Hassi XAUUSD Advanced FVG EMA/BOS/RSI/Volume + Session FilterWhat it does :
This strategy automates a popular ICT-style idea on XAUUSD (Gold): trade only when price taps back into a Fair Value Gap (FVG), but filter entries with trend, structure, momentum, volume, and session rules. It manages risk with fixed TP/SL (points) and shows a compact backtest panel on chart.
Core Logic
1) Market Structure (BOS)
Detects recent swing highs/lows and flags a Break of Structure:
BOS Up when price breaks the latest swing high.
BOS Down when price breaks the latest swing low.
2) FVG Detection (3-candle)
Bullish FVG when low > high and low > high .
Bearish FVG when high < low and high < low .
The most recent qualifying gap is drawn as a shaded box (optional).
3) Bias & Filters
Trend Bias: price vs EMA (default 200). Longs only above EMA; shorts only below.
Momentum: optional RSI filter (default 14); avoid longs in OB & shorts in OS.
Volume: optional filter requiring current volume > SMA(20) × multiplier.
Sessions: optional London / New York (PKT) time windows.
Entries & Exits
Long Entry (all must be true)
Above EMA, RSI bullish, volume ok, session ok, BOS Up.
A recent Bullish FVG exists (within N bars).
Price taps back into the FVG (low ≤ top & close > bottom) with a bullish candle.
Short Entry (mirror)
Below EMA, RSI bearish, volume ok, session ok, BOS Down.
A recent Bearish FVG exists (within N bars).
Price taps (high ≥ bottom & close < top) with a bearish candle.
Risk / R:R
Exits use fixed points on XAUUSD (default TP 100, SL 50).
On many gold feeds 1.0 = 10 points; inputs convert to price automatically.
“One-trade-at-a-time”: a new signal won’t fire until the previous position is flat.
Chart Labels
On entry, the script plots BUY/SELL plus fixed TP/SL lines & labels anchored to the entry bar (they don’t drift with price).
Visuals & Tools
EMA line (green/red by bias).
Swing points (tiny triangles) to see structure.
FVG boxes (green/red, optional).
Session shading (subtle blue overlay).
Stats Panel (top-right):
Total Trades, TP Hits, SL Hits, Win Rate, Profit Factor, Net P&L.
Inputs (quick guide)
EMA Length (default 200)
Swing Lookback for BOS (default 5)
FVG Box Length (how far the zone extends to the right)
TP / SL (points) for XAUUSD + display Risk:Reward
Sessions (PKT): London & New York windows + toggle
Filters: Volume (multiplier), RSI (length, OB/OS)
Visibility: show/hide FVG boxes & TP/SL drawings
Alerts
Buy Signal / Sell Signal on valid entries
Position Opened / Position Closed notifications
Best Practices & Notes
Designed for XAUUSD 15-minute. You can test other timeframes, but retune TP/SL points and filters accordingly.
Broker ticks differ: if your symbol steps are not 0.1, adjust TP/SL points.
Use with a HTF confluence (e.g., D1/4H bias, key S/R, news awareness).
Backtests are approximations; real results vary with spreads, slippage, and execution.
Disclaimer: This tool is for educational purposes. It is not financial advice. Always test before using on live capital.
Search in scripts for "BOS"
BO - RSI - M5 BacktestingBO - RSI - M5 Backtesting -Rule of Strategy
A. Data
1. Chart M5 IDC
2. Symbol: EURJPY
B. Indicator
1. RSI
2. Length: 12 (adjustable)
3. Extreme Top: 75 (adjustable)
4. Extreme Bottom: 25 (adjustable)
C. Rule of Signal
1. Put Signal
* Rsi create a temporary peak over Extreme Top
row61: peak_rsi= rsi >rsi and rsi >rsi and rsi rsi_top
2. Call Signal
* Rsi create a temporary bottom under Extreme Bottom
row62: bott_rsi= rsi rsi and rsi
BO - Bar's direction Signal - BacktestingBO - Bar's direction Signal - Backtesting Options:
A. Factors Calculate probability of x bars same direction
1. Periods Counting: Data to count From day/month/year To day/month/year
2. Trading Time: only cases occurred in trading time were counted.
B. Timezone
1. Trading time depend on Time zone and specified chart.
2. Enable Highlight Trading Time to check your period time is correct
C. Date Backtesting
* Only cases occurred in Date Backtesting were reported.
D. Setup Options & Rule
1. Reversal after 2 bars same direction
* Probability of 3 bars same direction < 50
* 2 bars same direction is start of series
2. Reversal after 3 bars same direction
* Probability of 4 bars same direction < 50
* 3 bars same direction is start of series
3. Reversal after 4 bars same direction
* Probability of 4 bars same direction < 50
* 3 bars same direction is start of series
4. Reversal after 5 bars same direction
* Probability of 5 bars same direction < 50
* 4 bars same direction is start of series
5. Reversal after 6 bars same direction
* Probability of 6 bars same direction < 50
* 5 bars same direction is start of series
Liquidity Sweep + BOS Retest System — Prop Firm Edition🟦 Liquidity Sweep + BOS Retest System — Prop Firm Edition
A High-Probability Smart Money Strategy Built for NQ, ES, and Funding Accounts
🚀 Overview
The Liquidity Sweep + BOS Retest System (Prop Firm Edition) is a precision-engineered SMC strategy built specifically for prop firm traders. It mirrors institutional liquidity behavior and combines it with strict account-safe entry rules to help traders pass and maintain funding accounts with consistency.
Unlike typical indicators, this system waits for three confirmations — liquidity sweep, displacement, and a clean retest — before executing any trade. Every component is optimized for low drawdown, high R:R, and prop-firm-approved risk management.
Whether you’re trading Apex, TakeProfitTrader, FFF, or OneUp Trader, this system gives you a powerful mechanical framework that keeps you within rules while identifying the market’s highest-probability reversal zones.
🔥 Key Features
1. Liquidity Sweep Detection (Stop Hunt Logic)
Automatically identifies when price clears a previous swing high/low with a sweep confirmation candle.
✔ Filters noise
✔ Eliminates early entries
✔ Locks onto true liquidity grabs
2. Automatic Break of Structure (BOS) Confirmation
Price must show true displacement by breaking structure opposite the sweep direction.
✔ Confirms momentum shift
✔ Removes fake reversals
✔ Ensures institutional intent
3. Precision Retest Entry Model
The strategy enters only when price retests the BOS level at premium/discount pricing.
✔ Zero chasing
✔ Extremely tight stop loss placement
✔ Prop-firm-friendly controlled risk
4. Built-In Risk & Trade Management
SL set at swept liquidity
TP set by user-defined R:R multiplier
Optional session filter (NY Open by default)
One trade at a time (no pyramiding)
Automatically resets logic after each trade
This prevents overtrading — the #1 cause of evaluation and account breaches.
5. Designed for Prop Firm Futures Trading
This script is optimized for:
Trailing/static drawdown accounts
Micro contract precision
Funding evaluations
Low-risk, high-probability setups
Structured, rule-based execution
It reduces randomness and emotional trading by automating the highest-quality SMC sequence.
🎯 The Trading Model Behind the System
Step 1 — Liquidity Sweep
Price must take out a recent high/low and close back inside structure.
This confirms stop-hunting behavior and marks the beginning of a potential reversal.
Step 2 — BOS (Break of Structure)
Price must break the opposite side swing with a displacement candle. This validates a directional shift.
Step 3 — Retest Entry
The system waits for price to retrace into the BOS level and signal continuation.
This creates optimal R:R entry with minimal drawdown.
📈 Best Markets
NQ (NASDAQ Futures) – Highly recommended
ES, YM, RTY
Gold (XAUUSD)
FX majors
Crypto (with high volatility)
Works best on 1m, 2m, 5m, or 15m depending on your trading style.
🧠 Why Traders Love This System
✔ No signals until all confirmations align
✔ Reduces overtrading and emotional decisions
✔ Follows market structure instead of random indicators
✔ Perfect for maintaining long-term funded accounts
✔ Built around institutional-grade concepts
✔ Makes your trading consistent, calm, and rules-based
⚙️ Recommended Settings
Session: 06:30–08:00 MST (NY Open)
R:R: 1.5R – 3R
Contracts: Start with 1–2 micros
Markets: NQ for best structure & volume
📦 What’s Included
Complete strategy logic
All plots, labels, sweep markers & BOS alerts
BOS retest entry automation
Session filtering
Stop loss & take profit system
Full SMC logic pipeline
🏁 Summary
The Liquidity Sweep + BOS Retest System is a complete, prop-firm-ready, structure-based strategy that automates one of the cleanest and most reliable SMC entry models. It is designed to keep you safe, consistent, and rule-compliant while capturing premium institutional setups.
If you want to trade with confidence, discipline, and prop-firm precision — this system is for you.
Good Luck -BG
XAUUSD 1m SMC Zones (BOS + Flexible TP Modes + Trailing Runner)//@version=6
strategy("XAUUSD 1m SMC Zones (BOS + Flexible TP Modes + Trailing Runner)",
overlay = true,
initial_capital = 10000,
pyramiding = 10,
process_orders_on_close = true)
//━━━━━━━━━━━━━━━━━━━
// 1. INPUTS
//━━━━━━━━━━━━━━━━━━━
// TP / SL
tp1Pips = input.int(10, "TP1 (pips)", minval = 1)
fixedSLpips = input.int(50, "Fixed SL (pips)", minval = 5)
runnerRR = input.float(3.0, "Runner RR (TP2 = SL * RR)", step = 0.1, minval = 1.0)
// Daily risk
maxDailyLossPct = input.float(5.0, "Max daily loss % (stop trading)", step = 0.5)
maxDailyProfitPct = input.float(20.0, "Max daily profit % (stop trading)", step = 1.0)
// HTF S/R (1H)
htfTF = input.string("60", "HTF timeframe (minutes) for S/R block")
// Profit strategy (Option C)
profitStrategy = input.string("Minimal Risk | Full BE after TP1", "Profit Strategy", options = )
// Runner stop mode (your option 4)
runnerStopMode = input.string( "BE only", "Runner Stop Mode", options = )
// ATR trail settings (only used if ATR mode selected)
atrTrailLen = input.int(14, "ATR Length (trail)", minval = 1)
atrTrailMult = input.float(1.0, "ATR Multiplier (trail)", step = 0.1, minval = 0.1)
// Pip size (for XAUUSD: 1 pip = 0.10 if tick = 0.01)
pipSize = syminfo.mintick * 10.0
tp1Points = tp1Pips * pipSize
slPoints = fixedSLpips * pipSize
baseQty = input.float (1.0, "Base order size" , step = 0.01, minval = 0.01)
//━━━━━━━━━━━━━━━━━━━
// 2. DAILY RISK MANAGEMENT
//━━━━━━━━━━━━━━━━━━━
isNewDay = ta.change(time("D")) != 0
var float dayStartEquity = na
var bool dailyStopped = false
equityNow = strategy.initial_capital + strategy.netprofit
if isNewDay or na(dayStartEquity)
dayStartEquity := equityNow
dailyStopped := false
dailyPnL = equityNow - dayStartEquity
dailyPnLPct = dayStartEquity != 0 ? (dailyPnL / dayStartEquity) * 100.0 : 0.0
if not dailyStopped
if dailyPnLPct <= -maxDailyLossPct
dailyStopped := true
if dailyPnLPct >= maxDailyProfitPct
dailyStopped := true
canTradeToday = not dailyStopped
//━━━━━━━━━━━━━━━━━━━
// 3. 1H S/R ZONES (for direction block)
//━━━━━━━━━━━━━━━━━━━
htOpen = request.security(syminfo.tickerid, htfTF, open)
htHigh = request.security(syminfo.tickerid, htfTF, high)
htLow = request.security(syminfo.tickerid, htfTF, low)
htClose = request.security(syminfo.tickerid, htfTF, close)
// Engulf logic on HTF
htBullPrev = htClose > htOpen
htBearPrev = htClose < htOpen
htBearEngulf = htClose < htOpen and htBullPrev and htOpen >= htClose and htClose <= htOpen
htBullEngulf = htClose > htOpen and htBearPrev and htOpen <= htClose and htClose >= htOpen
// Liquidity sweep on HTF previous candle
htSweepHigh = htHigh > ta.highest(htHigh, 5)
htSweepLow = htLow < ta.lowest(htLow, 5)
// Store last HTF zones
var float htResHigh = na
var float htResLow = na
var float htSupHigh = na
var float htSupLow = na
if htBearEngulf and htSweepHigh
htResHigh := htHigh
htResLow := htLow
if htBullEngulf and htSweepLow
htSupHigh := htHigh
htSupLow := htLow
// Are we inside HTF zones?
