Trend Score with Dynamic Stop Loss RTH
📘 Trend Score with Dynamic Stop Loss (RTH) — Guide
🔎 Overview
This indicator tracks intraday momentum during Regular Trading Hours and flags trend flips using a cumulative TrendScore. It also draws dynamic stop-loss levels and shows a live stats table for quick decision-making and journaling.
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⚙️ Core Concepts
1) TrendScore (per bar)
• +1 if the current bar makes a higher high than the previous bar (counted once per bar).
• –1 if the current bar makes a lower low than the previous bar (counted once per bar).
• If a bar takes both the prior high and low, the net contribution can cancel out within that bar.
2) Cumulative TrendScore (running total)
• The per-bar TrendScore accumulates across the session to form the cumulative TrendScore (TS).
• TS resets to 0 at session open and is cleared at session close.
• Rising TS = persistent upside pressure; falling TS = persistent downside pressure.
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🔄 Flip Rules (3-point reversal of the cumulative TrendScore)
A flip occurs when the cumulative TrendScore reverses by 3 points in the opposite direction of the current trend.
• Bullish Flip
• Trigger: After a decline, the cumulative TrendScore rises by +3 from its down-leg.
• Interpretation: Bulls have taken control.
• Stop-loss: the lowest price of the prior (down) leg.
• Bearish Flip
• Trigger: After a rise, the cumulative TrendScore falls by –3 from its up-leg.
• Interpretation: Bears have taken control.
• Stop-loss: the highest price of the prior (up) leg.
Flip bars are marked with ▲ (lime) for bullish and ▼ (red) for bearish.
Note: If you prefer a different reversal distance, adjust the flip distance setting in the script’s inputs (default is 3).
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📏 Stop-Loss Lines
• A dotted line is drawn at the prior leg’s extreme:
Green (below price) after a bullish flip.
Red (above price) after a bearish flip.
• Options:
Remove on touch for a clean chart.
Freeze on touch to keep a visual record for journaling.
• All stop lines are cleared at session end.
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🧮 Stats Table (what you see)
• Trend: Bull / Bear / Neutral
• Bars in Trend: Count since the flip bar
• Since Flip: Current close minus flip bar close
• Since SL: Current close minus active stop level
• MFE-Maximum Favorable Excursion: Highest favorable move since flip
• MAE-Maximum Adverse Excursion: Largest adverse move since flip
Table colors reflect the current trend (green for bull, red for bear).
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📊 Trading Playbook
Entries
• Aggressive: Enter immediately on a flip marker.
• Conservative: Wait for a small pullback that doesn’t violate the stop.
Stops
• Place the stop at the script’s flip stop-loss line (the prior leg extreme).
Exits
Choose one style and stick with it:
• Stop-only: Exit when the stop is hit.
• Time-based: Flatten at session close.
• Targets: Scale/close at 1R, 2R.
• Trailing: Trail behind minor swings once MFE > 1R.
Ultimately Exit choice is your own edge, so you must decide for yourself.
💡 Best Practices
• Skip the first few bars after the open (gap noise).
• Use regular candles (Heikin-Ashi will distort highs/lows).
• If you want fewer flips, increase the flip distance (e.g., 4 or 5). For more
responsiveness, use 2. Otherwise, increase your time frame to 5m, 10m, 15m.
• Keep SL lines frozen (not auto-removed) if you’re journaling.
Search in scripts for "TAKE"
Position Size CalculatorPosition Size Calculator
This open-source Pine Script® indicator helps traders manage risk by calculating position size, margin, and risk/reward based on account size, leverage, entry, stop-loss, and take-profit. It features a customizable table and optional chart lines/labels for clear trade planning across stocks, forex, crypto, and futures.
What It Does
- Position Size: Computes units to trade based on risk percentage and stop-loss distance, capped by leverage.
- Margin: Calculates initial margin in base currency and USD, with account size percentage.
- Risk/Reward: Shows risk-reward ratio, percentage price movements, and USD gains/losses.
- Visualization: Displays results in a table and optional chart lines/labels with customizable styles.
How It Works
- Precision: Adjusts price formatting using syminfo.mintick for accuracy across assets.
- Calculations: Position size = accountSize * (riskPercent / 100) / |entry - stoploss|, capped by accountSize * leverage / entry. Margin = positionSize / leverage. Risk-reward = |takeprofit - entry| / |stoploss - entry|.
- Display: Table shows metrics; optional lines/labels plot entry, stop-loss, and take-profit with percentage and USD details.
How to Use
- Set Inputs:
1- Account Size (USD): Your capital (e.g., 1000).
2- % Risk per Trade: Risk tolerance (e.g., 1%).
3- Leverage: Broker leverage (e.g., 1x, 10x).
4- Entry, Stop Loss, Take Profit: Trade prices.
5- Show Lines and Labels: Enable chart overlays.
- Customize: Adjust table position, colors, and line styles (Solid, Dashed, Dotted).
- View Results: Table shows position size, margin, and risk/reward. Chart lines/labels (if enabled) display prices, percentages, and USD outcomes.
- Apply: Use metrics for trade execution; modify code for custom features.
Notes
- Ensure valid inputs (entry ≠ stop-loss, both positive) to avoid “N/A”.
- Open-source: Inspect or extend the code for your needs.
- Contact the author via TradingView for feedback.
RTH Levels: VWAP + PDH/PDL + ONH/ONL + IBAlgo Index — Levels Pro (ONH/ONL • PDH/PDL • VWAP±Bands • IB • Gaps)
Purpose. A session-aware, non-repainting levels tool for intraday decision-making. Designed for futures and indices, with clean visuals, alerts, and a one-click Minimal Mode for screenshot-ready charts.
What it plots
• PDH/PDL (RTH-only) – Prior Regular Trading Hours high/low, computed intraday and frozen at the RTH close (no 24h mix-ups, no repainting).
• ONH/ONL – Prior Overnight high/low, held throughout RTH.
• RTH VWAP with ±σ bands – Volume-weighted variance, reset each RTH.
• Initial Balance (IB) – First N minutes of RTH, plus 1.5× / 2.0× extensions after IB completes.
• Today’s RTH Open & Prior RTH Close – With gap detection and “gap filled” alert.
• Killzone shading – NY Open (09:30–10:30 ET) and Lunch (11:15–13:30 ET).
• Values panel (top-right) – Each level with live distance in points & ticks.
• Right-edge level tags – With anti-overlap (stagger + vertical jitter).
• Price-scale tags – Native trackprice markers that always “stick” to the axis.
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New in v6.4
• Minimal Mode: one click for a clean look (thinner lines, VWAP bands/IB extensions hidden, on-chart right-edge labels off; price-scale tags remain).
• Theme presets: Dark Hi-Contrast / Light Minimal / Futures Classic / Muted Dark.
• Anti-overlap controls: horizontal staggering, vertical jitter, and baseline offset to keep tags readable even when levels cluster.
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Quick start (2 minutes)
1. Add to chart → keep defaults.
2. Sessions (ET):
• RTH Session default: 09:30–16:00 (US equities cash hours).
• Overnight Session default: 18:00–09:29.
Adjust for your market if you use different “day” hours (e.g., many use 08:20–13:30 ET for COMEX Gold).
3. Theme & Minimal Mode: pick a Theme Preset; enable Minimal Mode for screenshots.
4. Visibility: toggle PD/ON/VWAP/IB/References/Panel to taste.
5. Right-edge labels: turn Show Right-Edge Labels on. If they crowd, tune:
• Anti-overlap: min separation (ticks)
• Horizontal offset per tag (bars)
• Vertical jitter per step (ticks)
• Right-edge baseline offset (bars)
6. Alerts: open Add alert → Condition: and pick the events you want.
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How levels are computed (no repainting)
• PDH/PDL: Intraday H/L are accumulated only while in RTH and saved at RTH close for “yesterday’s” values.
• ONH/ONL: Accumulated across the defined Overnight window and then held during RTH.
• RTH VWAP & ±σ: Volume-weighted mean and standard deviation, reset at the RTH open.
• IB: First N minutes of RTH (default 60). Extensions (1.5×/2.0×) appear after IB completes.
• Gaps: Today’s RTH open vs prior RTH close; “Gap Filled” triggers when price trades back to prior close.
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Practical playbooks (how to trade around the levels)
1) PDH/PDL interactions
• Rejection: Price taps PDH/PDL then closes back inside → mean-reversion toward VWAP/IB.
• Acceptance: Close/hold beyond PDH/PDL with momentum → continuation to next HTF/IB target.
• Alert: PD Touch/Break.
2) ONH/ONL “taken”
• Often one ON extreme is taken during RTH. ONH Taken / ONL Taken → check if it’s a clean break or sweep & reclaim.
• Sweep + reclaim near VWAP can fuel rotations through the ON range.
3) VWAP ±σ framework
• Balanced: First tag of ±1σ often reverts toward VWAP.
• Trend: Persistent trade beyond ±1σ + IB break → target ±2σ/±3σ.
• Alerts: VWAP Cross and VWAP Reject (cross then immediate fail back).
4) IB breaks
• After IB completes, a clean IB break commonly targets 1.5× and sometimes 2.0×.
• Quick return inside IB = possible fade back to the opposite IB edge/VWAP.
• Alerts: IB Break Up / Down.
5) Gaps
• Gap-and-go: Opening drive away from prior close + VWAP support → trend until IB completion.
• Gap-fill: Weak open and VWAP overhead/underfoot → trade toward prior close; manage on Gap Filled alert.
