show_signals = input.bool(true, "Show Entry Signals")
use_orderflow = input.bool(true, "Use Order Flow Proxy")
use_ml_flag = input.bool(false, "Use ML Risk Flag")
use_session_filter = input.bool(true, "Use Volatility Sessions")
// ————— Symbol Filter (Optional) —————
symbol_nq = input.bool(true, "Enable NQ")
symbol_es = input.bool(true, "Enable ES")
symbol_gold = input.bool(true, "Enable Gold")
is_nq = str.contains(syminfo.ticker, "NQ")
is_es = str.contains(syminfo.ticker, "ES")
is_gold = str.contains(syminfo.ticker, "GC")
symbol_filter = (symbol_nq and is_nq) or (symbol_es and is_es) or (symbol_gold and is_gold)
// ————— Calculations —————
rsi = ta.rsi(close, rsi_len)
atr = ta.atr(atr_len)
basis = ta.sma(close, bb_len)
dev = bb_mult * ta.stdev(close, bb_len)
bb_upper = basis + dev
bb_lower = basis - dev
rolling_vol = ta.sma(volume, 20)
vol_spike = volume > volume_mult * rolling_vol
// ————— Session Filter (EST) —————
est_offset = -5
est_hour = (hour + est_offset + 24) % 24
session_filter = (est_hour >= 18 or est_hour < 6) or (est_hour >= 14 and est_hour < 17)
session_ok = not use_session_filter or session_filter
// ————— Order Flow Proxy —————
mfi = ta.mfi(close, 14)
buy_imbalance = ta.crossover(mfi, 50)
sell_imbalance = ta.crossunder(mfi, 50)
reversal_candle = close > open and close > ta.highest(close , 3)
// ————— ML Risk Flag (Placeholder) —————
ml_risk_flag = use_ml_flag and (ta.sma(close, 5) > ta.sma(close, 20))
// ————— Entry Conditions —————
long_cond = symbol_filter and session_ok and vol_spike and rsi < rsi_low_thresh and close < bb_lower and (not use_orderflow or (buy_imbalance and reversal_candle)) and (not use_ml_flag or ml_risk_flag)
short_cond = symbol_filter and session_ok and vol_spike and rsi > rsi_high_thresh and (not use_orderflow or sell_imbalance) and (not use_ml_flag or ml_risk_flag)
// ————— Position Sizing —————
risk_amt = capital * (risk_pct / 100)
position_size = risk_amt / atr
// ————— Plot Signals —————
plotshape(show_signals and long_cond, title="Long Signal", location=location.belowbar, color=color.green, style=shape.triangleup, size=size.small)
plotshape(show_signals and short_cond, title="Short Signal", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small)
// ————— Alerts —————
alertcondition(long_cond, title="Long Entry Alert", message="Pump fade detected: Long setup triggered")
alertcondition(short_cond, title="Short Entry Alert", message="Dump detected: Short setup triggered")
🏆 AI Gold Master IndicatorsAI Gold Master Indicators - Technical Overview
Core Purpose: Advanced Pine Script indicator that analyzes 20 technical indicators simultaneously for XAUUSD (Gold) trading, generating automated buy/sell signals through a sophisticated scoring system.
Key Features
📊 Multi-Indicator Analysis
Processes 20 indicators: RSI, MACD, Bollinger Bands, EMA crossovers, Stochastic, Williams %R, CCI, ATR, Volume, ADX, Parabolic SAR, Ichimoku, MFI, ROC, Fibonacci retracements, Support/Resistance, Candlestick patterns, MA Ribbon, VWAP, Market Structure, and Cloud MA
Each indicator generates BUY (🟢), SELL (🔴), or NEUTRAL (⚪) signals
⚖️ Dual Scoring Systems
Weighted System: Each indicator has configurable weights (10-200 points, total 1000), with higher weights for critical indicators like RSI (150) and MACD (150)
Simple Count System: Basic counting of BUY vs SELL signals across all indicators
🎯 Signal Generation
Configurable thresholds for both systems (weighted score threshold: 400-600 recommended)
Dynamic risk management with ATR-based TP/SL levels
Signal strength filtering to reduce false positives
📈 Advanced Configuration
Customizable thresholds for all 20 indicators (RSI levels, Stochastic bounds, Williams %R zones, etc.)
Dynamic weight bonuses that adapt to dominant market trends
Risk management with configurable TP1/TP2 multipliers and stop losses
🎛️ Visual Interface
Real-time master table displaying all indicators, their values, weights, and current signals
Visual trading signals (triangles) with detailed labels
Optional TP/SL lines and performance statistics
💡 Optimization Features
Gold-specific parameter tuning
Trend analysis with configurable lookback periods
Volume spike detection and volatility analysis
Multi-timeframe compatibility (15m, 1H, 4H recommended)
The system combines traditional technical analysis with modern weighting algorithms to provide comprehensive market analysis specifically optimized for gold trading.
Ragazzi è una meraviglia, pronto all uso, già configurato provatelo divertitevi e fate tanti soldoni poi magari una piccola donazione spontanea sarebbe molto gradita visto il tempo, risorse e gli insulti della moglie che mi diceva che perdevo tempo, fatemi sapere se vi piace.
nel codice troverete una descrizione del funzionamento se vi vengono in mente delle idee per migliorarlo contattatemi troverete i mie contatti in tabella un saluto.
Asistente de Barra de Estado ADX
// This is an all-in-one indicator designed to visually represent the market environment
// based on the G2 (trend-following) and SMOG (reversal/ranging) trading systems.
// It replaces the need for a separate ADX indicator.
//
// FEATURES:
//
// 1. Multi-Timeframe ADX:
// - 5-Minute ADX (Blue Line - The "Referee"): Determines the overall market environment (Trending or Ranging).
// - 1-Minute ADX (Yellow Line - The "Trigger"): Measures immediate momentum for trade entries.
//
// 2. Environment Background Coloring:
// The indicator's own background panel changes color to provide an instant signal:
// - Green: G2 Bullish Environment (5-min ADX > 25 & Price is Trending Up)
// - Red: G2 Bearish Environment (5-min ADX > 25 & Price is Trending Down)
// - Gray: Gray Zone (Indecisive/Risky Market, 5-min ADX between 20-25)
// - Blue: SMOG Environment (Weak/Ranging Market, 5-min ADX < 20)
//
// 3. Reference Lines:
// Includes horizontal lines at the key 20 and 25 levels for easy reference.