inHtfRes = not na(htResHigh) and close <= htResHigh and close >= htResLow
inHtfSup = not na(htSupLow) and close >= htSupLow and close <= htSupHigh
// Block direction against HTF zones
longBlockedByZone = inHtfRes // no buys in HTF resistance
shortBlockedByZone = inHtfSup // no sells in HTF support
//━━━━━━━━━━━━━━━━━━━
// 4. 1m LOCAL ZONES (LIQUIDITY SWEEP + ENGULF + QUALITY SCORE)
//━━━━━━━━━━━━━━━━━━━
// 1m engulf patterns
bullPrev1 = close > open
bearPrev1 = close < open
bearEngulfNow = close < open and bullPrev1 and open >= close and close <= open
bullEngulfNow = close > open and bearPrev1 and open <= close and close >= open
// Liquidity sweep by previous candle on 1m
sweepHighPrev = high > ta.highest(high, 5)
sweepLowPrev = low < ta.lowest(low, 5)
// Local zone storage (one active support + one active resistance)
// Quality score: 1 = engulf only, 2 = engulf + sweep (we only trade ≥2)
var float supLow = na
var float supHigh = na
var int supQ = 0
var bool supUsed = false
var float resLow = na
var float resHigh = na
var int resQ = 0
var bool resUsed = false
// New resistance zone: previous bullish candle -> bear engulf
if bearEngulfNow
resLow := low
resHigh := high
resQ := sweepHighPrev ? 2 : 1
resUsed := false
// New support zone: previous bearish candle -> bull engulf
if bullEngulfNow
supLow := low
supHigh := high
supQ := sweepLowPrev ? 2 : 1
supUsed := false
// Raw "inside zone" detection
inSupRaw = not na(supLow) and close >= supLow and close <= supHigh
inResRaw = not na(resHigh) and close <= resHigh and close >= resLow
// QUALITY FILTER: only trade zones with quality ≥ 2 (engulf + sweep)
highQualitySup = supQ >= 2
highQualityRes = resQ >= 2
inSupZone = inSupRaw and highQualitySup and not supUsed
inResZone = inResRaw and highQualityRes and not resUsed
// Plot zones
plot(supLow, "Sup Low", color = color.new(color.lime, 60), style = plot.style_linebr)
plot(supHigh, "Sup High", color = color.new(color.lime, 60), style = plot.style_linebr)
plot(resLow, "Res Low", color = color.new(color.red, 60), style = plot.style_linebr)
plot(resHigh, "Res High", color = color.new(color.red, 60), style = plot.style_linebr)
//━━━━━━━━━━━━━━━━━━━
// 5. MODERATE BOS (3-BAR FRACTAL STRUCTURE)
//━━━━━━━━━━━━━━━━━━━
// 3-bar swing highs/lows
swHigh = high > high and high > high
swLow = low < low and low < low
var float lastSwingHigh = na
var float lastSwingLow = na
if swHigh
lastSwingHigh := high
if swLow
lastSwingLow := low
// BOS conditions
bosUp = not na(lastSwingHigh) and close > lastSwingHigh
bosDown = not na(lastSwingLow) and close < lastSwingLow
// Zone “arming” and BOS validation
var bool supArmed = false
var bool resArmed = false
var bool supBosOK = false
var bool resBosOK = false
// Arm zones when first touched
if inSupZone
supArmed := true
if inResZone
resArmed := true
// BOS after arming → zone becomes valid for entries
if supArmed and bosUp
supBosOK := true
if resArmed and bosDown
resBosOK := true
// Reset BOS flags when new zones are created
if bullEngulfNow
supArmed := false
supBosOK := false
if bearEngulfNow
resArmed := false
resBosOK := false
//━━━━━━━━━━━━━━━━━━━
// 6. ENTRY CONDITIONS (ZONE + BOS + RISK STATE)
//━━━━━━━━━━━━━━━━━━━
flatOrShort = strategy.position_size <= 0
flatOrLong = strategy.position_size >= 0
longSignal = canTradeToday and not longBlockedByZone and inSupZone and supBosOK and flatOrShort
shortSignal = canTradeToday and not shortBlockedByZone and inResZone and resBosOK and flatOrLong
//━━━━━━━━━━━━━━━━━━━
// 7. ORDER LOGIC – TWO PROFIT STRATEGIES
//━━━━━━━━━━━━━━━━━━━
// Common metrics
atrTrail = ta.atr(atrTrailLen)
// MINIMAL MODE: single trade, BE after TP1, optional trailing
// HYBRID MODE: two trades (Scalp @ TP1, Runner @ TP2)
// Persistent tracking
var float longEntry = na
var float longTP1 = na
var float longTP2 = na
var float longSL = na
var bool longBE = false
var float longRunEntry = na
var float longRunTP1 = na
var float longRunTP2 = na
var float longRunSL = na
var bool longRunBE = false
var float shortEntry = na
var float shortTP1 = na
var float shortTP2 = na
var float shortSL = na
var bool shortBE = false
var float shortRunEntry = na
var float shortRunTP1 = na
var float shortRunTP2 = na
var float shortRunSL = na
var bool shortRunBE = false
isMinimal = profitStrategy == "Minimal Risk | Full BE after TP1"
isHybrid = profitStrategy == "Hybrid | Scalp TP + Runner TP"
//━━━━━━━━━━ LONG ENTRIES ━━━━━━━━━━
if longSignal
if isMinimal
longEntry := close
longSL := longEntry - slPoints
longTP1 := longEntry + tp1Points
longTP2 := longEntry + slPoints * runnerRR
longBE := false
strategy.entry("Long", strategy.long)
supUsed := true
supArmed := false
supBosOK := false
else if isHybrid
longRunEntry := close
longRunSL := longRunEntry - slPoints
longRunTP1 := longRunEntry + tp1Points
longRunTP2 := longRunEntry + slPoints * runnerRR
longRunBE := false
// Two separate entries, each 50% of baseQty (for backtest)
strategy.entry("LongScalp", strategy.long, qty = baseQty * 0.5)
strategy.entry("LongRun", strategy.long, qty = baseQty * 0.5)
supUsed := true
supArmed := false
supBosOK := false
//━━━━━━━━━━ SHORT ENTRIES ━━━━━━━━━━
if shortSignal
if isMinimal
shortEntry := close
shortSL := shortEntry + slPoints
shortTP1 := shortEntry - tp1Points
shortTP2 := shortEntry - slPoints * runnerRR
shortBE := false
strategy.entry("Short", strategy.short)
resUsed := true
resArmed := false
resBosOK := false
else if isHybrid
shortRunEntry := close
shortRunSL := shortRunEntry + slPoints
shortRunTP1 := shortRunEntry - tp1Points
shortRunTP2 := shortRunEntry - slPoints * runnerRR
shortRunBE := false
strategy.entry("ShortScalp", strategy.short, qty = baseQty * 50)
strategy.entry("ShortRun", strategy.short, qty = baseQty * 50)
resUsed := true
resArmed := false
resBosOK := false
//━━━━━━━━━━━━━━━━━━━
// 8. EXIT LOGIC – MINIMAL MODE
//━━━━━━━━━━━━━━━━━━━
// LONG – Minimal Risk: 1 trade, BE after TP1, runner to TP2
if isMinimal and strategy.position_size > 0 and not na(longEntry)
// Move to BE once TP1 is touched
if not longBE and high >= longTP1
longBE := true
// Base SL: BE or initial SL
float dynLongSL = longBE ? longEntry : longSL
// Optional trailing after BE
if longBE
if runnerStopMode == "Structure trail" and not na(lastSwingLow) and lastSwingLow > longEntry
dynLongSL := math.max(dynLongSL, lastSwingLow)
if runnerStopMode == "ATR trail"
trailSL = close - atrTrailMult * atrTrail
dynLongSL := math.max(dynLongSL, trailSL)
strategy.exit("Long Exit", "Long", stop = dynLongSL, limit = longTP2)
// SHORT – Minimal Risk: 1 trade, BE after TP1, runner to TP2
if isMinimal and strategy.position_size < 0 and not na(shortEntry)
if not shortBE and low <= shortTP1
shortBE := true
float dynShortSL = shortBE ? shortEntry : shortSL
if shortBE
if runnerStopMode == "Structure trail" and not na(lastSwingHigh) and lastSwingHigh < shortEntry
dynShortSL := math.min(dynShortSL, lastSwingHigh)
if runnerStopMode == "ATR trail"
trailSLs = close + atrTrailMult * atrTrail
dynShortSL := math.min(dynShortSL, trailSLs)
strategy.exit("Short Exit", "Short", stop = dynShortSL, limit = shortTP2)
//━━━━━━━━━━━━━━━━━━━
// 9. EXIT LOGIC – HYBRID MODE
//━━━━━━━━━━━━━━━━━━━
// LONG – Hybrid: Scalp + Runner
if isHybrid
// Scalp leg: full TP at TP1
if strategy.opentrades > 0
strategy.exit("LScalp TP", "LongScalp", stop = longRunSL, limit = longRunTP1)
// Runner leg
if strategy.position_size > 0 and not na(longRunEntry)
if not longRunBE and high >= longRunTP1
longRunBE := true
float dynLongRunSL = longRunBE ? longRunEntry : longRunSL
if longRunBE
if runnerStopMode == "Structure trail" and not na(lastSwingLow) and lastSwingLow > longRunEntry
dynLongRunSL := math.max(dynLongRunSL, lastSwingLow)
if runnerStopMode == "ATR trail"
trailRunSL = close - atrTrailMult * atrTrail
dynLongRunSL := math.max(dynLongRunSL, trailRunSL)
strategy.exit("LRun TP", "LongRun", stop = dynLongRunSL, limit = longRunTP2)
// SHORT – Hybrid: Scalp + Runner
if isHybrid
if strategy.opentrades > 0
strategy.exit("SScalp TP", "ShortScalp", stop = shortRunSL, limit = shortRunTP1)
if strategy.position_size < 0 and not na(shortRunEntry)
if not shortRunBE and low <= shortRunTP1
shortRunBE := true
float dynShortRunSL = shortRunBE ? shortRunEntry : shortRunSL
if shortRunBE
if runnerStopMode == "Structure trail" and not na(lastSwingHigh) and lastSwingHigh < shortRunEntry
dynShortRunSL := math.min(dynShortRunSL, lastSwingHigh)
if runnerStopMode == "ATR trail"
trailRunSLs = close + atrTrailMult * atrTrail
dynShortRunSL := math.min(dynShortRunSL, trailRunSLs)
strategy.exit("SRun TP", "ShortRun", stop = dynShortRunSL, limit = shortRunTP2)
//━━━━━━━━━━━━━━━━━━━
// 10. RESET STATE WHEN FLAT
//━━━━━━━━━━━━━━━━━━━
if strategy.position_size == 0
longEntry := na
shortEntry := na
longBE := false
shortBE := false
longRunEntry := na
shortRunEntry := na
longRunBE := false
shortRunBE := false
//━━━━━━━━━━━━━━━━━━━
// 11. VISUAL ENTRY MARKERS
//━━━━━━━━━━━━━━━━━━━
plotshape(longSignal, title = "Long Signal", style = shape.triangleup,
location = location.belowbar, color = color.lime, size = size.tiny, text = "L")
plotshape(shortSignal, title = "Short Signal", style = shape.triangledown,
location = location.abovebar, color = color.red, size = size.tiny, text = "S")
Gold Scalping BOS & CHoCHThis strategy is designed for scalping gold (XAU/USD) on the 3-minute timeframe, utilizing Break of Structure (BOS) and Change of Character (CHoCH) to identify high-probability trade setups. Unlike traditional SMA crossover strategies, this method focuses purely on price action and market structure shifts, allowing for early entries and better risk management.