Pro tip: Stack confluences (e.g., ONL sweep + VWAP reclaim + IB hold) and respect your execution rules (e.g., require a 5-minute close in direction, or your order-flow confirmation).
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Inputs you’ll actually touch
• Sessions (ET): Session Timezone, RTH Session, Overnight Session.
• Visibility: toggles for PD/ON/VWAP/IB/Ref/Panel.
• VWAP bands: set σ multipliers (±1/±2/±3).
• IB: duration (minutes) and extension multipliers (1.5× / 2.0×).
• Style & Theme: Theme Preset, Main Line Width, Trackprice, Minimal Mode, and anti-overlap controls.
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Alerts included
• PD Touch/Break — High ≥ PDH or Low ≤ PDL
• ONH Taken / ONL Taken — First in-RTH take of ONH/ONL
• VWAP Cross — Close crosses VWAP
• VWAP Reject — Cross then immediate fail back
• IB Break Up / Down — Break of IB High/Low after IB completes
• Gap Filled — Price trades back to prior RTH close
Setup: Add alert → Condition: Algo Index — Levels Pro → choose event → message → Notify on app/email.
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Panel guide
The top-right panel shows each level plus live distance from last price:
LevelValue (Δpoints | Δticks)
Coloring: green if level is below current price, red if above.
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Styling & screenshot tips
• Use Theme Preset that matches your chart.
• For dark charts, “Dark Hi-Contrast” with Main Line Width = 3 works well.
• Enable Trackprice for crisp axis tags that always stick to the right edge.
• Turn on Minimal Mode for cleaner screenshots (no VWAP bands or IB extensions, on-chart tags off; price-scale tags remain).
• If tags crowd, increase min separation (ticks) to 30–60 and horizontal offset to 3–5; add vertical jitter (4–12 ticks) and/or push tags farther right with baseline offset (bars).
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Behavior & limitations
• Levels are computed incrementally; tables refresh on the last bar for efficiency.
• Right-edge labels are placed at bar_index + offset and do not track extra right-margin scrolling (TradingView limitation). The price-scale tags (from trackprice) do track the axis.
• “RTH” is what you define in inputs. If your market uses different day hours, change the session strings so PDH/PDL reflect your definition of “yesterday’s session.”
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FAQ
Q: My PDH/PDL don’t match the daily chart.
A: By design this uses RTH-only highs/lows, not 24h daily bars. Adjust sessions if you want a different definition.
Q: Right-edge tags overlap or don’t sit at the far right.
A: Increase min separation / horizontal offset / vertical jitter and/or push tags farther with baseline offset. If you want markers that always hug the axis, rely on Trackprice.
Q: Can I change killzones?
A: Yes—edit the session strings in settings or request a version with user inputs for custom windows.
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Disclaimer
Educational use only. This is not financial advice. Always apply your own risk management and confirmation rules.
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Enjoy it? Please ⭐ the script and share screenshots using Minimal Mode + a Theme Preset that fits your style.
SMC_CommonLibrary "SMC_Common"
Common types and utilities for Smart Money Concepts indicators
get_future_time(bars_ahead)
Parameters:
bars_ahead (int)
get_time_at_offset(offset)
Parameters:
offset (int)
get_mid_time(time1, time2)
Parameters:
time1 (int)
time2 (int)
timeframe_to_string(tf)
Parameters:
tf (string)
is_psychological_level(price)
Parameters:
price (float)
detect_swing_high(src_high, lookback)
Parameters:
src_high (float)
lookback (int)
detect_swing_low(src_low, lookback)
Parameters:
src_low (float)
lookback (int)
detect_fvg(h, l, min_size)
Parameters:
h (float)
l (float)
min_size (float)
analyze_volume(vol, volume_ma)
Parameters:
vol (float)
volume_ma (float)
create_label(x, y, label_text, bg_color, label_size, use_time)
Parameters:
x (int)
y (float)
label_text (string)
bg_color (color)
label_size (string)
use_time (bool)
SwingPoint
Fields:
price (series float)
bar_index (series int)
bar_time (series int)
swing_type (series string)
strength (series int)
is_major (series bool)
timeframe (series string)
LiquidityLevel
Fields:
price (series float)
bar_index (series int)
bar_time (series int)
liq_type (series string)
touch_count (series int)
is_swept (series bool)
quality_score (series float)
level_type (series string)
OrderBlock
Fields:
start_bar (series int)
end_bar (series int)
start_time (series int)
end_time (series int)
top (series float)
bottom (series float)
ob_type (series string)
has_liquidity_sweep (series bool)
has_fvg (series bool)
is_mitigated (series bool)
is_breaker (series bool)
timeframe (series string)
mitigation_level (series float)
StructureBreak
Fields:
level (series float)
break_bar (series int)
break_time (series int)
break_type (series string)
direction (series string)
is_confirmed (series bool)
source_swing_bar (series int)
source_time (series int)
SignalData
Fields:
signal_type (series string)
entry_price (series float)
stop_loss (series float)
take_profit (series float)
risk_reward_ratio (series float)
confluence_count (series int)
confidence_score (series float)
strength (series string)
Current Hourly Open Liquidity with Sweep DetectionStatistics indicate that if the current hourly candle reaches the high or low of the previous hourly candle, there is a strong likelihood that the price will return to the current hour's open, depending on how quickly the previous hour's high or low was swept. If the sweep occurs within the first 20 minutes, there is a 75% chance the current hour's open will be reached; if it takes between 21 and 40 minutes, the probability decreases to 50%; and if it takes longer than 41 minutes, the chance drops to 25%.
These statistics can help identify manipulation on the hourly timeframe and guide trade decisions accordingly. For instance, if the previous hourly high is taken within the first 20 minutes but the current hour's open is not reached, it may be wise to avoid long positions until it happens or consider short positions in the direction of the open liquidity, using your existing entry rules and risk management.
The indicator highlights the current hour's open with a line and label to visually represent that liquidity pool, adjusting the line's color based on whether and when the previous hour's high or low was tapped. Once the open is reached, the indicator can, depending on settings, remove the line and label from the chart (this is enabled by default) since the liquidity pool is no longer relevant, preventing chart clutter.
All colors, line widths, label text sizes, and colors can be customized.
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
Reverse Keltner Channel StrategyReverse Keltner Channel Strategy
Overview
The Reverse Keltner Channel Strategy is a mean-reversion trading system that capitalizes on price movements between Keltner Channels. Unlike traditional Keltner Channel strategies that trade breakouts, this system takes the contrarian approach by entering positions when price returns to the channel after overextending.
Strategy Logic
Long Entry Conditions:
Price crosses above the lower Keltner Channel from below
This signals a potential reversal after an oversold condition
Position is entered at market price upon signal confirmation
Long Exit Conditions:
Take Profit: Price reaches the upper Keltner Channel
Stop Loss: Placed at half the channel width below entry price
Short Entry Conditions:
Price crosses below the upper Keltner Channel from above
This signals a potential reversal after an overbought condition
Position is entered at market price upon signal confirmation
Short Exit Conditions:
Take Profit: Price reaches the lower Keltner Channel
Stop Loss: Placed at half the channel width above entry price
Key Features
Mean Reversion Approach: Takes advantage of price tendency to return to mean after extreme moves
Adaptive Stop Loss: Stop loss dynamically adjusts based on market volatility via ATR
Visual Signals: Entry points clearly marked with directional triangles
Fully Customizable: All parameters can be adjusted to fit various market conditions
Customizable Parameters
Keltner EMA Length: Controls the responsiveness of the channel (default: 20)
ATR Multiplier: Determines channel width/sensitivity (default: 2.0)
ATR Length: Affects volatility calculation period (default: 10)
Stop Loss Factor: Adjusts risk management aggressiveness (default: 0.5)
Best Used On
This strategy performs well on:
Currency pairs with defined ranging behavior
Commodities that show cyclical price movements
Higher timeframes (4H, Daily) for more reliable signals
Markets with moderate volatility
Risk Management
The built-in stop loss mechanism automatically adjusts to market conditions by calculating position risk relative to the current channel width. This approach ensures that risk remains proportional to potential reward across varying market conditions.
Notes for Optimization
Consider adjusting the EMA length and ATR multiplier based on the specific asset and timeframe:
Lower values increase sensitivity and generate more signals
Higher values produce fewer but potentially more reliable signals
As with any trading strategy, thorough backtesting is recommended before live implementation.
Past performance is not indicative of future results. Always practice sound risk management.
ADR% Extension Levels from SMA 50I created this indicator inspired by RealSimpleAriel (a swing trader I recommend following on X) who does not buy stocks extended beyond 4 ADR% from the 50 SMA and uses extensions from the 50 SMA at 7-8-9-10-11-12-13 ADR% to take profits with a 20% position trimming.
RealSimpleAriel's strategy (as I understood it):
-> Focuses on leading stocks from leading groups and industries, i.e., those that have grown the most in the last 1-3-6 months (see on Finviz groups and then select sector-industry).
-> Targets stocks with the best technical setup for a breakout, above the 200 SMA in a bear market and above both the 50 SMA and 200 SMA in a bull market, selecting those with growing Earnings and Sales.
-> Buys stocks on breakout with a stop loss set at the day's low of the breakout and ensures they are not extended beyond 4 ADR% from the 50 SMA.
-> 3-5 day momentum burst: After a breakout, takes profits by selling 1/2 or 1/3 of the position after a 3-5 day upward move.