//
// HOW TO USE:
// Use this indicator as the primary tool to decide whether to look for a G2
// (trend-following) or a SMOG (reversal) setup.
//
EMA Range OscillatorEMA Range Oscillator (ERO) - User Guide
Overview
The EMA Range Oscillator (ERO) is a technical indicator that measures the distance between two Exponential Moving Averages (EMAs) and the distance between price and EMA. It normalizes these distances into a 0-100 range, helping traders identify trend strength, market momentum, and potential reversal points.
Components
Main Line
Green Line: EMA20 > EMA50 (Uptrend)
Red Line: EMA20 < EMA50 (Downtrend)
Histogram
White Histogram: Price distance from EMA20
Key Levels
Upper Level (80): High divergence zone
Middle Level (50): Neutral zone
Lower Level (20): Low divergence zone
Parameters
ParameterDefaultDescriptionFast EMA20Short-term EMA periodSlow EMA50Long-term EMA periodNormalization Period100Lookback period for scalingUpper80Upper threshold levelLower20Lower threshold level
How to Read the Indicator
High Values (Above 80)
Strong trend in progress
EMAs are widely separated
High momentum
Potential overbought/oversold conditions
Watch for possible trend exhaustion
Low Values (Below 20)
Consolidation phase
EMAs are close together
Low volatility
Potential breakout setup
Range-bound market conditions
Middle Zone (20-80)
Normal market conditions
Moderate trend strength
Balanced momentum
Look for directional clues from color changes
Trend Display Table (with Change Alerts)📌 Indicator: Trend Display Table (with Change Alerts)
This indicator helps identify trend direction based on a 15-minute 20 SMA compared against a 10 EMA applied to that SMA.
Trend Logic:
Bullish → 20 SMA crosses above 10 EMA (on SMA values)
Bearish → 20 SMA crosses below 10 EMA (on SMA values)
Neutral → No crossover (trend continues from previous state)
Display:
A compact trend table appears on the chart (top-right), showing the current trend with customizable colors, font size, and background.
Alerts:
Alerts are triggered only when the trend changes (from Bullish → Bearish or Bearish → Bullish).
This prevents repeated alerts on every bar.
✅ Useful for:
Confirming higher timeframe trend bias
Filtering trades in choppy markets
Getting notified instantly when the trend flips
DYNAMIC TRADING DASHBOARDStudy Material for the "Dynamic Trading Dashboard"
This Dynamic Trading Dashboard is designed as an educational tool within the TradingView environment. It compiles commonly used market indicators and analytical methods into one visual interface so that traders and learners can see relationships between indicators and price action. Understanding these indicators, step by step, can help traders develop discipline, improve technical analysis skills, and build strategies. Below is a detailed explanation of each module.
________________________________________
1. Price and Daily Reference Points
The dashboard displays the current price, along with percentage change compared to the day’s opening price. It also highlights whether the price is moving upward or downward using directional symbols. Alongside, it tracks daily high, low, open, and daily range.
For traders, daily levels provide valuable reference points. The daily high and low are considered intraday support and resistance, while the median price of the day often acts as a pivot level for mean reversion traders. Monitoring these helps learners see how price oscillates within daily ranges.
________________________________________
2. VWAP (Volume Weighted Average Price)
VWAP is calculated as a cumulative average price weighted by volume. The dashboard compares the current price with VWAP, showing whether the market is trading above or below it.
For traders, VWAP is often a guide for institutional order flow. Price trading above VWAP suggests bullish sentiment, while trading below VWAP indicates bearish sentiment. Learners can use VWAP as a training tool to recognize trend-following vs. mean reversion setups.
________________________________________
3. Volume Analysis
The system distinguishes between buy volume (when the closing price is higher than the open) and sell volume (when the closing price is lower than the open). A progress bar highlights the ratio of buying vs. selling activity in percentage.
This is useful because volume confirms price action. For instance, if prices rise but sell volume dominates, it can signal weakness. New traders learning with this tool should focus on how volume often precedes price reversals and trends.
________________________________________
4. RSI (Relative Strength Index)
RSI is a momentum oscillator that measures price strength on a scale from 0 to 100. The dashboard classifies RSI readings into overbought (>70), oversold (<30), or neutral zones and adds visual progress bars.
RSI helps learners understand momentum shifts. During training, one should notice how trending markets can keep RSI extended for longer periods (not immediate reversal signals), while range-bound markets react more sharply to RSI extremes. It is an excellent tool for practicing trend vs. range identification.
________________________________________
5. MACD (Moving Average Convergence Divergence)
The MACD indicator involves a fast EMA, slow EMA, and signal line, with focus on crossovers. The dashboard shows whether a “bullish cross” (MACD above signal line) or “bearish cross” (MACD below signal line) has occurred.
MACD teaches traders to identify trend momentum shifts and divergence. During practice, traders can explore how MACD signals align with VWAP trends or RSI levels, which helps in building a structured multi-indicator analysis.
________________________________________
6. Stochastic Oscillator
This indicator compares the current close relative to a range of highs and lows over a period. Displayed values oscillate between 0 and 100, marking zones of overbought (>80) and oversold (<20).
Stochastics are useful for students of trading to recognize short-term momentum changes. Unlike RSI, it reacts faster to price volatility, so false signals are common. Part of the training exercise can be to observe how stochastic “flips” can align with volume surges or daily range endpoints.
________________________________________
7. Trend & Momentum Classification
The dashboard adds simple labels for trend (uptrend, downtrend, neutral) based on RSI thresholds. Additionally, it provides quick momentum classification (“bullish hold”, “bearish hold”, or neutral).
This is beneficial for beginners as it introduces structured thinking: differentiating long-term market bias (trend) from short-term directional momentum. By combining both, traders can practice filtering signals instead of trading randomly.
________________________________________
8. Accumulation / Distribution Bias
Based on RSI levels, the script generates simplified tags such as “Accumulate Long”, “Accumulate Short”, or “Wait”.
This is purely an interpretive guide, helping learners think in terms of accumulation phases (when markets are low) and distribution phases (when markets are high). It reinforces the concept that trading is not only directional but also involves timing.
________________________________________
9. Overall Market Status and Score
Finally, the dashboard compiles multiple indicators (VWAP position, RSI, MACD, Stochastics, and price vs. median levels) into a Market Score expressed as a percentage. It also labels the market as Overbought, Oversold, or Normal.