Core Concepts:
Break of Structure (BOS) – Confirms a continuation of the trend when price breaks the last swing high (bullish) or last swing low (bearish).
Change of Character (CHoCH) – Detects possible trend reversals by identifying a shift in market momentum.
Dynamic Support & Resistance – Uses the last 10-bar highs and lows to determine adaptive stop-loss (SL) and take-profit (TP) levels.
Risk-to-Reward Ratio (1:2 RR) – Ensures trades are executed with a favorable risk/reward ratio.
Entry Conditions:
Buy Entry:
BOS (Bullish) confirmed (price breaks the previous swing high).
CHoCH (Bullish) confirms trend shift.
Price crosses back above the last swing low (confirmation of support).
Sell Entry:
BOS (Bearish) confirmed (price breaks the previous swing low).
CHoCH (Bearish) confirms trend shift.
Price crosses back below the last swing high (confirmation of resistance).
Exit Conditions:
Stop Loss (SL): Set at the most recent dynamic support (for buys) or resistance (for sells).
Take Profit (TP): 2x the risk (1:2 risk-reward ratio).
Advantages of This Strategy:
✅ No lagging indicators – Uses price action for real-time entries.
✅ High probability setups – Focuses only on strong structural breaks.
✅ Adaptive SL/TP – Uses real market structure instead of fixed values.
✅ Optimized for Scalping – Best suited for quick in-and-out trades.
Best Time to Trade:
🔹 London & New York Sessions (High volatility for gold).
4H Confirmation + 1H SFP BOS Retest4H Confirmation + 1H Entry (SFP + BOS + Retest)Run it on 1H
Uses 4H EMAs for higher-timeframe direction (confirmation)
Uses 1H SFP + BOS + retest + RSI for entries
This gives you more trades, still guided by the 4H trend
SMC Pro [Stansbooth]
🔮 SMC × Fibonacci Confluence Engine — The Hidden Algorithm of the Markets
Welcome to a level of chart analysis where mathematics , market psychology , and institutional logic merge into one ultra-intelligent system.
This indicator decodes the true structure of price delivery by combining Smart Money Concepts with the timeless precision of Fibonacci ratios , revealing what retail traders can’t see — *the algorithmic heartbeat of the market*.
✨ What Makes This Indicator Different
Instead of drawing random lines or reacting to late signals, this tool **anticipates** market behavior by reading the footprints left behind by institutional algorithms. Every element is placed with purpose — every zone, every shift, every fib level — all forming a seamless narrative that explains *why* price moves the way it does.
🔥 Core Intelligence Features
Advanced BOS/CHOCH Auto-Detection — Spot structure shifts before momentum even forms.
Institutional Liquidity Mapping
— Identify liquidity pools, engineered sweeps, equal highs/lows, and trap zones designed by smart money.
Fibonacci-Aligned Precision Zones
— Auto-generated fib grids synced with SMC levels for pinpoint reversal and continuation setups.
Imbalance Engine
— FVGs, displacement, inefficiencies, and mitigation blocks displayed with crystal clarity.
Premium/Discount Algorithm
— Understand instantly whether price is in a zone of accumulation or distribution.
🚀 Designed for Traders Who Want an Edge
Whether you're scalping fast moves, capturing intraday swings, or holding higher-timeframe plays, this indicator provides a professional lens into the market. It turns complex price action into a structured, predictable system where every move has logic and every entry has confluence.
You don’t just see the chart —
you see the intention behind every push, pull, manipulation, and reversal.
💎 Why It Feels Like a Cheat Code
Because it mirrors the way institutions analyze the market:
— Identify liquidity
— Seek equilibrium
— Deliver price
— Create inefficiency
— Mitigate
— Continue the narrative
Using SMC and Fibonacci together unlocks the “algorithmic geometry” behind price movement, giving you clarity where others see chaos.
⚡ Trade With Confidence, Confluence & Control
This indicator isn’t just a tool.
It’s a complete trading framework — structured, intelligent, and deadly accurate.
Master the markets.
Decode the algorithm.
Trade like smart money .
adrianasibaja_ ALGO (Liquidity/BOS/FVG + Sessions + Risk Locks)This strategy is an institutional-style automated trading system designed for XAU/USD and FTMO-funded accounts.
It combines liquidity sweeps, Break of Structure (BOS) and Fair Value Gap (FVG) confirmations with multi-filter confluences (RSI, ADX, ATR, EMA trend bias, and candle quality).
The algorithm automatically filters trades by session (London/New York), day of week, and volatility. It includes full FTMO risk management features such as daily loss lock, consecutive loss lock, and trade cooldowns.
RunRox - Backtesting System (ASMC)Introducing RunRox - Backtesting System (ASMC), a specially designed backtesting system built on the robust structure of our Advanced SMC indicator. This innovative tool evaluates various Smart Money Concept (SMC) trading setups and serves as an automatic optimizer, displaying which entry and exit points have historically shown the best results. With cutting-edge technology, RunRox - Backtesting System (ASMC) provides you with effective strategies, maximizing your trading potential and taking your trading to the next level
🟠 HOW OUR BACKTESTING SYSTEM WORKS
Our backtesting system for the Advanced SMC (ASMC) indicator is meticulously designed to provide traders with a thorough analysis of their Smart Money Concept (SMC) strategies. Here’s an overview of how it works:
🔸 Advanced SMC Structure
Our ASMC indicator is built upon an enhanced SMC structure that integrates the Institutional Distribution Model (IDM), precise retracements, and five types of order blocks (CHoCH OB, IDM OB, Local OB, BOS OB, Extreme OB). These components allow for a detailed understanding of market dynamics and the identification of key trading opportunities.
🔸 Data Integration and Analysis
1. Historical Data Testing:
Our system tests various entry and exit points using historical market data.
The ASMC indicator is used to simulate trades based on predefined SMC setups, evaluating their effectiveness over a specified time period.
Traders can select different parameters such as entry points, stop-loss, and take-profit levels to see how these setups would have performed historically.
2. Entry and Exit Events:
The backtester can simulate trades based on 12 different entry events, 14 target events, and 14 stop-loss events, providing a comprehensive testing framework.
It allows for testing with multiple combinations of entry and exit strategies, ensuring a robust evaluation of trading setups.
3. Order Block Sensitivity:
The system uses the sensitivity settings from the ASMC indicator to determine the most relevant order blocks and fair value gaps (FVGs) for entry and exit points.
It distinguishes between different types of order blocks, helping traders identify strong institutional zones versus local zones.
🔸 Optimization Capabilities
1. Auto-Optimizer:
The backtester includes an auto-optimizer feature that evaluates various setups to find those with the best historical performance.
It automatically adjusts parameters to identify the most effective strategies for both trend-following and counter-trend trading.
2. Stop Loss and Take Profit Optimization:
It optimizes stop-loss and take-profit levels by testing different settings and identifying those that provided the best historical results.
This helps traders refine their risk management and maximize potential returns.
3. Trailing Stop Optimization:
The system also optimizes trailing stops, ensuring that traders can maximize their profits by adjusting their stops dynamically as the market moves.
🔸 Comprehensive Reporting
1. Performance Metrics:
The backtesting system provides detailed reports, including key performance metrics such as Net Profit, Win Rate, Profit Factor, and Max Drawdown.
These metrics help traders understand the historical performance of their strategies and make data-driven decisions.
2. Flexible Settings:
Traders can adjust initial balance, commission rates, and risk per trade settings to simulate real-world trading conditions.
The system supports testing with different leverage settings, allowing for realistic assessments even with tight stop-loss levels.
🔸 Conclusion
The RunRox Backtesting System (ASMC) is a powerful tool for traders seeking to validate and optimize their SMC strategies. By leveraging historical data and sophisticated optimization algorithms, it provides insights into the most effective setups, enhancing trading performance and decision-making.
🟠 HERE ARE THE AVAILABLE FEATURES
Historical backtesting for any setup – Select any entry point, exit point, and various stop-loss options to see the results of your setup on historical data.
Auto-optimizer for finding the best setups – The indicator displays settings that have shown the best results historically, providing valuable insights.
Auto-optimizer for counter-trend setups – Discover entry and exit points for counter-trend trading based on historical performance.
Auto-optimizer for stop-loss – The indicator shows stop-loss points that have been most effective historically.
Auto-optimizer for take-profit – The indicator identifies take-profit points that have performed well in historical trading data.
Auto-optimizer for trailing stop – The indicator presents trailing stop settings that have shown the best historical results.
And much more within our indicator, all of which we will cover in this post. Next, we will showcase the possible entry points, targets, and stop-loss options available for testing your strategies
🟠 ENTRY SETTINGS
12 Event Triggers for Trade Entry
Extr. ChoCh OB
Extr. ChoCh FVG
ChoCh
ChoCh OB
ChoCh FVG
IDM OB
IDM FVG
BoS FVG
BoS OB
BoS
Extr. BoS FVG
Extr. BoS OB
3 Trade Direction Options
Long Only: Enter long positions only
Short Only: Enter short positions only
Long and Short: Enter both long and short positions based on trend
3 Levels for Order Block/FVG Entries
Beginning: Enter the trade at the first touch of the Order Block/FVG
Middle: Enter the trade when the middle of the Order Block/FVG is reached
End: Enter the trade upon full filling of the Order Block/FVG
*Three levels work only for Order Blocks and FVG. For trade entries based on BOS or CHoCH, these settings do not apply as these parameters are not available for these types of entries
You can choose any combination of trade entries imaginable.