-> 20% trimming on extension from the 50 SMA: At 7 ADR% (ADR% calculated over 20 days) extension from the 50 SMA, takes profits by selling 20% of the remaining position. Continues to trim 20% of the remaining position based on the stock price extension from the 50 SMA, calculated using the 20-period ADR%, thus trimming 20% at 8-9-10-11 ADR% extension from the 50 SMA. Upon reaching 12-13 ADR% extension from the 50 SMA, considers the stock overextended, closes the remaining position, and evaluates a short.
-> Trailing stop with ascending SMA: Uses a chosen SMA (10, 20, or 50) as the definitive stop loss for the position, depending on the stock's movement speed (preferring larger SMAs for slower-moving stocks or for long-term theses). If the stock's closing price falls below the chosen SMA, the entire position is closed.
In summary:
-->Buy a breakout using the day's low of the breakout as the stop loss (this stop loss is the most critical).
--> Do not buy stocks extended beyond 4 ADR% from the 50 SMA.
--> Sell 1/2 or 1/3 of the position after 3-5 days of upward movement.
--> Trim 20% of the position at each 7-8-9-10-11-12-13 ADR% extension from the 50 SMA.
--> Close the entire position if the breakout fails and the day's low of the breakout is reached.
--> Close the entire position if the price, during the rise, falls below a chosen SMA (10, 20, or 50, depending on your preference).
--> Definitively close the position if it reaches 12-13 ADR% extension from the 50 SMA.
I used Grok from X to create this indicator. I am not a programmer, but based on the ADR% I use, it works.
Below is Grok from X's description of the indicator:
Script Description
The script is a custom indicator for TradingView that displays extension levels based on ADR% relative to the 50-period Simple Moving Average (SMA). Below is a detailed description of its features, structure, and behavior:
1. Purpose of the Indicator
Name: "ADR% Extension Levels from SMA 50".
Objective: Draw horizontal blue lines above and below the 50-period SMA, corresponding to specific ADR% multiples (4, 7, 8, 9, 10, 11, 12, 13). These levels represent potential price extension zones based on the average daily percentage volatility.
Overlay: The indicator is overlaid on the price chart (overlay=true), so the lines and SMA appear directly on the price graph.
2. Configurable Inputs
The indicator allows users to customize parameters through TradingView settings:
SMA Length (smaLength):
Default: 50 periods.
Description: Specifies the number of periods for calculating the Simple Moving Average (SMA). The 50-period SMA serves as the reference point for extension levels.
Constraint: Minimum 1 period.
ADR% Length (adrLength):
Default: 20 periods.
Description: Specifies the number of days to calculate the moving average of the daily high/low ratio, used to determine ADR%.
Constraint: Minimum 1 period.
Scale Factor (scaleFactor):
Default: 1.0.
Description: An optional multiplier to adjust the distance of extension levels from the SMA. Useful if levels are too close or too far due to an overly small or large ADR%.
Constraint: Minimum 0.1, increments of 0.1.
Tooltip: "Adjust if levels are too close or far from SMA".
3. Main Calculations
50-period SMA:
Calculated with ta.sma(close, smaLength) using the closing price (close).
Serves as the central line around which extension levels are drawn.
ADR% (Average Daily Range Percentage):
Formula: 100 * (ta.sma(dhigh / dlow, adrLength) - 1).
Details:
dhigh and dlow are the daily high and low prices, obtained via request.security(syminfo.tickerid, "D", high/low) to ensure data is daily-based, regardless of the chart's timeframe.
The dhigh / dlow ratio represents the daily percentage change.
The simple moving average (ta.sma) of this ratio over 20 days (adrLength) is subtracted by 1 and multiplied by 100 to obtain ADR% as a percentage.
The result is multiplied by scaleFactor for manual adjustments.
Extension Levels:
Defined as ADR% multiples: 4, 7, 8, 9, 10, 11, 12, 13.
Stored in an array (levels) for easy iteration.
For each level, prices above and below the SMA are calculated as:
Above: sma50 * (1 + (level * adrPercent / 100))
Below: sma50 * (1 - (level * adrPercent / 100))
These represent price levels corresponding to a percentage change from the SMA equal to level * ADR%.
4. Visualization
Horizontal Blue Lines:
For each level (4, 7, 8, 9, 10, 11, 12, 13 ADR%), two lines are drawn:
One above the SMA (e.g., +4 ADR%).
One below the SMA (e.g., -4 ADR%).
Color: Blue (color.blue).
Style: Solid (style=line.style_solid).
Management:
Each level has dedicated variables for upper and lower lines (e.g., upperLine1, lowerLine1 for 4 ADR%).
Previous lines are deleted with line.delete before drawing new ones to avoid overlaps.
Lines are updated at each bar with line.new(bar_index , level, bar_index, level), covering the range from the previous bar to the current one.
Labels:
Displayed only on the last bar (barstate.islast) to avoid clutter.
For each level, two labels:
Above: E.g., "4 ADR%", positioned above the upper line (style=label.style_label_down).
Below: E.g., "-4 ADR%", positioned below the lower line (style=label.style_label_up).
Color: Blue background, white text.
50-period SMA:
Drawn as a gray line (color.gray) for visual reference.
Diagnostics:
ADR% Plot: ADR% is plotted in the status line (orange, histogram style) to verify the value.
ADR% Label: A label on the last bar near the SMA shows the exact ADR% value (e.g., "ADR%: 2.34%"), with a gray background and white text.
5. Behavior
Dynamic Updating:
Lines update with each new bar to reflect new SMA 50 and ADR% values.
Since ADR% uses daily data ("D"), it remains constant within the same day but changes day-to-day.
Visibility Across All Bars:
Lines are drawn on every bar, not just the last one, ensuring visibility on historical data as well.
Adaptability:
The scaleFactor allows level adjustments if ADR% is too small (e.g., for low-volatility symbols) or too large (e.g., for cryptocurrencies).
Compatibility:
Works on any timeframe since ADR% is calculated from daily data.
Suitable for symbols with varying volatility (e.g., stocks, forex, cryptocurrencies).
6. Intended Use
Technical Analysis: Extension levels represent significant price zones based on average daily volatility. They can be used to:
Identify potential price targets (e.g., take profit at +7 ADR%).
Assess support/resistance zones (e.g., -4 ADR% as support).
Measure price extension relative to the 50 SMA.
Trading: Useful for strategies based on breakouts or mean reversion, where ADR% levels indicate reversal or continuation points.
Debugging: Labels and ADR% plot help verify that values align with the symbol’s volatility.
7. Limitations
Dependence on Daily Data: ADR% is based on daily dhigh/dlow, so it may not reflect intraday volatility on short timeframes (e.g., 1 minute).
Extreme ADR% Values: For low-volatility symbols (e.g., bonds) or high-volatility symbols (e.g., meme stocks), ADR% may require adjustments via scaleFactor.
Graphical Load: Drawing 16 lines (8 upper, 8 lower) on every bar may slow the chart for very long historical periods, though line management is optimized.
ADR% Formula: The formula 100 * (sma(dhigh/dlow, Length) - 1) may produce different values compared to other ADR% definitions (e.g., (high - low) / close * 100), so users should be aware of the context.
8. Visual Example
On a chart of a stock like TSLA (daily timeframe):
The 50 SMA is a gray line tracking the average trend.
Assuming an ADR% of 3%:
At +4 ADR% (12%), a blue line appears at sma50 * 1.12.
At -4 ADR% (-12%), a blue line appears at sma50 * 0.88.
Other lines appear at ±7, ±8, ±9, ±10, ±11, ±12, ±13 ADR%.
On the last bar, labels show "4 ADR%", "-4 ADR%", etc., and a gray label shows "ADR%: 3.00%".
ADR% is visible in the status line as an orange histogram.
9. Code: Technical Structure
Language: Pine Script @version=5.
Inputs: Three configurable parameters (smaLength, adrLength, scaleFactor).
Calculations:
SMA: ta.sma(close, smaLength).
ADR%: 100 * (ta.sma(dhigh / dlow, adrLength) - 1) * scaleFactor.
Levels: sma50 * (1 ± (level * adrPercent / 100)).
Graphics:
Lines: Created with line.new, deleted with line.delete to avoid overlaps.
Labels: Created with label.new only on the last bar.
Plots: plot(sma50) for the SMA, plot(adrPercent) for debugging.
Optimization: Uses dedicated variables for each line (e.g., upperLine1, lowerLine1) for clear management and to respect TradingView’s graphical object limits.
10. Possible Improvements
Option to show lines only on the last bar: Would reduce visual clutter.
Customizable line styles: Allow users to choose color or style (e.g., dashed).
Alert for anomalous ADR%: A message if ADR% is too small or large.
Dynamic levels: Allow users to specify ADR% multiples via input.
Optimization for short timeframes: Adapt ADR% for intraday timeframes.
Conclusion
The script creates a visual indicator that helps traders identify price extension levels based on daily volatility (ADR%) relative to the 50 SMA. It is robust, configurable, and includes debugging tools (ADR% plot and labels) to verify values. The ADR% formula based on dhigh/dlow
Liquidity Zones Alerts"Liquidity Zones Alerts" is a powerful smart-money-based indicator designed to detect key liquidity grabs and provide high-probability reversal signals using a combination of market structure, volume, volatility, and candlestick confirmation.
🧠 How It Works
The core logic of this indicator is built around the Smart Money Concepts:
🔺 Liquidity Sweeps: Detects when price takes out previous daily or weekly highs/lows, suggesting stop hunts or engineered liquidity moves by institutional players.