This scoring system isn’t a recommendation but a learning framework. Students can analyze how combining different indicators improves decision-making. The key training focus here is confluence: not depending on one indicator but observing when several conditions align.
Extended Study Material with Formulas
________________________________________
1. Daily Reference Levels (High, Low, Open, Median, Range)
• Day High (H): Maximum price of the session.
DayHigh=max(Hightoday)DayHigh=max(Hightoday)
• Day Low (L): Minimum price of the session.
DayLow=min(Lowtoday)DayLow=min(Lowtoday)
• Day Open (O): Opening price of the session.
DayOpen=OpentodayDayOpen=Opentoday
• Day Range:
Range=DayHigh−DayLowRange=DayHigh−DayLow
• Median: Mid-point between high and low.
Median=DayHigh+DayLow2Median=2DayHigh+DayLow
These act as intraday guideposts for seeing how far the price has stretched from its key reference levels.
________________________________________
2. VWAP (Volume Weighted Average Price)
VWAP considers both price and volume for a weighted average:
VWAPt=∑i=1t(Pricei×Volumei)∑i=1tVolumeiVWAPt=∑i=1tVolumei∑i=1t(Pricei×Volumei)
Here, Price_i can be the average price (High + Low + Close) ÷ 3, also known as hlc3.
• Interpretation: Price above VWAP = bullish bias; Price below = bearish bias.
________________________________________
3. Volume Buy/Sell Analysis
The dashboard splits total volume into buy volume and sell volume based on candle type.
• Buy Volume:
BuyVol=Volumeif Close > Open, else 0BuyVol=Volumeif Close > Open, else 0
• Sell Volume:
SellVol=Volumeif Close < Open, else 0SellVol=Volumeif Close < Open, else 0
• Buy Ratio (%):
VolumeRatio=BuyVolBuyVol+SellVol×100VolumeRatio=BuyVol+SellVolBuyVol×100
This helps traders gauge who is in control during a session—buyers or sellers.
________________________________________
4. RSI (Relative Strength Index)
RSI measures strength of momentum by comparing gains vs. losses.
Step 1: Compute average gains (AG) and losses (AL).
AG=Average of Upward Closes over N periodsAG=Average of Upward Closes over N periodsAL=Average of Downward Closes over N periodsAL=Average of Downward Closes over N periods
Step 2: Calculate relative strength (RS).
RS=AGALRS=ALAG
Step 3: RSI formula.
RSI=100−1001+RSRSI=100−1+RS100
• Used to detect overbought (>70), oversold (<30), or neutral momentum zones.
________________________________________
5. MACD (Moving Average Convergence Divergence)
• Fast EMA:
EMAfast=EMA(Close,length=fast)EMAfast=EMA(Close,length=fast)
• Slow EMA:
EMAslow=EMA(Close,length=slow)EMAslow=EMA(Close,length=slow)
• MACD Line:
MACD=EMAfast−EMAslowMACD=EMAfast−EMAslow
• Signal Line:
Signal=EMA(MACD,length=signal)Signal=EMA(MACD,length=signal)
• Histogram:
Histogram=MACD−SignalHistogram=MACD−Signal
Crossovers between MACD and Signal are used in studying bullish/bearish phases.
________________________________________
6. Stochastic Oscillator
Stochastic compares the current close against a range of highs and lows.
%K=Close−LowestLowHighestHigh−LowestLow×100%K=HighestHigh−LowestLowClose−LowestLow×100
Where LowestLow and HighestHigh are the lowest and highest values over N periods.
The %D line is a smooth version of %K (using a moving average).
%D=SMA(%K,smooth)%D=SMA(%K,smooth)
• Values above 80 = overbought; below 20 = oversold.
________________________________________
7. Trend and Momentum Classification
This dashboard generates simplified trend/momentum logic using RSI.
• Trend:
• RSI < 40 → Downtrend
• RSI > 60 → Uptrend
• In Between → Neutral
• Momentum Bias:
• RSI > 70 → Bullish Hold
• RSI < 30 → Bearish Hold
• Otherwise Neutral
This is not predictive, only a classification framework for educational use.
________________________________________
8. Accumulation/Distribution Bias
Based on extreme RSI values:
• RSI < 25 → Accumulate Long Bias
• RSI > 80 → Accumulate Short Bias
• Else → Wait/No Action
This helps learners understand the idea of accumulation at lows (strength building) and distribution at highs (profit booking).
________________________________________
9. Overall Market Status and Score
The tool adds up 5 bullish conditions:
1. Price above VWAP
2. RSI > 50
3. MACD > Signal
4. Stochastic > 50
5. Price above Daily Median
BullishScore=ConditionsMet5×100BullishScore=5ConditionsMet×100
Then it categorizes the market:
• RSI > 70 or Stoch > 80 → Overbought
• RSI < 30 or Stoch < 20 → Oversold
• Else → Normal
This encourages learners to think in terms of probabilistic conditions instead of single-indicator signals.
________________________________________
⚠️ Warning:
• Trading financial markets involves substantial risk.
• You can lose more money than you invest.
• Past performance of indicators does not guarantee future results.
• This script must not be copied, resold, or republished without authorization from aiTrendview.
By using this material or the code, you agree to take full responsibility for your trading decisions and acknowledge that this is not financial advice.
________________________________________
⚠️ Disclaimer and Warning (From aiTrendview)
This Dynamic Trading Dashboard is created strictly for educational and research purposes on the TradingView platform. It does not provide financial advice, buy/sell recommendations, or guaranteed returns. Any use of this tool in live trading is completely at the user’s own risk. Markets are inherently risky; losses can exceed initial investment.
The intellectual property of this script and its methodology belongs to aiTrendview. Unauthorized reproduction, modification, or redistribution of this code is strictly prohibited. By using this study material or the script, you acknowledge personal responsibility for any trading outcomes. Always consult professional financial advisors before making investment decisions.
Advanced Volume Profile Pro Delta + POC + VAH/VAL# Advanced Volume Profile Pro - Delta + POC + VAH/VAL Analysis System
## WHAT THIS SCRIPT DOES
This script creates a comprehensive volume profile analysis system that combines traditional volume-at-price distribution with delta volume calculations, Point of Control (POC) identification, and Value Area (VAH/VAL) analysis. Unlike standard volume indicators that show only total volume over time, this script analyzes volume distribution across price levels and estimates buying vs selling pressure using multiple calculation methods to provide deeper market structure insights.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Traditional volume indicators show when volume occurs but not where price finds acceptance or rejection. Standalone volume profiles lack directional bias information, while basic delta calculations don't provide structural context. Traders need to understand both volume distribution AND directional sentiment at key price levels.