🟠 TARGET SETTINGS
14 Target Events, Including Fixed % and Fixed RR (Risk/Reward):
Fixed - % change in price
Fixed RR - Risk Reward per trade
Extr. ChoCh OB
Extr. ChoCh FVG
ChoCh
ChoCh OB
ChoCh FVG
IDM OB
IDM FVG
BoS FVG
BoS OB
BoS
Extr. BoS FVG
Extr. BoS OB
3 Levels of Order Block/FVG for Target
Beginning: Close the trade at the first touch of your target.
Middle: Close the trade at the midpoint of your chosen target.
End: Close the trade when your target is fully filled.
Customizable Parameters
Easily set your Fixed % and Fixed RR targets with a user-friendly input field. This field works only for the Fixed and Fixed RR entry parameters. When selecting a different entry point, this field is ignored
Choose any combination of target events to suit your trading strategy.
🟠 STOPLOSS SETTINGS
14 Possible StopLoss Events Including Entry Orderblock/FVG
Fixed - Fix the loss on the trade when the price moves by N%
Entry Block
Extr. ChoCh OB
Extr. ChoCh FVG
ChoCh
ChoCh OB
ChoCh FVG
IDM OB
IDM FVG
BoS FVG
BoS OB
BoS
Extr. BoS FVG
Extr. BoS OB
3 Levels for Order Blocks/FVG Exits
Beginning: Exit the trade at the first touch of the order block/FVG.
Middle: Exit the trade at the middle of the order block/FVG.
End: Exit the trade at the full completion of the order block/FVG.
Dedicated Field for Setting Fixed % Value
Set a fixed % value in a dedicated field for the Fixed parameter. This field works only for the Fixed parameter. When selecting other exit parameters, this field is ignored.
🟠 ADDITIONAL SETTINGS
Trailing Stop, %
Set a Trailing Stop as a percentage of your trade to potentially increase profit based on historical data.
Move SL to Breakeven, bars
Move your StopLoss to breakeven after exiting the entry zone for a specified number of bars. This can enhance your potential WinRate based on historical performance.
Skip trade if RR less than
This feature allows you to skip trades where the potential Risk-to-Reward ratio is less than the number set in this field.
🟠 EXAMPLE OF MANUAL SETUP
For example, let me show you how it works on the chart. You select entry parameters, stop loss parameters, and take profit parameters for your trades, and the strategy automatically tests this setup on historical data, allowing you to see the results of this strategy.
In the screenshot above, the parameters were as follows:
Trade Entry: CHoCH OB (Beginning)
Stop Loss: Entry Block
Take Profit: Break of BOS
The indicator will automatically test all possible trades on the chart and display the results for this setup.
🟠 AUTO OPTIMIZATION SETTINGS
In the screenshot above, you can see the optimization table displaying various entry points, exits, and stop-loss settings, along with their historical performance results and other parameters. This feature allows you to identify trading setups that have shown the best historical outcomes.
This functionality will enhance your trading approach, providing you with valuable insights based on historical data. You’ll be aware of the Smart Money Concept settings that have historically worked best for any specific chart and timeframe.
Our indicator includes various optimization options designed to help you find the most effective settings based on historical data. There are 5 optimization modes, each offering unique benefits for every trader
Trend Entry - Optimization of the best settings for trend-following trades. The strategy will enter trades only in the direction of the trend. If the trend is upward, it will look for long entry points and vice versa.
Counter Trend Entry - Finding setups against the trend. If the trend is upward, the script will search for short entry points. This is the opposite of trend entry optimization.
Stop Loss - Identifying stop-loss points that showed the best historical performance for the specific setup you have configured. This helps in finding effective exit points to minimize losses.
Take Profit - Determining targets for the configured setup based on historical performance, helping to identify potentially profitable take profit levels.
Trailing Stop - Finding optimal percentages for the trailing stop function based on historical data, which can potentially increase the profit of your trades.
Ability to set parameters for auto-optimization within a specified range. For example, if you choose FixRR TP from 1 to 10, the indicator will automatically test all possible Risk Reward Take Profit variations from 1 to 10 and display the results for each parameter individually.
Ability to set initial deposit parameters, position commissions, and risk per trade as a fixed percentage or fixed amount. Additionally, you can set the maximum leverage for a trade.
There are times when the stop loss is very close to the entry point, and adhering to the risk per trade values set in the settings may not allow for such a loss in any situation. That’s why we added the ability to set the maximum possible leverage, allowing you to test your trading strategy even with very tight stop losses.
Duplicated Smart Money Structure settings from our Advanced SMC indicator that you can adjust to match your trading style flexibly. All these settings will be taken into account during the optimization process or when manually calculating settings.
Additionally, you can test your strategy based on higher timeframe order blocks. For example, you can test a strategy on a 1-minute chart while displaying order blocks from a 15-minute timeframe. The auto-optimizer will consider all these parameters, including higher timeframe order blocks, and will enter trades based on these order blocks.
Highly flexible dashboard and results optimization settings allow you to display the tables you need and sort results by six different criteria: Profit Factor, Profit, Winrate, Max Drawdown, Wins, and Trades. This enables you to find the exact setup you desire, based on these comprehensive data points.
🟠 ALERT CUSTOMIZATION
With this indicator, you can set up buy and sell alerts based on the test results, allowing you to create a comprehensive trading strategy. This feature enables you to receive real-time signals, making it a powerful tool for implementing your trading strategies.
🟠 STRATEGY PROPERTIES
For backtesting, we used realistic initial data for entering trades, such as:
Starting balance: $1000
Commission: 0.01%
Risk per trade: 1%
To ensure realistic data, we used the above settings. We offer two methods for calculating your order size, and in our case, we used a 1% risk per trade. Here’s what it means:
Risk per trade: This is the maximum loss from your deposit if the trade goes against you. The trade volume can change depending on your stop-loss distance from the entry point. Here’s the formula we use to calculate the possible volume for a single trade:
1. quantity = percentage_risk * balance / loss_per_1_contract (incl. fee)
Then, we calculate the maximum allowed volume based on the specified maximum leverage:
2. max_quantity = maxLeverage * balance / entry_price
3. If quantity < max_quantity, meaning the leverage is less than the maximum allowed, we keep quantity. If quantity > max_quantity, we use max_quantity (the maximum allowed volume according to the set leverage).
This way, depending on the stop-loss distance, the position size can vary and be up to 100% of your deposit, but the loss in each trade will not exceed the set percentage, which in our case is 1% for this backtest. This is a standard risk calculation method based on your stop-loss distance.
🔸 Statistical Significance of Trade Data
In our strategy, you may notice there weren’t enough trades to form statistically significant data. This is inherent to the Smart Money Concept (SMC) strategy, where the focus is not on the number of trades but rather on the risk-to-reward ratio per trade. In SMC strategies, it’s crucial to avoid taking numerous uncertain setups and instead perform a comprehensive analysis of the market situation.
Therefore, our strategy results show fewer than 100 trades. It’s important to understand that this small sample size isn’t statistically significant and shouldn’t be relied upon for strategy analysis. Backtesting with a small number of trades should not be used to draw conclusions about the effectiveness of a strategy.
🔸 Versatile Use Cases
The methods of using this indicator are numerous, ranging from identifying potentially the best-performing order blocks on the chart to creating a comprehensive trading strategy based on the data provided by our indicator. We believe that every trader will find a valuable application for this tool, enhancing their entry and exit points in trades.
Disclaimer
Past performance is not indicative of future results. The results shown by this indicator do not guarantee similar outcomes in the future. Use this tool as part of a comprehensive trading strategy, considering all market conditions and risks.
How to access
For access to this indicator, please read the author’s instructions below this post
S&D Light+ Enhanced# S&D Light+ Enhanced - Supply & Demand Zone Trading Strategy
## 📊 Overview
**S&D Light+ Enhanced** is an advanced Supply and Demand zone identification and trading strategy that combines institutional order flow concepts with smart money techniques. This strategy automatically identifies high-probability reversal zones based on Break of Structure (BOS), momentum analysis, and first retest principles.