📈 Volume Filter: Ensures signals only appear during above-average volume, filtering out noise and low-interest moves.
⚡ Volatility Filter: Flags high-range candles relative to the average, catching flash crashes/spikes that often precede strong reversals.
🔄 Engulfing Candle Confirmation: Confirms entry with a bullish or bearish engulfing pattern after liquidity is taken — increasing signal reliability.
🧭 Premium/Discount Zone Logic: Trades are filtered to ensure longs are only taken in discount zones, and shorts in premium zones, using a 20-period market range for context.
📌 Features
✅ Daily & Weekly liquidity zones toggle
✅ Visual signals with clean 🔻(short) & 🔺(long) arrows
✅ Auto-detection of flash crashes
✅ Alerts on both long and short setups
✅ Optional previous high/low level plotting for context
✅ Background highlighting of valid signal candles
✅ Multi-timeframe friendly and compatible with any asset
🛠️ Use Case
Whether you're a scalper or a swing trader, this tool helps you spot institutional entry zones before the move happens. It works especially well when combined with your existing bias or supply/demand zones.
💬 “Price doesn't move randomly — it hunts liquidity. This indicator shows you where and when it happens.”
ETH/USDT EMA Crossover Strategy - OptimizedStrategy Name: EMA Crossover Strategy for ETH/USDT
Description:
This trading strategy is designed for the ETH/USDT pair and is based on exponential moving average (EMA) crossovers combined with momentum and volatility indicators. The strategy uses multiple filters to identify high-probability signals in both bullish and bearish trends, making it suitable for traders looking to trade in trending markets.
Strategy Components
EMAs (Exponential Moving Averages):
EMA 200: Used to identify the primary trend. If the price is above the EMA 200, it is considered a bullish trend; if below, a bearish trend.
EMA 50: Acts as an additional filter to confirm the trend.
EMA 20 and EMA 50 Short: These short-term EMAs generate entry signals through crossovers. A bullish crossover (EMA 20 crosses above EMA 50 Short) is a buy signal, while a bearish crossover (EMA 20 crosses below EMA 50 Short) is a sell signal.
RSI (Relative Strength Index):
The RSI is used to avoid overbought or oversold conditions. Long trades are only taken when the RSI is above 30, and short trades when the RSI is below 70.
ATR (Average True Range):
The ATR is used as a volatility filter. Trades are only taken when there is sufficient volatility, helping to avoid false signals in quiet markets.
Volume:
A volume filter is used to confirm sufficient market participation in the price movement. Trades are only taken when volume is above average.
Strategy Logic
Long Trades:
The price must be above the EMA 200 (bullish trend).
The EMA 20 must cross above the EMA 50 Short.
The RSI must be above 30.
The ATR must indicate sufficient volatility.
Volume must be above average.
Short Trades:
The price must be below the EMA 200 (bearish trend).
The EMA 20 must cross below the EMA 50 Short.
The RSI must be below 70.
The ATR must indicate sufficient volatility.
Volume must be above average.
How to Use the Strategy
Setup:
Add the script to your ETH/USDT chart on TradingView.
Adjust the parameters according to your preferences (e.g., EMA periods, RSI, ATR, etc.).
Signals:
Buy and sell signals will be displayed directly on the chart.
Long trades are indicated with an upward arrow, and short trades with a downward arrow.
Risk Management:
Use stop-loss and take-profit orders in all trades.
Consider a risk-reward ratio of at least 1:2.
Backtesting:
Test the strategy on historical data to evaluate its performance before using it live.
Advantages of the Strategy
Trend-focused: The strategy is designed to trade in trending markets, increasing the probability of success.
Multiple filters: The use of RSI, ATR, and volume reduces false signals.
Adaptability: It can be adjusted for different timeframes, although it is recommended to test it on 5-minute and 15-minute charts for ETH/USDT.
Warnings
Sideways markets: The strategy may generate false signals in markets without a clear trend. It is recommended to avoid trading in such conditions.
Optimization: Make sure to optimize the parameters according to the market and timeframe you are using.
Risk management: Never trade without stop-loss and take-profit orders.
Author
Jose J. Sanchez Cuevas
Version
v1.0
ICT Bread and Butter Sell-SetupICT Bread and Butter Sell-Setup – TradingView Strategy
Overview:
The ICT Bread and Butter Sell-Setup is an intraday trading strategy designed to capitalize on bearish market conditions. It follows institutional order flow and exploits liquidity patterns within key trading sessions—London, New York, and Asia—to identify high-probability short entries.
Key Components of the Strategy:
🔹 London Open Setup (2:00 AM – 8:20 AM NY Time)
The London session typically sets the initial directional move of the day.
A short-term high often forms before a downward push, establishing the daily high.
🔹 New York Open Kill Zone (8:20 AM – 10:00 AM NY Time)
The New York Judas Swing (a temporary rally above London’s high) creates an opportunity for short entries.
Traders fade this move, anticipating a sell-off targeting liquidity below previous lows.
🔹 London Close Buy Setup (10:30 AM – 1:00 PM NY Time)
If price reaches a higher timeframe discount array, a retracement higher is expected.
A bullish order block or failure swing signals a possible reversal.
The risk is set just below the day’s low, targeting a 20-30% retracement of the daily range.
🔹 Asia Open Sell Setup (7:00 PM – 2:00 AM NY Time)
If institutional order flow remains bearish, a short entry is taken around the 0-GMT Open.
Expect a 15-20 pip decline as the Asian range forms.
Strategy Rules:
📉 Short Entry Conditions:
✅ New York Judas Swing occurs (price moves above London’s high before reversing).
✅ Short entry is triggered when price closes below the open.
✅ Stop-loss is set 10 pips above the session high.
✅ Take-profit targets liquidity zones on higher timeframes.
📈 Long Entry (London Close Reversal):
✅ Price reaches a higher timeframe discount array between 10:30 AM – 1:00 PM NY Time.
✅ A bullish order block confirms the reversal.
✅ Stop-loss is set 10 pips below the day’s low.
✅ Take-profit targets 20-30% of the daily range retracement.
📉 Asia Open Sell Entry:
✅ Price trades slightly above the 0-GMT Open.
✅ Short entry is taken at resistance, targeting a quick 15-20 pip move.
Why Use This Strategy?
🚀 Institutional Order Flow Tracking – Aligns with smart money concepts.
📊 Precise Session Timing – Uses market structure across London, New York, and Asia.
🎯 High-Probability Entries – Focuses on liquidity grabs and engineered stop hunts.
📉 Optimized Risk Management – Defined stop-loss and take-profit levels.
This strategy is ideal for traders looking to trade with institutions, fade liquidity grabs, and capture high-probability short setups during the trading day. 📉🔥
[TehThomas] - ICT Liquidity sweepsThe ICT Liquidity Sweeps Indicator is designed to track liquidity zones in the market areas where stop-losses and pending orders are typically clustered. This indicator marks buyside liquidity (resistance) and sellside liquidity (support), helping traders identify areas where price is likely to manipulate liquidity before making a significant move.
This tool is based on Inner Circle Trader (ICT) Smart Money Concepts, which emphasize how institutional traders, or “Smart Money,” manipulate liquidity to fuel price movements. By identifying these zones, traders can anticipate liquidity sweeps and position themselves accordingly.
⚙️ How It Works
1️⃣ Detects Key Liquidity Zones
The script automatically identifies significant swing highs and swing lows in price action using a pivot-based method.
A swing high (buyside liquidity) is a peak where price struggles to break higher, forming a resistance level.
A swing low (sellside liquidity) is a valley where price struggles to go lower, creating a support level.
These liquidity points are prime targets for liquidity sweeps before a true trend direction is confirmed.
2️⃣ Draws Liquidity Lines
Once a swing high or low is identified, a horizontal line is drawn at that level.
The lines extend to the right, serving as future liquidity targets until they are broken.
The indicator allows customization in terms of color, line width, and maximum number of liquidity lines displayed at once.
3️⃣ Handles Liquidity Sweeps
When price breaks a liquidity level, the indicator reacts based on the chosen action setting:
Dotted/Dashed: The line remains visible but changes style to indicate a sweep.
Delete: The line is completely removed once price has interacted with it.
This feature ensures that traders can easily spot where liquidity has been taken and determine whether a reversal or continuation is likely.
4️⃣ Prevents Chart Clutter
To maintain a clean chart, the script limits the number of liquidity lines displayed at any given time.
When new liquidity zones are formed, the oldest lines are automatically removed, keeping the focus on the most relevant liquidity zones.
🎯 How to Use the ICT Liquidity Sweeps Indicator
🔍 Identifying Liquidity Grabs
This indicator helps you identify areas where Smart Money is targeting liquidity before making a move.
Buyside Liquidity (BSL) Sweeps:
Occur when price spikes above a resistance level before reversing downward.
Indicate that Smart Money has hunted stop-losses and buy stops before driving price lower.
Sellside Liquidity (SSL) Sweeps:
Occur when price drops below a support level before reversing upward.
Indicate that Smart Money has collected liquidity from stop-losses and sell stops before pushing price higher.
📈 Combining with Market Structure Shifts (MSS)
One of the best ways to use this indicator is in conjunction with our Market Structure Shifts Indicator.
Liquidity sweeps + MSS Confirmation give strong high-probability trade setups:
Wait for a liquidity sweep (price takes out a liquidity level).