**The Solution:** This script implements an integrated approach that:
- Maps volume distribution across price levels using configurable row density
- Estimates delta (buying vs selling pressure) using three different methodologies
- Identifies Point of Control (highest volume price level) for key support/resistance
- Calculates Value Area boundaries where 70% of volume traded
- Provides real-time alerts for key level interactions and volume imbalances
**Unique Features:**
1. **Developing POC Visualization**: Real-time tracking of Point of Control migration throughout the session via blue dotted trail, revealing institutional accumulation/distribution patterns before they complete
2. **Multi-Method Delta Calculation**: Price Action-based, Bid/Ask estimation, and Cumulative methods for different market conditions
3. **Adaptive Timeframe System**: Auto-adjusts calculation parameters based on chart timeframe for optimal performance
4. **Flexible Profile Types**: N Bars Back (precise control), Days Back (calendar-based), and Session-based analysis modes
5. **Advanced Imbalance Detection**: Identifies and highlights significant buying/selling imbalances with configurable thresholds
6. **Comprehensive Alert System**: Monitors POC touches, Value Area entry/exit, and major volume imbalances
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Volume Profile Methodology:
**1. Price Level Distribution:**
- Divides price range into user-defined rows (10-50 configurable)
- Calculates row height: `(Highest Price - Lowest Price) / Number of Rows`
- Distributes each bar's volume across price levels it touched proportionally
**2. Delta Volume Calculation Methods:**
**Price Action Method:**
```
Price Range = High - Low
Buy Pressure = (Close - Low) / Price Range
Sell Pressure = (High - Close) / Price Range
Buy Volume = Total Volume × Buy Pressure
Sell Volume = Total Volume × Sell Pressure
Delta = Buy Volume - Sell Volume
```
**Bid/Ask Estimation Method:**
```
Average Price = (High + Low + Close) / 3
Buy Volume = Close > Average ? Volume × 0.6 : Volume × 0.4
Sell Volume = Total Volume - Buy Volume
```
**Cumulative Method:**
```
Buy Volume = Close > Open ? Volume : Volume × 0.3
Sell Volume = Close ≤ Open ? Volume : Volume × 0.3
```
**3. Point of Control (POC) Identification:**
- Scans all price levels to find maximum volume concentration
- POC represents the price level with highest trading activity
- Acts as significant support/resistance level
- **Developing POC Feature**: Tracks POC evolution in real-time via blue dotted trail, showing how institutional interest migrates throughout the session. Upward POC migration indicates accumulation patterns, downward migration suggests distribution, providing early trend signals before price confirmation.
**4. Value Area Calculation:**
- Starts from POC and expands up/down to encompass 70% of total volume
- VAH (Value Area High): Upper boundary of value area
- VAL (Value Area Low): Lower boundary of value area
- Expansion algorithm prioritizes direction with higher volume
**5. Adaptive Range Selection:**
Based on profile type and timeframe optimization:
- **N Bars Back**: Fixed lookback period with performance optimization (20-500 bars)
- **Days Back**: Calendar-based analysis with automatic timeframe adjustment (1-365 days)
- **Session**: Current trading session or custom session times
### Performance Optimization Features:
- **Sampling Algorithm**: Reduces calculation load on large datasets while maintaining accuracy
- **Memory Management**: Clears previous drawings to prevent performance degradation
- **Safety Constraints**: Prevents excessive memory usage with configurable limits
## HOW TO USE THIS SCRIPT
### Initial Setup:
1. **Profile Configuration**: Select profile type based on trading style:
- N Bars Back: Precise control over data range
- Days Back: Intuitive calendar-based analysis
- Session: Real-time session development
2. **Row Density**: Set number of rows (30 default) - more rows = higher resolution, slower performance
3. **Delta Method**: Choose calculation method based on market type:
- Price Action: Best for trending markets
- Bid/Ask Estimate: Good for ranging markets
- Cumulative: Smoothed approach for volatile markets
4. **Visual Settings**: Configure colors, position (left/right), and display options
### Reading the Profile:
**Volume Bars:**
- **Length**: Represents relative volume at that price level
- **Color**: Green = net buying pressure, Red = net selling pressure
- **Intensity**: Darker colors indicate volume imbalances above threshold
**Key Levels:**
- **POC (Blue Line)**: Highest volume price - major support/resistance
- **VAH (Purple Dashed)**: Value Area High - upper boundary of fair value
- **VAL (Orange Dashed)**: Value Area Low - lower boundary of fair value
- **Value Area Fill**: Shaded region showing main trading range
**Developing POC Trail:**
- **Blue Dotted Lines**: Show real-time POC evolution throughout the session
- **Migration Patterns**: Upward trail indicates bullish accumulation, downward trail suggests bearish distribution
- **Early Signals**: POC movement often precedes price movement, providing advance warning of institutional activity
- **Institutional Footprints**: Reveals where smart money concentrated volume before final POC establishment
### Trading Applications:
**Support/Resistance Analysis:**
- POC acts as magnetic price level - expect reactions
- VAH/VAL provide intermediate support/resistance levels
- Profile edges show areas of low volume acceptance
**Developing POC Analysis:**
- **Upward Migration**: POC moving higher = institutional accumulation, bullish bias
- **Downward Migration**: POC moving lower = institutional distribution, bearish bias
- **Stable POC**: Tight clustering = balanced market, range-bound conditions
- **Early Trend Detection**: POC direction change often precedes price breakouts
**Entry Strategies:**
- Buy at VAL with POC as target (in uptrends)
- Sell at VAH with POC as target (in downtrends)
- Breakout plays above/below profile extremes
**Volume Imbalance Trading:**
- Strong buying imbalance (>60% threshold) suggests continued upward pressure
- Strong selling imbalance suggests continued downward pressure
- Imbalances near key levels provide high-probability setups
**Multi-Timeframe Context:**
- Use higher timeframe profiles for major levels
- Lower timeframe profiles for precise entries
- Session profiles for intraday trading structure
## SCRIPT SETTINGS EXPLANATION
### Volume Profile Settings:
- **Profile Type**: Determines data range for calculation
- N Bars Back: Exact number of bars (20-500 range)
- Days Back: Calendar days with timeframe adaptation (1-365 days)
- Session: Trading session-based (intraday focus)