## 🎯 Key Features
### Smart Zone Detection
- **Automatic Supply & Demand Zone Identification** - Detects institutional zones where price is likely to react
- **Multi-Candle Momentum Analysis** - Validates zones with configurable momentum requirements
- **Break of Structure (BOS) Confirmation** - Ensures zones are created only after significant structure breaks
- **Quality Filters** - Minimum zone size and ATR-based filtering to eliminate weak zones
### Advanced Zone Management
- **Customizable Zone Display** - Choose between Geometric or Volume-Weighted midlines
- **First Retest Logic** - Option to trade only the first touch of each zone for higher probability setups
- **Zone Capacity Control** - Maintains a clean chart by limiting stored zones per type
- **Visual Zone Status** - Automatically marks consumed zones with faded midlines
### Risk Management
- **Dynamic Stop Loss** - Positioned beyond zone boundaries with adjustable buffer
- **Risk-Reward Ratio Control** - Customizable R:R for consistent risk management
- **Entry Spacing** - Minimum bars between signals prevents overtrading
- **Position Sizing** - Built-in percentage of equity allocation
## 🔧 How It Works
### Zone Creation Logic
**Supply Zones (Selling Pressure):**
1. Strong momentum downward movement (configurable body-to-range ratio)
2. Identified bullish base candle (where institutions accumulated shorts)
3. Break of Structure downward (price breaks below recent swing low)
4. Zone created at the base candle's high/low range
**Demand Zones (Buying Pressure):**
1. Strong momentum upward movement
2. Identified bearish base candle (where institutions accumulated longs)
3. Break of Structure upward (price breaks above recent swing high)
4. Zone created at the base candle's high/low range
### Entry Conditions
**Long Entry:**
- Price retests a demand zone (touches top of zone)
- Rejection confirmed (close above zone)
- Zone hasn't been used (if "first retest only" enabled)
- Minimum bars since last entry respected
**Short Entry:**
- Price retests a supply zone (touches bottom of zone)
- Rejection confirmed (close below zone)
- Zone hasn't been used (if "first retest only" enabled)
- Minimum bars since last entry respected
## ⚙️ Customizable Parameters
### Display Settings
- **Show Zones** - Toggle zone visualization on/off
- **Max Stored Zones** - Control number of active zones (1-50 per type)
- **Color Customization** - Adjust supply/demand colors and transparency
### Zone Quality Filters
- **Momentum Body Fraction** - Minimum body size for momentum candles (0.1-0.9)
- **Min Momentum Candles** - Number of consecutive momentum candles required (1-5)
- **Big Candle Body Fraction** - Alternative single-candle momentum threshold (0.5-0.95)
- **Min Zone Size %** - Minimum zone height as percentage of price (0.01-5.0%)
### BOS Configuration
- **Swing Length** - Lookback period for structure identification (3-20)
- **ATR Length** - Period for volatility measurement (1-50)
- **BOS Required Break** - ATR multiplier for valid structure break (0.1-3.0)
### Midline Options
- **None** - No midline displayed
- **Geometric** - Simple average of zone top/bottom
- **CenterVolume** - Volume-weighted center based on highest volume bar in window
### Risk Management
- **SL Buffer %** - Additional space beyond zone boundary (0-5%)
- **Take Profit RR** - Risk-reward ratio for target placement (0.5-10x)
### Entry Rules
- **Only 1st Retest per Zone** - Trade zones only once for higher quality
- **Min Bars Between Entries** - Prevent overtrading (1-20 bars)
## 📈 Recommended Settings
### Conservative (Lower Frequency, Higher Quality)
```
Momentum Body Fraction: 0.30
Min Momentum Candles: 2-3
BOS Required Break: 0.8-1.0
Min Zone Size: 0.15-0.20%
Only 1st Retest: Enabled
```
### Balanced (Default)
```
Momentum Body Fraction: 0.28
Min Momentum Candles: 2
BOS Required Break: 0.7
Min Zone Size: 0.12%
Only 1st Retest: Enabled
```
### Aggressive (Higher Frequency, More Signals)
```
Momentum Body Fraction: 0.20-0.25
Min Momentum Candles: 1-2
BOS Required Break: 0.4-0.5
Min Zone Size: 0.08-0.10%
Only 1st Retest: Disabled
```
## 🎨 Visual Elements
- **Red Boxes** - Supply zones (potential selling areas)
- **Green Boxes** - Demand zones (potential buying areas)
- **Dotted Midlines** - Center of each zone (fades when zone is used)
- **Debug Triangles** - Shows when zone creation conditions are met
- Red triangle down = Supply zone created
- Green triangle up = Demand zone created
## 📊 Best Practices
1. **Use on Higher Timeframes** - 1H, 4H, and Daily charts work best for institutional zones
2. **Combine with Trend** - Trade zones in direction of overall market structure
3. **Wait for Confirmation** - Don't enter immediately at zone touch; wait for rejection
4. **Adjust for Market Volatility** - Increase BOS multiplier in choppy markets
5. **Monitor Zone Quality** - Fresh zones typically have higher success rates
6. **Backtest Your Settings** - Optimize parameters for your specific market and timeframe
## ⚠️ Risk Disclaimer
This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Always:
- Use proper position sizing
- Set appropriate stop losses
- Test thoroughly before live trading
- Consider market conditions and overall trend
- Never risk more than you can afford to lose
## 🔍 Data Window Information
The strategy provides real-time metrics visible in the data window:
- Supply Zones Count
- Demand Zones Count
- ATR Value
- Momentum Signals (Up/Down)
- BOS Signals (Up/Down)
## 📝 Version History
**v1.0 - Enhanced Edition**
- Improved BOS detection logic
- Extended base candle search range
- Added comprehensive input validation
- Enhanced visual feedback system
- Robust array bounds checking
- Debug signals for troubleshooting
## 💡 Tips for Optimization
- **Trending Markets**: Lower momentum requirements, tighter BOS filters
- **Ranging Markets**: Increase zone size minimum, enable first retest only
- **Volatile Assets**: Increase ATR multiplier and SL buffer
- **Lower Timeframes**: Reduce swing length, increase min bars between entries
- **Higher Timeframes**: Increase swing length, relax momentum requirements
---
**Created with focus on institutional order flow, smart money concepts, and practical risk management.**
*Happy Trading! 📈*
PowerHouse SwiftEdge AI v2.10 StrategyOverview
The PowerHouse SwiftEdge AI v2.10 Strategy is a sophisticated trading system designed to identify high-probability trade setups in forex, stocks, and cryptocurrencies. By combining multi-timeframe trend analysis, momentum signals, volume confirmation, and smart money concepts (Change of Character and Break of Structure ), this strategy offers traders a robust tool to capitalize on market trends while minimizing false signals. The strategy’s unique “AI” component analyzes trends across multiple timeframes to provide a clear, actionable dashboard, making it accessible for both novice and experienced traders. The strategy is fully customizable, allowing users to tailor its filters to their trading style.
What It Does
This strategy generates Buy and Sell signals based on a confluence of technical indicators and smart money concepts. It uses:
Multi-Timeframe Trend Analysis: Confirms the market’s direction by analyzing trends on the 1-hour (60M), 4-hour (240M), and daily (D) timeframes.
Momentum Filter: Ensures trades align with strong price movements to avoid choppy markets.
Volume Filter: Validates signals with above-average volume to confirm market participation.
Breakout Filter: Requires price to break key levels for added confirmation.
Smart Money Signals (CHoCH/BOS): Identifies reversals (CHoCH) and trend continuations (BOS) based on pivot points.
AI Trend Dashboard: Summarizes trend strength, confidence, and predictions across timeframes, helping traders make informed decisions without needing to analyze complex data manually.
The strategy also plots dynamic support and resistance trendlines, take-profit (TP) levels, and “Get Ready” signals to alert users of potential setups before they fully develop. Trades are executed with predefined take-profit and stop-loss levels for disciplined risk management.
How It Works
The strategy integrates multiple components to create a cohesive trading system:
Multi-Timeframe Trend Analysis:
The strategy evaluates trends on three timeframes (1H, 4H, Daily) using Exponential Moving Averages (EMA) and Volume-Weighted Average Price (VWAP). A trend is considered bullish if the price is above both the EMA and VWAP, bearish if below, or neutral otherwise.
Signals are only generated when the trend on the user-selected higher timeframe aligns with the trade direction (e.g., Buy signals require a bullish higher timeframe trend). This reduces noise and ensures trades follow the broader market context.
Momentum Filter:
Measures the percentage price change between consecutive bars and compares it to a volatility-adjusted threshold (based on the Average True Range ). This ensures trades are taken only during significant price movements, filtering out low-momentum conditions.
Volume Filter (Optional):
Checks if the current volume exceeds a long-term average and shows positive short-term volume change. This confirms strong market participation, reducing the risk of false breakouts.
Breakout Filter (Optional):
Requires the price to break above (for Buy) or below (for Sell) recent highs/lows, ensuring the signal aligns with a structural shift in the market.
Smart Money Concepts (CHoCH/BOS):
Change of Character (CHoCH): Detects potential reversals when the price crosses under a recent pivot high (for Sell) or over a recent pivot low (for Buy) with a bearish or bullish candle, respectively.
Break of Structure (BOS): Confirms trend continuations when the price breaks below a recent pivot low (for Sell) or above a recent pivot high (for Buy) with strong momentum.
These signals are plotted as horizontal lines with labels, making it easy to visualize key levels.
AI Trend Dashboard:
Combines trend direction, momentum, and volatility (ATR) across timeframes to calculate a trend score. Scores above 0.5 indicate an “Up” trend, below -0.5 indicate a “Down” trend, and otherwise “Neutral.”
Displays a table summarizing trend strength (as a percentage), AI confidence (based on trend alignment), and Cumulative Volume Delta (CVD) for market context.
A second table (optional) shows trend predictions for 1H, 4H, and Daily timeframes, helping traders anticipate future market direction.
Dynamic Trendlines:
Plots support and resistance lines based on recent swing lows and highs within user-defined periods (shortTrendPeriod, longTrendPeriod). These lines adapt to market conditions and are colored based on trend strength.
Why This Combination?
The PowerHouse SwiftEdge AI v2.10 Strategy is original because it seamlessly integrates traditional technical analysis (EMA, VWAP, ATR, volume) with smart money concepts (CHoCH, BOS) and a proprietary AI-driven trend analysis. Unlike standalone indicators, this strategy:
Reduces False Signals: By requiring confluence across trend, momentum, volume, and breakout filters, it minimizes trades in choppy or low-conviction markets.
Adapts to Market Context: The ATR-based momentum threshold adjusts dynamically to volatility, ensuring signals remain relevant in both trending and ranging markets.
Simplifies Decision-Making: The AI dashboard distills complex multi-timeframe data into a user-friendly table, eliminating the need for manual analysis.
Leverages Smart Money: CHoCH and BOS signals capture institutional price action patterns, giving traders an edge in identifying reversals and continuations.
The combination of these components creates a balanced system that aligns short-term trade entries with longer-term market trends, offering a unique blend of precision, adaptability, and clarity.
How to Use
Add to Chart:
Apply the strategy to your TradingView chart on a liquid symbol (e.g., EURUSD, BTCUSD, AAPL) with a timeframe of 60 minutes or lower (e.g., 15M, 60M).
Configure Inputs:
Pivot Length: Adjust the number of bars (default: 5) to detect pivot highs/lows for CHoCH/BOS signals. Higher values reduce noise but may delay signals.
Momentum Threshold: Set the base percentage (default: 0.01%) for momentum confirmation. Increase for stricter signals.
Take Profit/Stop Loss: Define TP and SL in points (default: 10 each) for risk management.
Higher/Lower Timeframe: Choose timeframes (60M, 240M, D) for trend filtering. Ensure the chart timeframe is lower than or equal to the higher timeframe.
Filters: Enable/disable momentum, volume, or breakout filters to suit your trading style.
Trend Periods: Set shortTrendPeriod (default: 30) and longTrendPeriod (default: 100) for trendline plotting. Keep below 2000 to avoid buffer errors.
AI Dashboard: Toggle Enable AI Market Analysis to show/hide the prediction table and adjust its position.
Interpret Signals:
Buy/Sell Labels: Green "Buy" or red "Sell" labels indicate trade entries with predefined TP/SL levels plotted.
Get Ready Signals: Yellow "Get Ready BUY" or orange "Get Ready SELL" labels warn of potential setups.
CHoCH/BOS Lines: Aqua (CHoCH Sell), lime (CHoCH Buy), fuchsia (BOS Sell), or teal (BOS Buy) lines mark key levels.
Trendlines: Green/lime (support) or fuchsia/purple (resistance) dashed lines show dynamic support/resistance.
AI Dashboard: Check the top-right table for trend strength, confidence, and CVD. The optional bottom table shows trend predictions (Up, Down, Neutral).
Backtest and Trade:
Use TradingView’s Strategy Tester to evaluate performance. Adjust TP/SL and filters based on results.
Trade manually based on signals or automate with TradingView alerts (set alerts for Buy/Sell labels).
Originality and Value
The PowerHouse SwiftEdge AI v2.10 Strategy stands out by combining multi-timeframe analysis, smart money concepts, and an AI-driven dashboard into a single, user-friendly system. Its adaptive momentum threshold, robust filtering, and clear visualizations empower traders to make confident decisions without needing advanced technical knowledge. Whether you’re a day trader or swing trader, this strategy provides a versatile, data-driven approach to navigating dynamic markets.
Important Notes:
Risk Management: Always use appropriate position sizing and risk management, as the strategy’s TP/SL levels are customizable.
Symbol Compatibility: Test on liquid symbols with sufficient historical data (at least 2000 bars) to avoid buffer errors.
Performance: Backtest thoroughly to optimize settings for your market and timeframe.