Look for an MSS in the opposite direction (e.g., price sweeps a high, then breaks a recent low).
Enter the trade in the new direction with stop-loss above/below the liquidity sweep.
📊 Entry & Exit Strategies
Long Trade Example:
Price sweeps a key sellside liquidity level (SSL) → creates a false breakdown.
MSS confirms a reversal (price breaks structure upwards).
Enter long position after confirmation.
Stop-loss below the liquidity grab to minimize risk.
Short Trade Example:
Price sweeps a key buyside liquidity level (BSL) → takes liquidity above resistance.
MSS confirms a bearish move (price breaks a key support level).
Enter short position after confirmation.
Stop-loss above the liquidity grab.
🚀 Why This Indicator is a Game-Changer
✅ Helps Identify Smart Money Manipulation – Understand where institutions are likely to grab liquidity before the real move happens.
✅ Enhances Market Structure Analysis – When paired with MSS, liquidity sweeps become powerful signals for trend reversals.
✅ Filters Out False Breakouts – Many traders get caught in liquidity grabs. This indicator helps avoid bad entries.
✅ Keeps Your Chart Clean – The auto-limiting feature ensures that only the most relevant liquidity levels remain visible.
✅ Works on Any Timeframe – Whether you’re a scalper, day trader, or swing trader, liquidity concepts apply universally.
📌 Final Thoughts
The ICT Liquidity Sweeps Indicator is a must-have tool for traders who follow Smart Money Concepts. By tracking liquidity levels and highlighting sweeps, it allows traders to enter trades with precision while avoiding false breakouts.
When combined with Market Structure Shifts (MSS), this strategy becomes even more powerful, offering traders an edge in spotting reversals and timing entries effectively.
__________________________________________
Thanks for your support!
If you found this idea helpful or learned something new, drop a like 👍 and leave a comment—I’d love to hear your thoughts! 🚀
Make sure to follow me for more price action insights, free indicators, and trading strategies. Let’s grow and trade smarter together! 📈✨
Hanzo_Wave_Price %Hanzo_Wave_Price % is a custom indicator for the TradingView platform that combines RSI (Relative Strength Index) and Stochastic RSI while also displaying the percentage price change over a specified period. This indicator helps traders identify overbought and oversold conditions, analyze price waves, and forecast potential market movements.
How It Works
1. RSI and Stochastic RSI Calculation
RSI is calculated based on the selected price source (default: close) with a user-defined Main Line period.
Stochastic RSI is then applied and smoothed using a moving average.
The Main Line represents the smoothed Stochastic RSI, serving as a wave indicator to help identify potential entry and exit points.
2. Overbought and Oversold Zones
The 70 and 30 levels indicate overbought and oversold zones, displayed as dashed lines on the chart.
Additional 20% and 10% levels provide a visual reference for historical price changes, aiding in future predictions.
3. Percentage Price Change Calculation
The indicator calculates the percentage price change over a Barsback period (default: 30 candles).
Users can choose a multiplier (100 or 1000) for better visualization (1000 scales the values by dividing by 10).
The data is displayed as a colored area:
Red (Short) → Negative price change.
Green (Buy) → Positive price change.
Settings & Parameters
Multiplier 💪 – Selects the scaling factor (100 or 1000) for percentage values.
Main Line ✈️ – Stochastic smoothing period (smoothK).
Don't touch ✋ – Reserved value (do not modify).
RSI 🔴 – RSI calculation period.
Stochastic 🔵 – Stochastic RSI calculation period.
Source ⚠️ – Price source for calculations (default: close).
Price changes % 🔼🔽 – Enables percentage price change display.
Barsback ↩️ – Number of candles used to calculate price change.
Visual Representation
Gray Line (Takeprofit Line 🎯) – Smoothed Stochastic RSI.
Red Dashed Line (70) – Overbought zone.
Blue Dashed Line (30) – Oversold zone.
Percentage Price Change Display:
Green Fill → Price increase.
Red Fill → Price decrease.
Advantages
✅ Combined Analysis – Uses RSI and Stochastic RSI for more accurate market condition identification.
✅ Flexibility – Customizable parameters allow adaptation for different markets and strategies.
✅ Visual Clarity – Clearly defined zones and dynamic percentage change display.
✅ Additional Market Insights – The percentage price change helps assess market volatility.
Disadvantages
⚠ Lagging Signals – Smoothing may cause delayed response.
⚠ False Breakouts – The 70/30 levels may not always work effectively for all assets.
⚠ IMPORTANT!
This indicator is for informational and educational purposes only. Past performance does not guarantee future profits! Use it in combination with other technical analysis tools. 🚀
Example 1: Identifying a Long Position
📌 Scenario:
The asset price has dropped significantly (1-hour timeframe), and the Main Line (gray line) crosses below the 30 level. This signals oversold conditions, which may indicate a potential reversal or upward correction.
✅ How to Use:
1️⃣ Identifying the Entry Zone:
If the Main Line is below 30, consider looking for a long entry point.
2️⃣ Confirming the Signal:
Place a vertical line at the moment when the Main Line crosses the 30 level from below.
3️⃣ Confirmation on a Lower Timeframe:
Switch to a 30-minute timeframe and wait for the Main Line to cross above the 70 level.
Enter a long position at this point.
4️⃣ Analyzing Percentage Price Change:
Check the historical indicator behavior:
If a similar past movement resulted in a ~10% price increase (green fill), this may indicate potential upward momentum.
5️⃣ Setting Take-Profit:
Set a take-profit level at 10%, based on previous price movements.
Also, monitor when the Main Line crosses the 70 level, as this may signal a potential profit-taking point.
📊 Conclusion:
This method helps to precisely determine entry points by confirming signals across multiple timeframes and analyzing the historical volatility of the asset. 🚀
Example 2: Analyzing Percentage Price Change
📌 Scenario:
You have set the Barsback parameter to 30, and the indicator shows +3.5%. This means that over the last 30 candles, the price has increased by 3.5%.
However, such small changes might be visually difficult to notice. To improve visibility, you can enable the multiplier (1000), which will scale the displayed percentage change to 35%. This is purely for visual convenience—the actual price movement remains 3.5%.
✅ How to Use:
1️⃣ Identifying Trend Direction:
If the percentage change is positive (green area) → Uptrend.
If the percentage change is negative (red area) → Downtrend.
2️⃣ Analyzing Movement Strength:
Compare the current percentage change with previous waves to evaluate the strength of the movement.
For example:
If previous waves reached 10% or more, a current wave of 3.5% might indicate a weak trend or a local correction.
3️⃣ Additional Filtering with the Main Line (Gray Line):
Use the Main Line to confirm the trend.
If the percentage change shows an increase, but the Main Line is still below 30, further upward movement can be expected.
If the percentage change indicates a decline, but the Main Line is above 70, there is a higher probability of a downward reversal.
"It's unfortunate that TradingView restricts adding images to indicator descriptions unless you have a paid subscription. This makes it harder to share free tools effectively."
Enhanced Bollinger Bands Strategy with SL/TP// Title: Enhanced Bollinger Bands Strategy with SL/TP
// Description:
// This strategy is based on the classic Bollinger Bands indicator and incorporates Stop Loss (SL) and Take Profit (TP) levels for automated trading. It identifies potential long and short entry points based on price crossing the lower and upper Bollinger Bands, respectively. The strategy allows users to customize several parameters to suit different market conditions and risk tolerances.
// Key Features:
// * **Bollinger Bands:** Uses Simple Moving Average (SMA) as the basis and calculates upper and lower bands based on a user-defined standard deviation multiplier.
// * **Customizable Parameters:** Offers extensive customization, including SMA length, standard deviation multiplier, Stop Loss (SL) in pips, and Take Profit (TP) in pips.
// * **Long/Short Position Control:** Allows users to independently enable or disable long and short positions.
// * **Stop Loss and Take Profit:** Implements Stop Loss and Take Profit levels based on pip values to manage risk and secure profits. Entry prices are set to the band levels on signals.
// * **Visualizations:** Provides options to display Bollinger Bands and entry signals on the chart for easy analysis.
// Strategy Logic:
// 1. **Bollinger Bands Calculation:** The strategy calculates the Bollinger Bands using the specified SMA length and standard deviation multiplier.
// 2. **Entry Conditions:**
// * **Long Entry:** Enters a long position when the closing price crosses above the lower Bollinger Band and the `Enable Long Positions` setting is enabled.
// * **Short Entry:** Enters a short position when the closing price crosses below the upper Bollinger Band and the `Enable Short Positions` setting is enabled.
// 3. **Exit Conditions:**
// * **Stop Loss:** Exits the position if the price reaches the Stop Loss level, calculated based on the input `Stop Loss (Pips)`.
// * **Take Profit:** Exits the position if the price reaches the Take Profit level, calculated based on the input `Take Profit (Pips)`.
// Input Parameters:
// * **SMA Length (length):** The length of the Simple Moving Average used to calculate the Bollinger Bands (default: 20).
// * **Standard Deviation Multiplier (mult):** The multiplier applied to the standard deviation to determine the width of the Bollinger Bands (default: 2.0).
// * **Enable Long Positions (enableLong):** A boolean value to enable or disable long positions (default: true).
// * **Enable Short Positions (enableShort):** A boolean value to enable or disable short positions (default: true).