- **Number of Rows**: Profile resolution (10-50 range)
- **Profile Width**: Visual width as chart percentage (10-50%)
- **Value Area %**: Volume percentage for VA calculation (50-90%, 70% standard)
- **Auto-Adjust**: Automatically optimizes for different timeframes
### Delta Volume Settings:
- **Show Delta Volume**: Enable/disable delta calculations
- **Delta Calculation Method**: Choose methodology based on market conditions
- **Highlight Imbalances**: Visual emphasis for significant volume imbalances
- **Imbalance Threshold**: Percentage for imbalance detection (50-90%)
### Session Settings:
- **Session Type**: Daily, Weekly, Monthly, or Custom periods
- **Custom Session Time**: Define specific trading hours
- **Previous Sessions**: Number of historical sessions to display
### Days Back Settings:
- **Lookback Days**: Number of calendar days to analyze (1-365)
- **Automatic Calculation**: Script automatically converts days to bars based on timeframe:
- Intraday: Accounts for 6.5 trading hours per day
- Daily: 1 bar per day
- Weekly/Monthly: Proportional adjustment
### N Bars Back Settings:
- **Lookback Bars**: Exact number of bars to analyze (20-500)
- **Precise Control**: Best for systematic analysis and backtesting
### Visual Customization:
- **Colors**: Bullish (green), Bearish (red), and level colors
- **Profile Position**: Left or Right side of chart
- **Profile Offset**: Distance from current price action
- **Labels**: Show/hide level labels and values
- **Smooth Profile Bars**: Enhanced visual appearance
### Alert Configuration:
- **POC Touch**: Alerts when price interacts with Point of Control
- **VA Entry/Exit**: Alerts for Value Area boundary interactions
- **Major Imbalance**: Alerts for significant volume imbalances
## VISUAL FEATURES
### Profile Display:
- **Horizontal Bars**: Volume distribution across price levels
- **Color Coding**: Delta-based coloring for directional bias
- **Smooth Rendering**: Optional smoothing for cleaner appearance
- **Transparency**: Configurable opacity for chart readability
### Level Lines:
- **POC**: Solid blue line with optional label
- **VAH/VAL**: Dashed colored lines with value displays
- **Extension**: Lines extend across relevant time periods
- **Value Area Fill**: Optional shaded region between VAH/VAL
### Information Table:
- **Current Values**: Real-time POC, VAH, VAL prices
- **VA Range**: Value Area width calculation
- **Positioning**: Multiple table positions available
- **Text Sizing**: Adjustable for different screen sizes
## IMPORTANT USAGE NOTES
**Realistic Expectations:**
- Volume profile analysis provides structural context, not trading signals
- Delta calculations are estimations based on price action, not actual order flow
- Past volume distribution does not guarantee future price behavior
- Combine with other analysis methods for comprehensive market view
**Best Practices:**
- Use appropriate profile types for your trading style:
- Day Trading: Session or Days Back (1-5 days)
- Swing Trading: Days Back (10-30 days) or N Bars Back
- Position Trading: Days Back (60-180 days)
- Consider market context (trending vs ranging conditions)
- Verify key levels with additional technical analysis
- Monitor profile development for changing market structure
**Performance Considerations:**
- Higher row counts increase calculation complexity
- Large lookback periods may affect chart performance
- Auto-adjust feature optimizes for most use cases
- Consider using session profiles for intraday efficiency
**Limitations:**
- Delta calculations are estimations, not actual transaction data
- Profile accuracy depends on available price/volume history
- Effectiveness varies across different instruments and market conditions
- Requires understanding of volume profile concepts for optimal use
**Data Requirements:**
- Requires volume data for accurate calculations
- Works best on liquid instruments with consistent volume
- May be less effective on very low volume or exotic instruments
This script serves as a comprehensive volume analysis tool for traders who need detailed market structure information with integrated directional bias analysis and real-time POC development tracking for informed trading decisions.
Bottom Reversal Radar — Berk v1.4Bottom Reversal Radar — Berk v1.4
What it does:
Combines RSI recovery after oversold, MACD bull cross, close above EMA8, near-EMA200 proximity, volume expansion, and simple bullish divergence (pivot lows) into a single score.
Signal: Trigger when Score ≥ Threshold (default 3). Set alert via Create Alert → “Dipten Dönüş — Ana Sinyal” → Once per bar close.
How it works
RSI recovery: After touching oversold (30), RSI crosses up 35 within last X bars.
MACD bull cross: MACD Line crosses above Signal.
Close above EMA8 and BOS (close above recent swing high) confirm momentum.
Near EMA200: Price within −5%…+2% band adds a point.
Volume spike: Volume ≥ 1.5× SMA(20) adds a point.
Bullish divergence: Lower price low + higher RSI low (pivot 3/3) adds a point.
Inputs
RSI(14), rsiOS=30, rsiRecover=35, Volume SMA(20) with 1.5× multiplier, EMA200 proximity band −5%…+2%, lookbackBars=5, Score threshold default 3.
Usage tips
Best on Daily / 4H. If too many false positives: raise threshold to 4 and volume to 1.8–2.0×.
Pair with Screener filters: RSI≥35, MACD Line>Signal, Price above EMA8, Volume/Avg(20)≥1.5, and near EMA200 (%).
Disclaimer
For educational purposes only. Not financial advice.
Release notes (v1.4)
Fixed bullDiv typo; simplified visuals; Pine v5.
Tags: rsi, macd, ema, volume, divergence, reversal, trend, screener, bist, stocks, crypto
Seasonality Monte Carlo Forecaster [BackQuant]Seasonality Monte Carlo Forecaster
Plain-English overview
This tool projects a cone of plausible future prices by combining two ideas that traders already use intuitively: seasonality and uncertainty. It watches how your market typically behaves around this calendar date, turns that seasonal tendency into a small daily “drift,” then runs many randomized price paths forward to estimate where price could land tomorrow, next week, or a month from now. The result is a probability cone with a clear expected path, plus optional overlays that show how past years tended to move from this point on the calendar. It is a planning tool, not a crystal ball: the goal is to quantify ranges and odds so you can size, place stops, set targets, and time entries with more realism.
What Monte Carlo is and why quants rely on it
• Definition . Monte Carlo simulation is a way to answer “what might happen next?” when there is randomness in the system. Instead of producing a single forecast, it generates thousands of alternate futures by repeatedly sampling random shocks and adding them to a model of how prices evolve.