Zendog V2 backtest DCA bot 3commasHi everyone,
After a few iterations and additional implemented features this version of the Backtester is now open source.
The Strategy is a Backtester for 3commas DCA bots. The main usage scenario is to plugin your external indicator, and backtest it using different DCA settings.
Before using this script please make sure you read these explanations and make sure you understand how it works.
Features:
- Because of Tradingview limitations on how orders are grouped into Trades, this Strategy statistics are calculated by the script, so please ignore the Strategy Tester statistics completely
Statistics Table explained:
- Status: either all deals are closed or there is a deal still running, in which case additional info
is provided below, as when the deal started, current PnL, current SO
- Finished deals: Total number of closed deals both Winning and Losing.
A deal is comprised as the Base Order (BO) + all Safety Orders (SO) related to that deal, so this number
will be different than the Strategy Tester List of Trades
- Winning Deals: Deal ended in profit
- Losing deals: Deals ended with loss due to Stop Loss. In the future I might add a Deal Stop condition to
the script, so that will count towards this number as well.
- Total days ( Max / Avg days in Deal ):
Total Days in the Backtest given by either Tradingview limitation on the number of candles or by the
config of the script regarding "Limit Date Range".
Max Days spent in a deal + which period this happened.
Avg days spent in a deal.
- Required capital: This is the total capital required to run the Backtester and it is automatically calculated by
the script taking into consideration BO size, SO size, SO volume scale. This should be the same as 3commas.
This number overwrites strategy.initial_capital and is used to calculate Profit and other stats, so you don't need
to update strategy.initial_capital every time you change BO/SO settings
- Profit after commission
- Buy and Hold return: The PnL that could have been obtained by buying at the close of the first candle of the
backtester and selling at the last.
- Covered deviation: The % of price move from initial BO order covered by SO settings
- Max Deviation: Biggest market % price move vs BO price, in the other direction (for long
is down, for short it is up)
- Max Drawdown: Biggest market % price move vs Avg price of the whole Trade (BO + any SO), in the other
direction (for long price goes down, for short it goes up)
This is calculated for the whole Trade so it is different than List of Trades
- Max / Avg bars in deal
- Total volume / Commission calculated by the strategy. For correct commission please set Commission in the
Inputs Tab and you may ignore Properties Tab
- Close stats for deals: This is a list of how many Trades were closed at each step, including Stop Loss (if
configured), together with covered deviation for that step, the number of deals, and the percentage of this
number from all the deals
TODO: Might add deal avg value for each step
- Settings Table that can be enabled / disabled just to have an overview of your configs on the chart, this is a
drawn on bottom left
- Steps Table similar to 3commas, this is also drawn on bottom left, so please disable Settings table if you want
to see this one
TODO: Might add extra stats here
- Deal start condition: built in RSI-7 or plugin any external indicator and compare with any value the indicator plots
(main purpose of this strategy is to connect your own studies, so using external indicator is recommended)
- Base order and safety orders configs similar to 3commas (order size, percent deviation, safety orders,
percent scale and volume scale)
- Long and Short
- Stop Loss
- Support for Take profit from base order or from Total volume of the deal
- Configs help (besides self explanatory):
- Chart theme: Adjust according to the theme you run on. There is no way to detect theme at the moment.
This adjust different colors
- Deal Start Type: Either a builtin RSI7 or "External indicator"
- Indicator Source an value: If using External Indicator then select source, comparison and value.
For example you could start a deal when Volume is greater than xxxx, or code a custom indicator that plots
different values based on your conditions and test those values
- Visuals / Decimals for display: Adjust according to your symbol
- BO Entry Price for steps table: This is the BO start deal price used to calculate the steps in the table
SmartMoneyConcept ProFlow StrategySmartMoneyConcept ProFlow is a complete SMC-based algo built for trending markets and clean volatility phases – especially on crypto pairs like BTC, ETH and perpetual futures.
It combines:
• Smart Money swing structure (BOS / CHoCH)
• Dynamic Support & Resistance levels
• Order Block–style gap detection
• Volatility normalization (ATR / Range / BBWidth)
• SuperTrend trend filter
• ATR & Volume-based exits, TP lock and session control
The goal: fewer random trades, more focused entries when structure + volatility + trend are in sync.
1. Core Idea
Smart Structure Levels (S/R)
– The strategy builds dynamic support/resistance using swing highs/lows.
– Breakouts above resistance or below support, with enough volatility (filter), become primary trade signals.
BOS / CHoCH Engine
– Tracks Break of Structure (BOS) and Change of Character (CHoCH).
– BOS up/down help define the current trend bias.
– CHoCH highlights potential reversals after a confirmed BOS in the opposite direction.
Order Block Gap Logic
– Detects displacement candles with gaps (based on ATR) to approximate OB-style “impulsive moves”.
– Bullish gaps can add confluence for long entries, bearish gaps for shorts.
Volatility-Aware Entries
– Uses normalized volatility (via ATR, Range or BBWidth).
– Filters out breakouts in dead, low-vol environments and focuses on moves with real expansion.
2. Trend & Risk Management Stack
SuperTrend Filter
– Optional “Only With SuperTrend Direction” to restrict entries to the current ST trend.
– ST flips can also force exits if you want to exit as soon as the main trend changes.
ATR-Based Stops & Trails
– ATR distance check to avoid ultra-tight stops that get chopped instantly.
– Three modes:
• StopOnly – classic fixed ATR stop.
• TrailOnly – trailing ATR-style stop.
• StopAndTrail – initial fixed stop that later trails with price.
Volume-Based Exits (Optional)
– Exit on extremely low volume (move losing participation).
– Or on opposite volume spikes (strong counter-pressure against your position).
– Or use Both for a more active volume management.
TP Lock Logic
– When unrealized profit reaches a chosen value, the position is closed and a “lock” can be applied.
– Use this lock to:
• block same-direction re-entries for that side, or
• allow them again depending on your preference.
3. Anti-Churn & Session Control
Anti-Churn Controls
– Minimum bars between entries.
– Cooldown after an ATR exit.
– Limit of max entries per bar.
Session Filter
– Restrict trading to a specific hourly window (e.g. main market session).
– Option to force close positions outside your active session.
– Handy for intraday traders who don’t want overnight or low-liquidity exposure.
4. SmartMoney Preset Modes
Preset Mode:
• EtherFlux – more flexible, for general breakout & volatility trading.
• SmartMoney – SMC-focused preset:
– Adjusted length, volatility filter and ATR settings.
– Option to disable exits from the strategy side (for manual risk control).
Switching presets automatically tunes multiple internal parameters so you don’t have to micromanage every input each time.
5. Visual Layer
This script has a complete visual suite to help you “read the tape”:
– Bar Colors by position and SuperTrend bias.
– Support / Resistance dots and lines (stepline style).
– Order Block markers (bullish / bearish gap labels).
– BOS / CHoCH labels to track structure shifts in real-time.
– Liquidation Zones (visual only)
• Approximate long and short liquidation areas based on assumed leverage.
• Shaded zones on the chart for quick liquidity map.
– Status Labels
• Session status (ACTIVE / OFF / DISABLED).
• Current position (LONG / SHORT / FLAT).
• TP Lock status (longs locked / shorts locked / no lock).
All visuals are designed for dark charts but also work on light themes with minor tweaks.
6. Quick Input Guide
• Levels Period & Volatility Filter – main structure sensitivity and breakout quality.
• Volatility Method – ATR / Range / BBWidth normalization for the vol filter.
• ATR Stop & Management – core risk rules: ATR multiplier, stop/trail mode, min ATR distance.
• SuperTrend Settings – trend bias and ST-flip exits.
• SmartMoney Preset – quick switch between EtherFlux and SmartMoney tuning.
• Volume Exits – low volume / opposite spike / both.
• Session Filter – hour-based trading window + optional forced flat outside session.
• Follow-Signal Mode – flip from long→short or short→long when signal reverses (signal-based rotation).
• TP Lock – secure profits at a fixed amount and optionally block same-direction re-entries.
• Liq Zones – visual only, for liquidity map (no direct trade logic).
How to Use (My Suggestion)
Start on 15m–4H charts for liquid pairs (BTC, ETH, majors).
Choose your preset:
– EtherFlux for more general breakout + vol trading.
– SmartMoney if you want stricter SMC behaviour.
Turn on SuperTrend + ATR stops for cleaner risk management.
Forward-test in replay / paper trading before using real capital.
Use the visual BOS/CHoCH + Liq Zones as context , not as blind signals.
Important
This is a backtest & research tool . It is not financial advice and does not guarantee profits. Always combine it with your own risk management, position sizing, and forward-testing before going live. Trading leveraged products and crypto can result in partial or full loss of capital.
SMC Trend Filter Strategy (EMA50/EMA200 + FVG)Overview
This strategy implements a multi-timeframe Smart Money Concept (SMC) trading system designed for intraday and swing trading.
It combines a Daily trend filter, Break of Structure (BOS) detection, Order Block (OB) zones, Fair Value Gap (FVG) confirmation, and an ATR-based trailing stop system to achieve structured and rule-based entries.
The strategy is fully automated for backtesting and allows users to evaluate SMC concepts without repainting or discretionary interpretation.
- Core Components
1. Higher-Timeframe Trend Filter (Daily EMA50/EMA200)
The strategy retrieves D1 data and determines market direction using EMA50 and EMA200:
Uptrend → EMA50 > EMA200
Downtrend → EMA50 < EMA200
Trades are only taken in the direction of the Daily trend to avoid counter-trend setups.
2. Market Structure & Break of Structure (BOS)
The strategy identifies swing highs/lows and detects when price breaks beyond them:
Bullish BOS: price closes above previous swing high
Bearish BOS: price closes below previous swing low
This forms the foundation of SMC market structure recognition.
3. Order Block Zone (OB)
Upon detecting a BOS, the strategy marks the previous candle as a potential Order Block:
For bullish BOS → OB = previous candle’s high/low
For bearish BOS → OB = previous candle’s high/low
The OB zone is visualized using a semi-transparent box extended forward
Qullamaggie [Modified] | FractalystWhat's the purpose of this strategy?
The strategy aims to identify high-probability breakout setups in trending markets, inspired by Kristjan "Qullamaggie" Kullamägi’s approach.
It focuses on capturing explosive price moves after periods of consolidation, using technical criteria like moving averages, breakouts, trailing stop-loss and momentum confirmation.
Ideal for swing traders seeking to ride strong trends while managing risk.
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How does the strategy work?
The strategy follows a systematic process to capture high-momentum breakouts:
Pre-Breakout Criteria:
Prior Price Surge: Identifies stocks that have rallied 30-100%+ in recent month(s), signaling strong underlying momentum (per Qullamaggie’s volatility expansion principles).
Consolidation Phase: Looks for a tightening price range (e.g., flag, pennant, or tight base), indicating a potential "coiling" before continuation.
Trend Confirmation: Uses moving averages (e.g., 20/50/200 EMA) to ensure the stock is trading above key averages on the daily chart, confirming an uptrend.
Price Break: Enters when price clears the consolidation high with conviction.
Risk Management:
Initial Stop Loss: Placed below the consolidation low or a recent swing point to limit downside.