// * **Pip Value (pipValue):** The value of a pip for the traded instrument. This is crucial for accurate Stop Loss and Take Profit calculations (default: 0.0001 for most currency pairs). **Important: Adjust this value to match the specific instrument you are trading.**
// * **Stop Loss (Pips) (slPips):** The Stop Loss level in pips (default: 10).
// * **Take Profit (Pips) (tpPips):** The Take Profit level in pips (default: 20).
// * **Show Bollinger Bands (showBands):** A boolean value to show or hide the Bollinger Bands on the chart (default: true).
// * **Show Entry Signals (showSignals):** A boolean value to show or hide entry signals on the chart (default: true).
// How to Use:
// 1. Add the strategy to your TradingView chart.
// 2. Adjust the input parameters to optimize the strategy for your chosen instrument and timeframe. Pay close attention to the `Pip Value`.
// 3. Backtest the strategy over different periods to evaluate its performance.
// 4. Use the `Enable Long Positions` and `Enable Short Positions` settings to customize the strategy for specific market conditions (e.g., only long positions in an uptrend).
// Important Notes and Disclaimers:
// * **Backtesting Results:** Past performance is not indicative of future results. Backtesting results can be affected by various factors, including market volatility, slippage, and transaction costs.
// * **Risk Management:** This strategy is provided for informational and educational purposes only and should not be considered financial advice. Always use proper risk management techniques when trading. Adjust Stop Loss and Take Profit levels according to your risk tolerance.
// * **Slippage:** The strategy takes into account slippage by specifying a slippage parameter on the `strategy` declaration. However, real-world slippage may vary.
// * **Market Conditions:** The performance of this strategy can vary significantly depending on market conditions. It may perform well in trending markets but poorly in ranging or choppy markets.
// * **Pip Value Accuracy:** **Ensure the `Pip Value` is correctly set for the specific instrument you are trading. Incorrect pip value will result in incorrect stop loss and take profit placement.** This is critical.
// * **Broker Compatibility:** The strategy's performance may vary depending on your broker's execution policies and fees.
// * **Disclaimer:** I am not a financial advisor, and this script is not financial advice. Use this strategy at your own risk. I am not responsible for any losses incurred while using this strategy.
Trend Strength/DirectionThis is a really good, though complex indicator, so I will add two different explanations so to appease both the laymen and those who take the time to read thoroughly.
Simple Explanation
This indicator utilizes 6HMA's to display their angles
The greater the angle ---> the stronger the trend
If more angles are positive, then trend is very strong
If more are negative, then very negative
Comprehensive Explanation
6 angles, each of a different time frame are used to represent direction and trend strength. Angles are used because they intrinsically represent momentum and speed. An angle of 45 represents a perfect balance between something that can cover the furthest distance without compensating for speed. 1 of the 6 angles is intended(though customizable) to represent the 5 hma's angle. This is because the 5hma is very good at representing very near term price action.
Angle Levels
Its important to understand what the angle levels mean for the underlying hma's. The 0 level represents a hma that is horizontal. This is important because this is the point at which it decides to be bullish or bearish. +/- 45, as noted before, represent bullishness/bearishness that represent strong trends without compensating for speed. A continuous increase/decrease and or a cross of these levels generally indicate significant change in sentiment, of which trades may be taken.
Strategy
You should weigh your decision by those angles that represent the longer time frame. If more angles represent a certain sentiment, it is obviously unwise to fight against that long term sentiment. The purpose of this indicator was to provide a proper representation of trend direction and strength, but also solve the problem of when you should 'dip' buy.
For an example: if all angles are increase or decreasing, then you may use the 5hma's angle to find the proper points at which you will enter a position.
***NOTE: I dont think the +/- 45 bands should indicate 'overbought' or 'oversold' zones that some might assume. Instead you should wait for a crossing of this zone.
Percentage price changeThis indicator marks bars whose values increase or decrease by an amount greater than or equal to the value of the specified parameter as a percentage. Bars that meet the condition are marked with labels, boxes and colors. In addition to the standard method of calculating the percentage change at the closing price of the current and previous bars, the indicator allows you to choose non-standard calculation methods (at the prices of opening and closing the current bar, as well as at the prices of the maximum at the minimum of the current bar). You can choose to display the percentage changes of individual bars as well as a series of bars. You can select the number of bars in a series of bars. You can also apply filters by the direction of the bars in the series or by the percentage of individual bars in the series.
It is important to remember that in version 5 of Pine Script™, the maximum possible number of labels and the maximum possible number of boxes cannot exceed 500!
There are several main parameters that can be changed in section PARAMETERS FOR CALCULATION:
1. 'Bars count' - The number of bars for which the percentage rise or fall is calculated.
2. ‘Percentage change’ - sets the price change as a percentage. Bars with a price range above or equal to the specified value will be marked on the chart.
3. ‘First and second points of calculation’ - the first and second points for calculating the percentage change. Here you can set several different values for the calculation:
- 'Cl.pr., Close' - Closing price of the previous bar and closing price of the current bar (or a series of bars) (these values are used for the standard calculation of the percentage change on the chart).
- 'Open, Close' - Opening and closing prices of the current bar (or a series of bars).
- 'High|Low' - Highest and lowest price of the current bar (or a series of bars).
- 'Cl.pr.|High|Low' - Highest or lowest price of the current bar (or a series of bars) (depending on whether the bar is going up or down) or closing price of the previous bar for first point (one of these values is automatically selected, which gives a larger result, depending on whether there is a gap between these values). Highest or lowest price of the current bar for second point.
In the LIMITS section, you can set the following parameters.
1. ‘Only for the last bar’ - If this option is selected, the indicator will be applied only for the last bar (or series of bars).
2. 'Only bars in one direction' - A condition that takes into account sequences from the selected number of bars going in only one direction. If at least one bar has a different direction from the other bars, then such a sequence will not be taken into account. This only works if the 'Bars count' is > 1.
3. "Cut off higher values" - This field cuts off higher values. Bars with a price range above or equal to the specified value will not be marked on the chart. This can be used in some cases to make the chart less loaded with data and more visual. Of course, you can also use this option however you want.
4. ‘Min percent in series of bars’ - If the value 'Number of bars' is > 1, then a series of bars is taken into account, in which the percentage change of individual bars is greater than or equal to the set value.
In the DATE RANGE section, you can set the limits of the time and date range in which the calculation will be performed. In some cases, this can be used in order not to exceed the limit on the number of labels or boxes, which cannot exceed 500. Of course, you can also use this option however you want. By default, the date range is unlimited.
'Timezone offset, hours' - It is used only for the correct display of the limits of the date range in the parameter table.
In the PRICE INCREASE LABELS and PRICE REDUCTION LABELS section, you can define the design of labels bars and boxes, such as colors, shapes, sizes, and location. You can set the colors of the bars separately on the Style tab. On the Style tab, you can also turn on/off the display of frames, labels and color markings of bars.
The PARAMETER TABLE section is designed to adjust the display of the table for a more visual display of the selected values of all parameters on the Arguments tab. Depending on which values have been set and which parameters have been enabled or disabled, the table will change its appearance, display or hide some rows. A single line 'Total found' will be displayed all the time. It shows the count of bars that meet the condition and count of labels or boxes used in the diagram. Since the bars are labeled with labels or boxes, their number cannot exceed 500 for Pine script version 5.
1. 'Pos.' - sets the main position of the table on the screen.
2. 'X off.', 'Y off.' - You can set the offset of the table along the X and Y axes. This option can be useful to avoid overlapping multiple tables if you want to use two or more instances of this indicator on your chart. The minimum value is -30, the maximum is 30. Positive values shift the table to the right on the X axis and up on the Y axis. Negative values shift the table to the left on the X axis and down on the Y axis.
3. 'Font color' - The font color in the table.
'Warn. font color', 'Warn. backgr. color' - The font and background colors in the 'Total found' row in the table. If the number of labels or boxes exceeds 500, the font and background will be colored in these colors.
4. ‘Font size’ – Sets the font size in the table.
5. 'Show hours and minutes in date/time range' - changes the date and time format of time range from {yyyy.MM.dd HH:mm} to {yyyy.MM.dd}.
6. 'View all params' - used to display all parameters, even those duplicated in the main line of the indicator.
7. ‘Title’ – If desired, you can make a header for the table.
The last row of the table shows the number of bars found that meet the conditions. Since these bars are marked with labels (in the case of one bar) or boxes (in the case of series of bars), the limit that can be marked on the chart is 500. Exceeding this value will be displayed in the table and additionally highlighted in red font. This will signal that not all bars found are displayed on the chart.
On the Style tab, you can turn the table display on/off.
US 30 Daily Breakout Strategy The US 30 Daily Breakout Strategy (Single Trade Per Breakout/Breakdown) is a trading approach for the US 30 (Dow Jones Industrial Average) that aims to capture breakout or breakdown moves based on the previous day’s high and low levels. The strategy includes mechanisms to take only one trade per breakout (or breakdown) each day and ensures that each trade is executed only when no other trade is open.
Entry Conditions:
Long Trade (Breakout): The strategy initiates a long position if the current candle closes above the previous day's high, indicating an upward breakout. Only one breakout trade can occur per day, regardless of whether the price remains above the previous high.
Short Trade (Breakdown): The strategy initiates a short position if the current candle closes below the previous day's low, indicating a downward breakdown. Similarly, only one breakdown trade can occur per day.
Risk Management:
Take Profit and Stop Loss: Each trade has a take profit and stop loss of 50 points, aiming to cap profit and limit loss effectively for each position.