• Why it is used . Markets are noisy. A single point forecast hides risk. Monte Carlo gives a distribution of outcomes so you can reason in probabilities: the median path, the 68% band, the 95% band, tail risks, and the chance of hitting a specific level within a horizon.
• Core strengths in quant finance .
– Path-dependent questions : “What is the probability we touch a stop before a target?” “What is the expected drawdown on the way to my objective?”
– Pricing and risk : Useful for path-dependent options, Value-at-Risk (VaR), expected shortfall (CVaR), stress paths, and scenario analysis when closed-form formulas are unrealistic.
– Planning under uncertainty : Portfolio construction and rebalancing rules can be tested against a cloud of plausible futures rather than a single guess.
• Why it fits trading workflows . It turns gut feel like “seasonality is supportive here” into quantitative ranges: “median path suggests +X% with a 68% band of ±Y%; stop at Z has only ~16% odds of being tagged in N days.”
How this indicator builds its probability cone
1) Seasonal pattern discovery
The script builds two day-of-year maps as new data arrives:
• A return map where each calendar day stores an exponentially smoothed average of that day’s log return (yesterday→today). The smoothing (90% old, 10% new) behaves like an EWMA, letting older seasons matter while adapting to new information.
• A volatility map that tracks the typical absolute return for the same calendar day.
It calculates the day-of-year carefully (with leap-year adjustment) and indexes into a 365-slot seasonal array so “March 18” is compared with past March 18ths. This becomes the seasonal bias that gently nudges simulations up or down on each forecast day.
2) Choice of randomness engine
You can pick how the future shocks are generated:
• Daily mode uses a Gaussian draw with the seasonal bias as the mean and a volatility that comes from realized returns, scaled down to avoid over-fitting. It relies on the Box–Muller transform internally to turn two uniform random numbers into one normal shock.
• Weekly mode uses bootstrap sampling from the seasonal return history (resampling actual historical daily drifts and then blending in a fraction of the seasonal bias). Bootstrapping is robust when the empirical distribution has asymmetry or fatter tails than a normal distribution.
Both modes seed their random draws deterministically per path and day, which makes plots reproducible bar-to-bar and avoids flickering bands.
3) Volatility scaling to current conditions
Markets do not always live in average volatility. The engine computes a simple volatility factor from ATR(20)/price and scales the simulated shocks up or down within sensible bounds (clamped between 0.5× and 2.0×). When the current regime is quiet, the cone narrows; when ranges expand, the cone widens. This prevents the classic mistake of projecting calm markets into a storm or vice versa.
4) Many futures, summarized by percentiles
The model generates a matrix of price paths (capped at 100 runs for performance inside TradingView), each path stepping forward for your selected horizon. For each forecast day it sorts the simulated prices and pulls key percentiles:
• 5th and 95th → approximate 95% band (outer cone).
• 16th and 84th → approximate 68% band (inner cone).
• 50th → the median or “expected path.”
These are drawn as polylines so you can immediately see central tendency and dispersion.
5) A historical overlay (optional)
Turn on the overlay to sketch a dotted path of what a purely seasonal projection would look like for the next ~30 days using only the return map, no randomness. This is not a forecast; it is a visual reminder of the seasonal drift you are biasing toward.
Inputs you control and how to think about them
Monte Carlo Simulation
• Price Series for Calculation . The source series, typically close.
• Enable Probability Forecasts . Master switch for simulation and drawing.
• Simulation Iterations . Requested number of paths to run. Internally capped at 100 to protect performance, which is generally enough to estimate the percentiles for a trading chart. If you need ultra-smooth bands, shorten the horizon.
• Forecast Days Ahead . The length of the cone. Longer horizons dilute seasonal signal and widen uncertainty.
• Probability Bands . Draw all bands, just 95%, just 68%, or a custom level (display logic remains 68/95 internally; the custom number is for labeling and color choice).
• Pattern Resolution . Daily leans on day-of-year effects like “turn-of-month” or holiday patterns. Weekly biases toward day-of-week tendencies and bootstraps from history.
• Volatility Scaling . On by default so the cone respects today’s range context.
Plotting & UI
• Probability Cone . Plots the outer and inner percentile envelopes.
• Expected Path . Plots the median line through the cone.
• Historical Overlay . Dotted seasonal-only projection for context.
• Band Transparency/Colors . Customize primary (outer) and secondary (inner) band colors and the mean path color. Use higher transparency for cleaner charts.
What appears on your chart
• A cone starting at the most recent bar, fanning outward. The outer lines are the ~95% band; the inner lines are the ~68% band.
• A median path (default blue) running through the center of the cone.
• An info panel on the final historical bar that summarizes simulation count, forecast days, number of seasonal patterns learned, the current day-of-year, expected percentage return to the median, and the approximate 95% half-range in percent.
• Optional historical seasonal path drawn as dotted segments for the next 30 bars.
How to use it in trading
1) Position sizing and stop logic
The cone translates “volatility plus seasonality” into distances.
• Put stops outside the inner band if you want only ~16% odds of a stop-out due to noise before your thesis can play.
• Size positions so that a test of the inner band is survivable and a test of the outer band is rare but acceptable.
• If your target sits inside the 68% band at your horizon, the payoff is likely modest; outside the 68% but inside the 95% can justify “one-good-push” trades; beyond the 95% band is a low-probability flyer—consider scaling plans or optionality.
2) Entry timing with seasonal bias
When the median path slopes up from this calendar date and the cone is relatively narrow, a pullback toward the lower inner band can be a high-quality entry with a tight invalidation. If the median slopes down, fade rallies toward the upper band or step aside if it clashes with your system.
3) Target selection
Project your time horizon to N bars ahead, then pick targets around the median or the opposite inner band depending on your style. You can also anchor dynamic take-profits to the moving median as new bars arrive.
4) Scenario planning & “what-ifs”
Before events, glance at the cone: if the 95% band already spans a huge range, trade smaller, expect whips, and avoid placing stops at obvious band edges. If the cone is unusually tight, consider breakout tactics and be ready to add if volatility expands beyond the inner band with follow-through.
5) Options and vol tactics
• When the cone is tight : Prefer long gamma structures (debit spreads) only if you expect a regime shift; otherwise premium selling may dominate.
• When the cone is wide : Debit structures benefit from range; credit spreads need wider wings or smaller size. Align with your separate IV metrics.