Break-Even Adjustment: Moves stop loss to breakeven once the trade reaches 1.5x risk-to-reward (RR), securing a "free trade" while letting winners run.
Trailing Stop (Unique Edge):
Market Structure Trailing: Instead of trailing via moving averages, the stop is dynamically adjusted using structural invalidation level. This adapts to price action, allowing the trade to stay open during volatile retracements while locking in gains as new structure forms.
Why This Matters: Most strategies use rigid trailing stops (e.g., below the 10EMA), which often exit prematurely in choppy markets. By trailing based on structure, this strategy avoids "noise" and captures larger trends, directly boosting overall returns.
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What markets or timeframes is this suited for?
This is a long-only strategy designed for trending markets, and it performs best in:
Markets: Stocks (especially high-growth, liquid equities), cryptocurrencies (major pairs with strong volatility), commodities (e.g., oil, gold), and futures (index/commodity futures).
Timeframes: Primarily daily charts for swing trades (1-30 day holds), though weekly charts can help confirm broader trends.
Key Advantage: The TradingView script allows instant backtesting with adjustable parameters
You can:
- Test historical performance across multiple markets to identify which assets align best with the strategy.
- Optimize settings (e.g., trailing stop sensitivity, moving averages etc.) to match a market’s volatility profile.
Build a diversified portfolio by filtering for markets that show consistent profitability in backtests.
For example, you might discover cryptos require tighter trailing stops due to volatility, while stocks thrive with wider structural stops. The script automates this analysis, letting you to trade confidently.
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What indicators or tools does the strategy use?
The strategy combines customizable technical tools with strict anti-lookahead safeguards:
Core Indicators:
Moving Averages: Adjustable periods (e.g., 20/50/200 EMA or SMA) and timeframes (daily/weekly) to confirm trend alignment. Users can test combinations (e.g., 10EMA vs. 20EMA) to optimize for specific markets.
Breakout Parameters:
Consolidation Length: Adjustable window to define the "tightness" of the pre-breakout pattern.
Entry Models: Flexible entry logics (Breakouts and fractals)
Anti-Lookahead Design:
All calculations (e.g., moving averages, consolidation ranges, volume averages) use only closed/confirmed data available at the time of the signal.
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How do I manage risk with this strategy?
The strategy prioritizes customizable risk controls to align with your trading style and account size:
User-Defined Risk Inputs:
Risk Per Trade: Set a % of Equity (e.g., 1-2%) to determine position size. The strategy auto-calculates shares/contracts to match your selected risk per trade.
Flexibility: Choose between fixed risk or equity-based scaling.
The script adjusts position sizing dynamically based on your selection.
Pyramiding Feature:
Customizable Entries: Adjust the number of pyramiding trades allowed (e.g., 1-3 additional positions) in the strategy settings. Each new entry is triggered only if the prior trade hits its 1.5x RR target and the trend remains intact.
Risk-Scaled Additions: New positions use profits from prior trades, compounding gains without increasing initial risk.
Risk-Free Trade Mechanic:
Once a trade reaches 1.5x RR, the stop loss is moved to breakeven, eliminating downside risk.
The strategy then opens a new position (if pyramiding is enabled) using a portion of the locked-in profit. This "snowballs" winners while keeping total capital exposure stable.
Impact on Net Profit & Drawdown:
Net Profit Boost: Pyramiding lets you ride multi-leg trends aggressively. For example, a 100% runner could generate 2-3x more profit vs. a single-entry approach.
Controlled Drawdowns: Since new positions are funded by profits (not initial capital), max drawdown stays anchored to your original risk per trade (e.g., 1-2% of account). Even if later entries fail, the breakeven stop on prior trades protects overall equity.
Why This Works: Most strategies either over-leverage (increasing drawdowns) or exit too early. By recycling profits into new positions only after securing risk-free capital, this approach mimics hedge fund "scaling in" tactics while staying retail-trader friendly.
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How does the strategy identify market structure for its trailing stoploss?
The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
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What are the underlying calculations?
The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
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What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
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What type of break-even method is used in this strategy? What are the underlying calculations?
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
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What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What Makes This Strategy Unique?
This strategy combines flexibility, smart risk management, and momentum focus in a way that’s rare and practical:
1. Adapts to Any Market Rhythm
Works on daily, weekly, or intraday charts without code changes.
Uses two entry types: classic breakouts (like trending stocks) or fractal patterns (to avoid false starts).
2. Smarter Stop-Loss System
No rigid rules: Stops adjust based on price structure (e.g., new “higher lows”), not fixed percentages.
Avoids whipsaws: Tightens stops only when the trend strengthens, not in choppy markets.
3. Safe Profit-Boosting Pyramiding
Adds new positions only after prior trades are risk-free (stops moved above breakeven).
Scales up using locked-in profits, not new capital, to grow gains safely.
4. Built-In Momentum Check
Tracks 1/3/6-month price growth to spotlight stocks with strong, lasting momentum.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Dollar Cost Averaging (DCA) | FractalystWhat's the purpose of this strategy?
The purpose of dollar cost averaging (DCA) is to grow investments over time using a disciplined, methodical approach used by many top institutions like MicroStrategy and other institutions.
Here's how it functions:
Dollar Cost Averaging (DCA): This technique involves investing a set amount of money regularly, regardless of market conditions. It helps to mitigate the risk of investing a large sum at a peak price by spreading out your investment, thus potentially lowering your average cost per share over time.
Regular Contributions: By adding money to your investments on a pre-determined frequency and dollar amount defined by the user, you take advantage of compounding. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
Technical Analysis: The strategy employs a market trend ratio to gauge market sentiment. It calculates the ratio of bullish vs bearish breakouts across various timeframes, assigning this ratio a percentage-based score to determine the directional bias. Once this score exceeds a user-selected percentage, the strategy looks to take buy entries, signaling a favorable time for investment based on current market trends.
Fundamental Analysis: This aspect looks at the health of the economy and companies within it to determine bullish market conditions. Specifically, we consider:
Specifically, it considers:
Interest Rate: High interest rates can affect borrowing costs, potentially slowing down economic growth or making stocks less attractive compared to fixed income.
Inflation Rate: Inflation erodes purchasing power, but moderate inflation can be a sign of a healthy economy. We look for investments that might benefit from or withstand inflation.
GDP Rate: GDP growth indicates the overall health of the economy; we aim to invest in sectors poised to grow with the economy.
Unemployment Rate: Lower unemployment typically signals consumer confidence and spending power, which can boost certain sectors.
By integrating these elements, the strategy aims to:
Reduce Investment Volatility: By spreading out your investments, you're less impacted by short-term market swings.
Enhance Growth Potential: Using both technical and fundamental filters helps in choosing investments that are more likely to appreciate over time.
Manage Risk: The strategy aims to balance the risk of market timing by investing consistently and choosing assets wisely based on both economic data and market conditions.
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What are Regular Contributions in this strategy?
Regular Contributions involve adding money to your investments on a pre-determined frequency and dollar amount defined by the user. The script will remind you to contribute based on your chosen schedule, which can be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach ensures that your returns can earn their own returns, much like interest on savings but potentially at a higher rate.
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How do regular contributions enhance compounding and reduce timing risk?
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
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How does the strategy integrate technical and fundamental analysis for investors?
A: The strategy combines technical and fundamental analysis in the following manner:
Technical Analysis: It uses a market trend ratio to determine the directional bias by calculating the ratio of bullish vs bearish breakouts. Once this ratio exceeds a user-selected percentage threshold, the strategy signals to take buy entries, optimizing the timing within the given timeframe(s).
Fundamental Analysis: This aspect assesses the broader economic environment to identify sectors or assets that are likely to benefit from current economic conditions. By understanding these fundamentals, the strategy ensures investments are made in assets with strong growth potential.
This integration allows the strategy to select investments that are both technically favorable for entry and fundamentally sound, providing a comprehensive approach to investment decisions in the crypto, stock, and commodities markets.
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How does the strategy identify market structure? What are the underlying calculations?
Q: How does the strategy identify market structure?
A: The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
What are the underlying calculations for identifying market structure?
A: The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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How does the script calculate trend score? What are the underlying calculations?
Market Trend Ratio: The script calculates the ratio of bullish to bearish breakouts. This involves:
Counting Bullish Breakouts: A bullish breakout is counted when the price breaks above a recent swing high (as identified in the strategy's market structure analysis).
Counting Bearish Breakouts: A bearish breakout is counted when the price breaks below a recent swing low.
Percentage-Based Score: This ratio is then converted into a percentage-based score:
For example, if there are 10 bullish breakouts and 5 bearish breakouts in a given timeframe, the ratio would be 10:5 or 2:1. This could be translated into a score where 66.67% (10/(10+5) * 100) represents the bullish trend strength.
The score might be calculated as (Number of Bullish Breakouts / Total Breakouts) * 100.
User-Defined Threshold: The strategy uses this score to determine when to take buy entries. If the trend score exceeds a user-defined percentage threshold, it indicates a strong enough bullish trend to justify a buy entry. For instance, if the user sets the threshold at 60%, the script would look for a buy entry when the trend score is above this level.
Timeframe Consideration: The calculations are performed across the timeframes specified by the user, ensuring the trend score reflects the market's behavior over different periods, which could be daily, weekly, or any other relevant timeframe.
This method provides a quantitative measure of market trend strength, helping to make informed decisions based on the balance between bullish and bearish market movements.
What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
For TP
- You can choose to set a take profit level at which your position gets fully closed.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What makes this strategy original?
Incorporation of Fundamental Analysis:
This strategy integrates fundamental analysis by considering key economic indicators such as interest rates, inflation, GDP growth, and unemployment rates. These fundamentals help in assessing the broader economic health, which in turn influences sector performance and market trends. By understanding these economic conditions, the strategy can identify sectors or assets that are likely to thrive, ensuring investments are made in environments conducive to growth. This approach allows for a more informed investment decision, aligning technical entries with fundamentally strong market conditions, thus potentially enhancing the strategy's effectiveness over time.
Technical Analysis Without Classical Methods:
The strategy's technical analysis diverges from traditional methods like moving averages by focusing on market structure through a trend score system.
Instead of using lagging indicators, it employs a real-time analysis of market trends by calculating the ratio of bullish to bearish breakouts. This provides several benefits:
Immediate Market Sentiment: The trend score system reacts more dynamically to current market conditions, offering insights into the market's immediate sentiment rather than historical trends, which can often lag behind real-time changes.
Reduced Overfitting: By not relying on moving averages or similar classical indicators, the strategy avoids the common pitfall of overfitting to historical data, which can lead to poor performance in new market conditions. The trend score provides a fresh perspective on market direction, potentially leading to more robust trading signals.
Clear Entry Signals: With the trend score, entry decisions are based on a clear percentage threshold, making the strategy's decision-making process straightforward and less subjective than interpreting moving average crossovers or similar signals.
Regular Contributions and Reminders:
The strategy encourages regular investments through a system of predefined frequency and amount, which could be weekly, bi-weekly, monthly, quarterly, or yearly. This systematic approach:
Enhances Compounding: Regular contributions leverage the power of compounding, where returns on investments can generate their own returns, potentially leading to exponential growth over time.