Daily Reset Mechanism:
At the start of each new day (based on New York time), the strategy resets its flags, allowing it to look for new breakout or breakdown trades. This reset ensures that only one trade can be taken per breakout or breakdown level each day.
Execution Logic
Flags for Trade Limitation: Flags (breakout_traded and breakdown_traded) are used to ensure only one breakout or breakdown trade is taken per day. These flags reset daily.
Dynamic Plotting: The previous day’s high and low are plotted on the chart, providing a visual reference for potential breakout or breakdown levels.
Overall Objective
This strategy is designed to capture single-directional daily moves by identifying significant breakouts or breakdowns beyond the previous day’s range. The fixed profit and loss limits ensure the trades are managed with controlled risk, while the daily reset feature prevents overtrading and limits each trade opportunity to one breakout and one breakdown attempt per day.
Quick scan for cycles🙏🏻
The followup for
As I told before, ML based algorading is all about detecting any kind of non-randomness & exploiting it (cuz allegedly u cant trade randomness), and cycles are legit patterns that can be leveraged
But bro would u really apply Fourier / Wavelets / 'whatever else heavy' on every update of thousands of datasets, esp in real time on HFT / nearly HFT data? That's why this metric. It works much faster & eats hell of a less electicity, will do initial rough filtering of time series that might contain any kind of cyclic behaviour. And then, only on these filtered datasets u gonna put Periodograms / Autocorrelograms and see what's going there for real. Better to do it 10x times less a day on 10x less datasets, right?
I ended up with 2 methods / formulas, I called em 'type 0' and 'type 1':
- type 0: takes sum of abs deviations from drift line, scales it by max abs deviation from the same drift line;
- type 1: takes sum of abs deviations from drift line, scales it by range of non-abs deviations from the same drift line.
Finnaly I've chosen type 0 , both logically (sum of abs dev divided by max abs dev makes more sense) and experimentally. About that actually, here are both formulas put on sine waves with uniform noise:
^^ generated sine wave with uniform noise
^^ both formulas on that wave
^^ both formulas on real data
As you can see type 0 is less affected by noise and shows higher values on synthetic data, but I decided to put type 1 inside as well, in case my analysis was not complete and on real data type 1 can actually be better since it has a lil higher info gain / info content (still not sure). But I can assure u that out of all other ways I've designed & tested for quite a time I tell you, these 2 are really the only ones who got there.
Now about dem thresholds and how to use it.
Both type 0 and type 1 can be modelled with Beta distribution, and based on it and on some obvious & tho non mainstream statistical modelling techniques, I got these thresholds, so these are not optimized overfitted values, but natural ones. Each type has 3 thresholds (from lowest to highest):
- typical value (turned off by default). aka basis ;
- typical deviation from typical value, aka deviation ;
- maximum modelled deviation from typical value (idk whow to call it properly for now, this is my own R&D), aka extension .
So when the metric is above one of these thresholds (which one is up to you, you'll read about it in a sec), it means that there might be a strong enough periodic signal inside the data, and the data got to be put through proper spectral analysis tools to confirm / deny it.
If you look at the pictures above again, you'll see gray signal, that's uniform noise. Take a look at it and see where does it sit comparing to the thresholds. Now you just undertand that picking up a threshold is all about the amount of false positives you care to withstand.
If you take basis as threshold, you'll get tons of false positives (that's why it's even turned off by default), but you'll almost never miss a true positive. If you take deviation as threshold, it's gonna be kinda balanced approach. If you take extension as threshold, you gonna miss some cycles, and gonna get only the strongest ones.
More true positives -> more false positives, less false positives -> less true positives, can't go around that mane
Just to be clear again, I am not completely sure yet, but I def lean towards type 0 as metric, and deviation as threshold.
Live Long and Prosper
P.S.: That was actually the main R&D of the last month, that script I've released earlier came out as derivative.
P.S.: These 2 are the first R&Ds made completely in " art-space", St. Petersburg. Come and see me, say wassup🤘🏻
Unlock the Power of Seasonality: Monthly Performance StrategyThe Monthly Performance Strategy leverages the power of seasonality—those cyclical patterns that emerge in financial markets at specific times of the year. From tax deadlines to industry-specific events and global holidays, historical data shows that certain months can offer strong opportunities for trading. This strategy was designed to help traders capture those opportunities and take advantage of recurring market patterns through an automated and highly customizable approach.
The Inspiration Behind the Strategy:
This strategy began with the idea that market performance is often influenced by seasonal factors. Historically, certain months outperform others due to a variety of reasons, like earnings reports, holiday shopping, or fiscal year-end events. By identifying these periods, traders can better time their market entries and exits, giving them an advantage over those who solely rely on technical indicators or news events.
The Monthly Performance Strategy was built to take this concept and automate it. Instead of manually analyzing market data for each month, this strategy enables you to select which months you want to focus on and then executes trades based on predefined rules, saving you time and optimizing the performance of your trades.
Key Features:
Customizable Month Selection: The strategy allows traders to choose specific months to test or trade on. You can select any combination of months—for example, January, July, and December—to focus on based on historical trends. Whether you’re targeting the historically strong months like December (often driven by the 'Santa Rally') or analyzing quieter months for low volatility trades, this strategy gives you full control.
Automated Monthly Entries and Exits: The strategy automatically enters a long position on the first day of your selected month(s) and exits the trade at the beginning of the next month. This makes it perfect for traders who want to benefit from seasonal patterns without manually monitoring the market. It ensures precision in entering and exiting trades based on pre-set timeframes.
Re-entry on Stop Loss or Take Profit: One of the standout features of this strategy is its ability to re-enter a trade if a position hits the stop loss (SL) or take profit (TP) level during the selected month. If your trade reaches either a SL or TP before the month ends, the strategy will automatically re-enter a new trade the next trading day. This feature ensures that you capture multiple trading opportunities within the same month, instead of exiting entirely after a successful or unsuccessful trade. Essentially, it keeps your capital working for you throughout the entire month, not just when conditions align perfectly at the beginning.
Built-in Risk Management: Risk management is a vital part of this strategy. It incorporates an Average True Range (ATR)-based stop loss and take profit system. The ATR helps set dynamic levels based on the market’s volatility, ensuring that your stops and targets adjust to changing market conditions. This not only helps limit potential losses but also maximizes profit potential by adapting to market behavior.
Historical Performance Testing: You can backtest this strategy on any period by setting the start year. This allows traders to analyze past market data and optimize their strategy based on historical performance. You can fine-tune which months to trade based on years of data, helping you identify trends and patterns that provide the best trading results.
Versatility Across Asset Classes: While this strategy can be particularly effective for stock market indices and sector rotation, it’s versatile enough to apply to other asset classes like forex, commodities, and even cryptocurrencies. Each asset class may exhibit different seasonal behaviors, allowing you to explore opportunities across various markets with this strategy.
How It Works:
The trader selects which months to test or trade, for example, January, April, and October.
The strategy will automatically open a long position on the first trading day of each selected month.
If the trade hits either the take profit or stop loss within the month, the strategy will close the current position and re-enter a new trade on the next trading day, provided the month has not yet ended. This ensures that the strategy continues to capture any potential gains throughout the month, rather than stopping after one successful trade.
At the start of the next month, the position is closed, and if the next month is also selected, a new trade is initiated following the same process.
Risk Management and Dynamic Adjustments:
Incorporating risk management with this strategy is as easy as turning on the ATR-based system. The strategy will automatically calculate stop loss and take profit levels based on the market’s current volatility, adjusting dynamically to the conditions. This ensures that the risk is controlled while allowing for flexibility in capturing profits during both high and low volatility periods.
Maximizing the Seasonal Edge:
By automating entries and exits based on specific months and combining that with dynamic risk management, the Ultimate Monthly Performance Strategy takes advantage of seasonal patterns without requiring constant monitoring. The added re-entry feature after hitting a stop loss or take profit ensures that you are always in the game, maximizing your chances to capture profitable trades during favorable seasonal periods.
Who Can Benefit from This Strategy?
This strategy is perfect for traders who:
Want to exploit the predictable, recurring patterns that occur during specific months of the year.
Prefer a hands-off, automated trading approach that allows them to focus on other aspects of their portfolio or life.
Seek to manage risk effectively with ATR-based stop losses and take profits that adjust to market conditions.
Appreciate the ability to re-enter trades when a take profit or stop loss is hit within the month, ensuring that they don't miss out on multiple opportunities during a favorable period.
In summary, the Ultimate Monthly Performance Strategy provides traders with a comprehensive tool to capitalize on seasonal trends, optimize their trading opportunities throughout the year, and manage risk effectively. The built-in re-entry system ensures you continue to benefit from the market even after hitting targets within the same month, making it a robust strategy for traders looking to maximize their edge in any market.
Risk Disclaimer:
Trading financial markets involves significant risk and may not be suitable for all investors. The Monthly Performance Strategy is designed to help traders identify seasonal trends, but past performance does not guarantee future results. It is important to carefully consider your risk tolerance, financial situation, and trading goals before using any strategy. Always use appropriate risk management and consult with a professional financial advisor if necessary. The use of this strategy does not eliminate the risk of losses, and traders should be prepared for the possibility of losing their entire investment. Be sure to test the strategy on a demo account before applying it in live markets.
E9 Shark-32 Pattern Strategy The E9 Shark-32 Pattern is a powerful trading tool designed to capitalize on the Shark-32 pattern—a specific Candlestick pattern.
The Shark-32 Pattern: What Is It?