Reading the probability cone like a pro
• Cone slope = seasonal drift. Upward slope means the calendar has historically favored positive drift from this date, downward slope the opposite.
• Cone width = regime volatility. A widening fan tells you that uncertainty grows fast; a narrow cone says the market typically stays contained.
• Mean vs. price gap . If spot trades well above the median path and the upper band, mean-reversion risk is high. If spot presses the lower inner band in an up-sloping cone, you are in the “buy fear” zone.
• Touches and pierces . Touching the inner band is common noise; piercing it with momentum signals potential regime change; the outer band should be rare and often brings snap-backs unless there is a structural catalyst.
Methodological notes (what the code actually does)
• Log returns are used for additivity and better statistical behavior: sim_ret is applied via exp(sim_ret) to evolve price.
• Seasonal arrays are updated online with EWMA (90/10) so the model keeps learning as each bar arrives.
• Leap years are handled; indexing still normalizes into a 365-slot map so the seasonal pattern remains stable.
• Gaussian engine (Daily mode) centers shocks on the seasonal bias with a conservative standard deviation.
• Bootstrap engine (Weekly mode) resamples from observed seasonal returns and adds a fraction of the bias, which captures skew and fat tails better.
• Volatility adjustment multiplies each daily shock by a factor derived from ATR(20)/price, clamped between 0.5 and 2.0 to avoid extreme cones.
• Performance guardrails : simulations are capped at 100 paths; the probability cone uses polylines (no heavy fills) and only draws on the last confirmed bar to keep charts responsive.
• Prerequisite data : at least ~30 seasonal entries are required before the model will draw a cone; otherwise it waits for more history.
Strengths and limitations
• Strengths :
– Probabilistic thinking replaces single-point guessing.
– Seasonality adds a small but meaningful directional bias that many markets exhibit.
– Volatility scaling adapts to the current regime so the cone stays realistic.
• Limitations :
– Seasonality can break around structural changes, policy shifts, or one-off events.
– The number of paths is performance-limited; percentile estimates are good for trading, not for academic precision.
– The model assumes tomorrow’s randomness resembles recent randomness; if regime shifts violently, the cone will lag until the EWMA adapts.
– Holidays and missing sessions can thin the seasonal sample for some assets; be cautious with very short histories.
Tuning guide
• Horizon : 10–20 bars for tactical trades; 30+ for swing planning when you care more about broad ranges than precise targets.
• Iterations : The default 100 is enough for stable 5/16/50/84/95 percentiles. If you crave smoother lines, shorten the horizon or run on higher timeframes.
• Daily vs. Weekly : Daily for equities and crypto where month-end and turn-of-month effects matter; Weekly for futures and FX where day-of-week behavior is strong.
• Volatility scaling : Keep it on. Turn off only when you intentionally want a “pure seasonality” cone unaffected by current turbulence.
Workflow examples
• Swing continuation : Cone slopes up, price pulls into the lower inner band, your system fires. Enter near the band, stop just outside the outer line for the next 3–5 bars, target near the median or the opposite inner band.
• Fade extremes : Cone is flat or down, price gaps to the upper outer band on news, then stalls. Favor mean-reversion toward the median, size small if volatility scaling is elevated.
• Event play : Before CPI or earnings on a proxy index, check cone width. If the inner band is already wide, cut size or prefer options structures that benefit from range.
Good habits
• Pair the cone with your entry engine (breakout, pullback, order flow). Let Monte Carlo do range math; let your system do signal quality.
• Do not anchor blindly to the median; recalc after each bar. When the cone’s slope flips or width jumps, the plan should adapt.
• Validate seasonality for your symbol and timeframe; not every market has strong calendar effects.
Summary
The Seasonality Monte Carlo Forecaster wraps institutional risk planning into a single overlay: a data-driven seasonal drift, realistic volatility scaling, and a probabilistic cone that answers “where could we be, with what odds?” within your trading horizon. Use it to place stops where randomness is less likely to take you out, to set targets aligned with realistic travel, and to size positions with confidence born from distributions rather than hunches. It will not predict the future, but it will keep your decisions anchored to probabilities—the language markets actually speak.
Correlation HeatMap Matrix Data [TradingFinder]🔵 Introduction
Correlation is a statistical measure that shows the degree and direction of a linear relationship between two assets.
Its value ranges from -1 to +1 : +1 means perfect positive correlation, 0 means no linear relationship, and -1 means perfect negative correlation.
In financial markets, correlation is used for portfolio diversification, risk management, pairs trading, intermarket analysis, and identifying divergences.
Correlation HeatMap Matrix Data TradingFinder is a Pine Script v6 library that calculates and returns raw correlation matrix data between up to 20 symbols. It only provides the data – it does not draw or render the heatmap – making it ideal for use in other scripts that handle visualization or further analysis. The library uses ta.correlation for fast and accurate calculations.
It also includes two helper functions for visual styling :
CorrelationColor(corr) : takes the correlation value as input and generates a smooth gradient color, ranging from strong negative to strong positive correlation.
CorrelationTextColor(corr) : takes the correlation value as input and returns a text color that ensures optimal contrast over the background color.
Library
"Correlation_HeatMap_Matrix_Data_TradingFinder"
CorrelationColor(corr)
Parameters:
corr (float)
CorrelationTextColor(corr)
Parameters:
corr (float)
Data_Matrix(Corr_Period, Sym_1, Sym_2, Sym_3, Sym_4, Sym_5, Sym_6, Sym_7, Sym_8, Sym_9, Sym_10, Sym_11, Sym_12, Sym_13, Sym_14, Sym_15, Sym_16, Sym_17, Sym_18, Sym_19, Sym_20)
Parameters:
Corr_Period (int)
Sym_1 (string)
Sym_2 (string)
Sym_3 (string)
Sym_4 (string)
Sym_5 (string)
Sym_6 (string)
Sym_7 (string)
Sym_8 (string)
Sym_9 (string)
Sym_10 (string)
Sym_11 (string)
Sym_12 (string)
Sym_13 (string)
Sym_14 (string)
Sym_15 (string)
Sym_16 (string)
Sym_17 (string)
Sym_18 (string)
Sym_19 (string)
Sym_20 (string)
🔵 How to use
Import the library into your Pine Script using the import keyword and its full namespace.
Decide how many symbols you want to include in your correlation matrix (up to 20). Each symbol must be provided as a string, for example FX:EURUSD .