The Shark-32 pattern is a technical formation that occurs when the following conditions are met:
Higher Highs and Lower Lows: The low of two bars ago is lower than the previous bar, and the previous bar's low is lower than the current bar. At the same time, the high of two bars ago is higher than the previous bar, and the previous bar’s high is higher than the current bar.
This unique setup forms the "Shark-32" pattern, which signals potential volume squeezes and trend changes in the market.
How Does the Strategy Work?
The E9 Shark-32 Pattern Strategy builds upon this pattern by defining clear entry and exit rules based on the pattern's confirmation. Here's a breakdown of how the strategy operates:
1. Identifying the Shark-32 Pattern
When the Shark-32 pattern is confirmed, the strategy "locks" the high and low prices from the initial bar of the pattern. These locked prices serve as key levels for future trade entries and exits.
2. Entry Conditions
The strategy waits for the price to cross the pattern's locked high or low, signaling potential market direction.
Long Entry: A long trade is triggered when the closing price crosses above the locked pattern high (green line).
Short Entry: A short trade is triggered when the closing price crosses below the locked pattern low (red line).
The strategy ensures that only one trade is taken for each Shark-32 pattern, preventing overtrading and allowing traders to focus on high-probability setups.
3. Stop Loss and Take Profit Levels
The strategy has built-in risk management through stop-loss and take-profit levels, which are visually represented by the lines on the chart:
Stop Loss:
Stop loss can be adjusted in settings.
Take Profit:
For long trades: The take-profit target is set at the upper white dotted line, which is projected above the pattern high.
For short trades: The take-profit target is set at the lower white dotted line, which is projected below the pattern low.
These clearly defined levels help traders to manage risk effectively while maximizing potential returns.
4. Visual Cues
To make trading decisions even easier, the strategy provides helpful visual cues:
Green Line (Pattern High): This line represents the high of the Shark-32 pattern and serves as a resistance level and short entry signal.
Red Line (Pattern Low): This line represents the low of the Shark-32 pattern and serves as a support level and long entry signal.
White Dotted Lines: These lines represent potential profit targets, projected both above and below the pattern. They help traders define where the market might go next.
Additionally, the strategy highlights the pattern formation with color-coded bars and background shading to draw attention to the Shark-32 pattern when it is confirmed. This adds a layer of visual confirmation, making it easier to spot opportunities in real-time.
5. No Repeated Trades
An important aspect of the strategy is that once a trade is taken (either long or short), no additional trades are executed until a new Shark-32 pattern is identified. This ensures that only valid and confirmed setups are acted upon.
StyleLibraryLibrary "StyleLibrary"
A small library of Pine Script functions that return built-in style variables.
method sizeStyle(size)
Takes a `string` that returns the corresponding built-in size style variable.
Namespace types: series string, simple string, input string, const string
Parameters:
size (string) : A `string` representing a built-in size style: `"Tiny"`, `"Small"`, `"Normal"`, `"Large"`,
`"Huge"`, `"Auto"`.
Returns: The respective built-in size style variable.
method sizeStyle(size)
Takes a `sizeStyle` that returns the corresponding built-in size style variable.
Namespace types: series sizeStyle
Parameters:
size (series sizeStyle) : A `sizeStyle` representing a built-in size style variable.
Returns: The respective built-in size style variable.
method lineStyle(style)
Takes a `string` that returns the corresponding built-in line style variable.
Namespace types: series string, simple string, input string, const string
Parameters:
style (string) : A `string` representing a built-in line style: `"Dashed"`, `"Dotted"`, `"Solid"`.
Returns: The respective built-in line style variable.
method lineStyle(style)
Takes a `lineStyle` that returns the corresponding built-in line style variable.
Namespace types: series lineStyle
Parameters:
style (series lineStyle) : A `lineStyle` representing a built-in line style variable.
Returns: The respective built-in line style variable.
method labelStyle(style)
Takes a `string` that returns the corresponding built-in label style variable.
Namespace types: series string, simple string, input string, const string
Parameters:
style (string) : A `string` representing a built-in label style:
`"Arrow Down"`, `"Arrow Up"`, `"Circle"`, `"Cross"`, `"Diamond"`, `"Flag"`,
`"Label Center"`, `"Label Down"`, `"Label Left"`, `"Label Lower Left"`,
`"Label Lower Right"`, `"Label Right"`, `"Label Up"`, `"Label Upper Left"`,
`"Label Upper Right"`, `"None"`, `"Square"`, `"Text Outline"`, `"Triangle Down"`,
`"Triangle Up"`, `"XCross"`.
Returns: The respective built-in label style variable.
method labelStyle(style)
Takes a `labelStyle` that returns the corresponding built-in label style variable.
Namespace types: series labelStyle
Parameters:
style (series labelStyle) : A `labelStyle` representing a built-in label style variable.
Returns: The respective built-in label style variable.
method fontStyle(font)
Takes a `string` that returns the corresponding built-in font style variable.
Namespace types: series string, simple string, input string, const string
Parameters:
font (string) : A `string` representing a built-in font style: `"Default"`, `"Monospace"`.
Returns: The respective built-in font style variable.
method positionStyle(position)
Takes a `string` that returns the corresponding built-in position style variable.
Namespace types: series string, simple string, input string, const string
Parameters:
position (string) : A `string` representing a built-in position style:
`"Bottom Center", `"Bottom Left", `"Bottom Right", `"Middle Center", `"Middle Left",
`"Middle Right", `"Top Center", `"Top Left", `"Top Right".
Returns: The respective built-in position style variable.
method displayStyle(display)
Takes a `simple string` that returns the corresponding built-in display style variable.
Namespace types: simple string, input string, const string
Parameters:
display (simple string) : A `simple string` representing a built-in display style: `"All"`, `"Data Window"`,
`"None"`, `"Pane"`, `"Price Scale"`, `"Status Line"`.
Returns: The respective built-in display style variable.
Daily Bias Engine | PDH/PDL Range This program is designed to track the previous day range and interactions with the mean threshold on the following day.
The bias strategy is simple:
If you create new range highs over a PDH, you will lean towards calls.
If you create new range lows over a PDL, you will learn towards puts.
If neither event happens, no bias can be determined and therefore no trades taken.
If by 12:00pm there still is no bias determined, it will show moderate strength based on the trend.
Remember, use this strategy to outline your bias and find a cheap entry model to take advantage of.
Multi-Factor StrategyThis trading strategy combines multiple technical indicators to create a systematic approach for entering and exiting trades. The goal is to capture trends by aligning several key indicators to confirm the direction and strength of a potential trade. Below is a detailed description of how the strategy works:
Indicators Used
MACD (Moving Average Convergence Divergence):
MACD Line: The difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
Signal Line: A 9-period EMA of the MACD line.
Usage: The strategy looks for crossovers between the MACD line and the Signal line as entry signals. A bullish crossover (MACD line crossing above the Signal line) indicates a potential upward movement, while a bearish crossover (MACD line crossing below the Signal line) signals a potential downward movement.
RSI (Relative Strength Index):
Usage: RSI is used to gauge the momentum of the price movement. The strategy uses specific thresholds: below 70 for long positions to avoid overbought conditions and above 30 for short positions to avoid oversold conditions.
ATR (Average True Range):
Usage: ATR measures market volatility and is used to set dynamic stop-loss and take-profit levels. A stop loss is set at 2 times the ATR, and a take profit at 3 times the ATR, ensuring that risk is managed relative to market conditions.
Simple Moving Averages (SMA):
50-day SMA: A short-term trend indicator.
200-day SMA: A long-term trend indicator.
Usage: The strategy uses the relationship between the 50-day and 200-day SMAs to determine the overall market trend. Long positions are taken when the price is above the 50-day SMA and the 50-day SMA is above the 200-day SMA, indicating an uptrend. Conversely, short positions are taken when the price is below the 50-day SMA and the 50-day SMA is below the 200-day SMA, indicating a downtrend.
Entry Conditions
Long Position:
-MACD Crossover: The MACD line crosses above the Signal line.
-RSI Confirmation: RSI is below 70, ensuring the asset is not overbought.
-SMA Confirmation: The price is above the 50-day SMA, and the 50-day SMA is above the 200-day SMA, indicating a strong uptrend.
Short Position:
MACD Crossunder: The MACD line crosses below the Signal line.
RSI Confirmation: RSI is above 30, ensuring the asset is not oversold.
SMA Confirmation: The price is below the 50-day SMA, and the 50-day SMA is below the 200-day SMA, indicating a strong downtrend.
Opposite conditions for shorts
Exit Strategy
Stop Loss: Set at 2 times the ATR from the entry price. This dynamically adjusts to market volatility, allowing for wider stops in volatile markets and tighter stops in calmer markets.
Take Profit: Set at 3 times the ATR from the entry price. This ensures a favorable risk-reward ratio of 1:1.5, aiming for higher rewards on successful trades.
Visualization
SMAs: The 50-day and 200-day SMAs are plotted on the chart to visualize the trend direction.
MACD Crossovers: Bullish and bearish MACD crossovers are highlighted on the chart to identify potential entry points.
Summary
This strategy is designed to align multiple indicators to increase the probability of successful trades by confirming trends and momentum before entering a position. It systematically manages risk with ATR-based stop loss and take profit levels, ensuring that trades are exited based on market conditions rather than arbitrary points. The combination of trend indicators (SMAs) with momentum and volatility indicators (MACD, RSI, ATR) creates a robust approach to trading in various market environments.