Choose the correlation period (Corr\_Period) in bars. This is the lookback window used for the calculation, such as 20, 50, or 100 bars.
Call Data_Matrix(Corr_Period, Sym_1, ..., Sym_20) with your selected parameters. The function will return an array containing the correlation values for every symbol pair (upper triangle of the matrix plus diagonal).
For example :
var string Sym_1 = '' , var string Sym_2 = '' , var string Sym_3 = '' , var string Sym_4 = '' , var string Sym_5 = '' , var string Sym_6 = '' , var string Sym_7 = '' , var string Sym_8 = '' , var string Sym_9 = '' , var string Sym_10 = ''
var string Sym_11 = '', var string Sym_12 = '', var string Sym_13 = '', var string Sym_14 = '', var string Sym_15 = '', var string Sym_16 = '', var string Sym_17 = '', var string Sym_18 = '', var string Sym_19 = '', var string Sym_20 = ''
switch Market
'Forex' => Sym_1 := 'EURUSD' , Sym_2 := 'GBPUSD' , Sym_3 := 'USDJPY' , Sym_4 := 'USDCHF' , Sym_5 := 'USDCAD' , Sym_6 := 'AUDUSD' , Sym_7 := 'NZDUSD' , Sym_8 := 'EURJPY' , Sym_9 := 'EURGBP' , Sym_10 := 'GBPJPY'
,Sym_11 := 'AUDJPY', Sym_12 := 'EURCHF', Sym_13 := 'EURCAD', Sym_14 := 'GBPCAD', Sym_15 := 'CADJPY', Sym_16 := 'CHFJPY', Sym_17 := 'NZDJPY', Sym_18 := 'AUDNZD', Sym_19 := 'USDSEK' , Sym_20 := 'USDNOK'
'Stock' => Sym_1 := 'NVDA' , Sym_2 := 'AAPL' , Sym_3 := 'GOOGL' , Sym_4 := 'GOOG' , Sym_5 := 'META' , Sym_6 := 'MSFT' , Sym_7 := 'AMZN' , Sym_8 := 'AVGO' , Sym_9 := 'TSLA' , Sym_10 := 'BRK.B'
,Sym_11 := 'UNH' , Sym_12 := 'V' , Sym_13 := 'JPM' , Sym_14 := 'WMT' , Sym_15 := 'LLY' , Sym_16 := 'ORCL', Sym_17 := 'HD' , Sym_18 := 'JNJ' , Sym_19 := 'MA' , Sym_20 := 'COST'
'Crypto' => Sym_1 := 'BTCUSD' , Sym_2 := 'ETHUSD' , Sym_3 := 'BNBUSD' , Sym_4 := 'XRPUSD' , Sym_5 := 'SOLUSD' , Sym_6 := 'ADAUSD' , Sym_7 := 'DOGEUSD' , Sym_8 := 'AVAXUSD' , Sym_9 := 'DOTUSD' , Sym_10 := 'TRXUSD'
,Sym_11 := 'LTCUSD' , Sym_12 := 'LINKUSD', Sym_13 := 'UNIUSD', Sym_14 := 'ATOMUSD', Sym_15 := 'ICPUSD', Sym_16 := 'ARBUSD', Sym_17 := 'APTUSD', Sym_18 := 'FILUSD', Sym_19 := 'OPUSD' , Sym_20 := 'USDT.D'
'Custom' => Sym_1 := Sym_1_C , Sym_2 := Sym_2_C , Sym_3 := Sym_3_C , Sym_4 := Sym_4_C , Sym_5 := Sym_5_C , Sym_6 := Sym_6_C , Sym_7 := Sym_7_C , Sym_8 := Sym_8_C , Sym_9 := Sym_9_C , Sym_10 := Sym_10_C
,Sym_11 := Sym_11_C, Sym_12 := Sym_12_C, Sym_13 := Sym_13_C, Sym_14 := Sym_14_C, Sym_15 := Sym_15_C, Sym_16 := Sym_16_C, Sym_17 := Sym_17_C, Sym_18 := Sym_18_C, Sym_19 := Sym_19_C , Sym_20 := Sym_20_C
= Corr.Data_Matrix(Corr_period, Sym_1 ,Sym_2 ,Sym_3 ,Sym_4 ,Sym_5 ,Sym_6 ,Sym_7 ,Sym_8 ,Sym_9 ,Sym_10,Sym_11,Sym_12,Sym_13,Sym_14,Sym_15,Sym_16,Sym_17,Sym_18,Sym_19,Sym_20)
Loop through or index into this array to retrieve each correlation value for your custom layout or logic.
Pass each correlation value to CorrelationColor() to get the corresponding gradient background color, which reflects the correlation’s strength and direction (negative to positive).
For example :
Corr.CorrelationColor(SYM_3_10)
Pass the same correlation value to CorrelationTextColor() to get the correct text color for readability against that background.
For example :
Corr.CorrelationTextColor(SYM_1_1)
Use these colors in a table or label to render your own heatmap or any other visualization you need.
Scanner ADX & VolumenThis indicator is a market scanner specifically designed for scalping traders. Its function is to simultaneously monitor 30 cryptocurrency pairs from the BingX exchange to identify entry opportunities based on the start of a new, strengthening trend.
Strategy and Logic:
The scanner is based on the combination of two key conditions on a 15-minute timeframe:
Trend Strength (ADX): The primary signal is generated when the ADX (Average Directional Index) crosses above the 20 level. An ADX moving above this threshold suggests that the market is breaking out of a consolidation phase and that a new trend (either bullish or bearish) is beginning to gain strength.
Volume Confirmation: To validate the ADX signal, the indicator checks if the current candle's volume is higher than its simple moving average (defaulting to 20 periods). An increase in volume confirms market interest and participation, adding greater reliability to the emerging move.
How to Use It:
The indicator displays a table in the top-right corner of your chart with the following information:
Par: The name of the cryptocurrency pair.
ADX: The current ADX value. It turns green when it exceeds the 20 level.
Volume: Shows "OK" if the current volume is higher than its average.
Signal: This is the most important column. When both conditions (ADX crossover and high volume) are met, it will display the message "¡ENTRADA!" ("ENTRY!") with a highlighted background, alerting you to a potential trading opportunity.
In summary, this scanner saves you the effort of manually analyzing 30 charts, allowing you to focus solely on the assets that present the best conditions for a scalping trade.