Reduces Timing Risk: By investing regularly, the strategy minimizes the risk associated with trying to time the market, spreading out the investment cost over time and potentially reducing the impact of volatility.
Automated Reminders: The script reminds users to make contributions based on their chosen schedule, ensuring consistency and discipline in investment practices, which is crucial for long-term success.
Long-Term Wealth Building:
Focused on long-term wealth accumulation, this strategy:
Promotes Patience and Discipline: By emphasizing regular contributions and a disciplined approach to both entry and risk management, it aligns with the principles of long-term investing, discouraging impulsive decisions based on short-term market fluctuations.
Diversification Across Asset Classes: Operating across crypto, stocks, and commodities, the strategy provides diversification, which is a key component of long-term wealth building, reducing risk through varied exposure.
Growth Over Time: The strategy's design to work with the market's natural growth cycles, supported by fundamental analysis, aims for sustainable growth rather than quick profits, aligning with the goals of investors looking to build wealth over decades.
This comprehensive approach, combining fundamental insights, innovative technical analysis, disciplined investment habits, and a focus on long-term growth, offers a unique and potentially effective pathway for investors seeking to build wealth steadily over time.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
BigBeluga - BacktestingThe Backtesting System (SMC) is a strategy builder designed around concepts of Smart Money.
What makes this indicator unique is that users can build a wide variety of strategies thanks to the external source conditions and the built-in one that are coded around concepts of smart money.
🔶 FEATURES
🔹 Step Algorithm
Crafting Your Strategy:
You can add multiple steps to your strategy, using both internal and external (custom) conditions.
Evaluating Your Conditions:
The system evaluates your conditions sequentially.
Only after the previous step becomes true will the next one be evaluated.
This ensures your strategy only triggers when all specified conditions are met.
Executing Your Strategy:
Once all steps in your strategy are true, the backtester automatically opens a market order.
You can also configure exit conditions within the strategy builder to manage your positions effectively.
🔹 External and Internal build-in conditions
Users can choose to use external or internal conditions or just one of the two categories.
Build-in conditions:
CHoCH or BOS
CHoCH or BOS Sweep
CHoCH
BOS
CHoCH Sweep
BOS Sweep
OB Mitigated
Price Inside OB
FVG Mitigated
Raid Found
Price Inside FVG
SFP Created
Liquidity Print
Sweep Area
Breakdown of each of the options:
CHoCH: Change of Character (not Charter) is a change from bullish to bearish market or vice versa.
BOS: Break of Structure is a continuation of the current trend.
CHoCH or BOS Sweep: Liquidity taken out from the market within the structure.
OB Mitigated: An order block mitigated.
FVG Mitigated: An imbalance mitigated.
Raid Found: Liquidity taken out from an imbalance.
SFP Created: A Swing Failure Pattern detected.
Liquidity Print: A huge chunk of liquidity taken out from the market.
Sweep Area: A level regained from the structure.
Price inside OB/FVG: Price inside an order block or an imbalance.
External inputs can be anything that is plotted on the chart that has valid entry points, such as an RSI or a simple Supertrend.
Equal
Greather Than
Less Than
Crossing Over
Crossing Under
Crossing
🔹 Direction
Users can change the direction of each condition to either Bullish or Bearish. This can be useful if users want to long the market on a bearish condition or vice versa.
🔹 Build-in Stop-Loss and Take-Profit features
Tailoring Your Exits:
Similar to entry creation, the backtesting system allows you to build multi-step exit strategies.
Each step can utilize internal and external (custom) conditions.
This flexibility allows you to personalize your exit strategy based on your risk tolerance and trading goals.
Stop-Loss and Take-Profit Options:
The backtesting system offers various options for setting stop-loss and take-profit levels.
You can choose from:
Dynamic levels: These levels automatically adjust based on market movements, helping you manage risk and secure profits.
Specific price levels: You can set fixed stop-loss and take-profit levels based on your comfort level and analysis.
Price - Set x point to a specific price
Currency - Set x point away from tot Currency points
Ticks - Set x point away from tot ticks
Percent - Set x point away from a fixed %
ATR - Set x point away using the Averge True Range (200 bars)
Trailing Stop (Only for stop-loss order)
🔶 USAGE
Users can create a variety of strategies using this script, limited only by their imagination.
Long entry : Bullish CHoCH after price is inside a bullish order block
Short entry : Bearish CHoCH after price is inside a bearish order block
Stop-Loss : Trailing Stop set away from price by 0.2%
Example below using external conditions
Long entry : Bullish Liquidity Prints after bullish CHoCH
Short entry : Bearish Liquidity Prints after Bearish CHoCH
Long Exit : RSI Crossing over 70 line
Short Exit : RSI Crossing over 30 line
Stop-Loss : Trailing Stop set away from price by 0.3%
🔶 PROPERTIES
Users will need to adjust the property tabs according to their individual balance to achieve realistic results.
An important aspect to note is that past performance does not guarantee future results. This principle should always be kept in mind.
🔶 HOW TO ACCESS
You can see the Author Instructions to get access.
Paid script
ChronoPulse MS-MACD Resonance StrategyChronoPulse MS-MACD Resonance Strategy
A systematic trading strategy that combines higher-timeframe market structure analysis with dual MACD momentum confirmation, ATR-based risk management, and real-time quality assurance monitoring.
Core Principles
The strategy operates on the principle of multi-timeframe confluence, requiring agreement between:
Market structure breaks (CHOCH/BOS) on a higher timeframe
Dual MACD momentum confirmation (classic and crypto-tuned profiles)
Trend alignment via directional EMAs
Volatility and volume filters
Quality score composite threshold
Strategy Components
Market Structure Engine : Detects Break of Structure (BOS) and Change of Character (CHOCH) events using confirmed pivots on a configurable higher timeframe. Default structure timeframe is 240 minutes (4H).
Dual MACD Fusion : Requires agreement between two MACD configurations:
Classic MACD: 12/26/9 (default)
Fusion MACD: 8/21/5 (default, optimized for crypto volatility)
Both must agree on direction before trade execution. This can be disabled to use single MACD confirmation.
Trend Alignment : Uses two EMAs for directional bias:
Directional EMA: 55 periods (default)
Execution Trend Guide: 34 periods (default)
Both must align with trade direction.
ATR Risk Management : All risk parameters are expressed in ATR multiples:
Stop Loss: 1.5 × ATR (default)
Take Profit: 3.0 × ATR (default)
Trail Activation: 1.0 × ATR profit required (default)
Trail Distance: 1.5 × ATR behind price (default)
Volume Surge Filter : Optional gate requiring current volume to exceed a multiple of the volume SMA. Default threshold is 1.4× the 20-period volume SMA.
Quality Score Gate : Composite score (0-1) combining:
Structure alignment (0.0-1.0)
Momentum strength (0.0-1.0)
Trend alignment (0.0-1.0)
ATR volatility score (0.0-1.0)
Volume intensity (0.0-1.0)
Default threshold: 0.62. Trades only execute when quality score exceeds this threshold.
Execution Discipline : Trade budgeting system:
Maximum trades per session: 6 (default)
Cooldown bars between entries: 5 (default)
Quality Assurance Console : Real-time monitoring panel displaying:
Structure status (pass/fail)
Momentum confirmation (pass/fail)
Volatility readiness (pass/fail)
Quality score (pass/fail)
Discipline compliance (pass/fail)
Performance metrics (win rate, profit factor)
Net PnL
Certification requires: Win Rate ≥ 40%, Profit Factor ≥ 1.4, Minimum 25 closed trades, and positive net profit.
Integrity Suite : Optional validation panel that audits:
Configuration sanity checks
ATR data readiness
EMA hierarchy validity
Performance realism checks
Strategy Settings
strategy(
title="ChronoPulse MS-MACD Resonance Strategy",
shorttitle="ChronPulse",
overlay=true,
max_labels_count=500,
max_lines_count=500,
initial_capital=100000,
currency=currency.USD,
pyramiding=0,
commission_type=strategy.commission.percent,
commission_value=0.015,
slippage=2,
default_qty_type=strategy.percent_of_equity,
default_qty_value=2.0,
calc_on_order_fills=true,
calc_on_every_tick=true,
process_orders_on_close=true
)
Key Input Parameters
Structure Timeframe : 240 (4H) - Higher timeframe for structure analysis
Structure Pivot Left/Right : 3/3 - Pivot confirmation periods
Structure Break Buffer : 0.15% - Buffer for structure break confirmation
MACD Fast/Slow/Signal : 12/26/9 - Classic MACD parameters
Fusion MACD Fast/Slow/Signal : 8/21/5 - Crypto-tuned MACD parameters
Directional EMA Length : 55 - Primary trend filter
Execution Trend Guide : 34 - Secondary trend filter
ATR Length : 14 - ATR calculation period
ATR Stop Multiplier : 1.5 - Stop loss in ATR units
ATR Target Multiplier : 3.0 - Take profit in ATR units
Trail Activation : 1.0 ATR - Profit required before trailing
Trail Distance : 1.5 ATR - Distance behind price
Volume Threshold : 1.4× - Volume surge multiplier
Quality Threshold : 0.62 - Minimum quality score (0-1)
Max Trades Per Session : 6 - Daily trade limit
Cooldown Bars : 5 - Bars between entries
Win-Rate Target : 40% - Minimum for QA certification
Profit Factor Target : 1.4 - Minimum for QA certification
Minimum Trades for QA : 25 - Required closed trades
Signal Generation Logic
A trade signal is generated when ALL of the following conditions are met:
Higher timeframe structure shows bullish (CHOCH/BOS) or bearish structure break
Both MACD profiles agree on direction (if fusion enabled)
Price is above both EMAs for longs (below for shorts)
ATR data is ready and above minimum threshold
Volume exceeds threshold × SMA (if volume gate enabled)
Quality score ≥ quality threshold
Trade budget available (under max trades per day)
Cooldown period satisfied
Risk Management
Stop loss and take profit are set immediately on entry
Trailing stop activates after 1.0 ATR of profit
Trailing stop maintains 1.5 ATR distance behind highest profit point
Position sizing uses 2% of equity per trade (default)
No pyramiding (single position per direction)
Limitations and Considerations
The strategy requires sufficient historical data for higher timeframe structure analysis
Quality gate may filter out many potential trades, reducing trade frequency
Performance metrics are based on historical backtesting and do not guarantee future results
Commission and slippage assumptions (0.015% + 2 ticks) may vary by broker
The strategy is optimized for trending markets with clear structure breaks
Choppy or ranging markets may produce false signals
Crypto markets may require different parameter tuning than traditional assets
Optimization Notes
The strategy includes several parameters that can be tuned for different market conditions:
Quality Threshold : Lower values (0.50-0.60) allow more trades but may reduce average quality. Higher values (0.70+) are more selective but may miss opportunities.
Structure Timeframe : Use 240 (4H) for intraday trading, Daily for swing trading, Weekly for position trading
Volume Gate : Disable for low-liquidity pairs or when volume data is unreliable
Dual MACD Fusion : Disable for mean-reverting markets where single MACD may be more responsive
Trade Discipline : Adjust max trades and cooldown based on your risk tolerance and market volatility
Non-Repainting Guarantee
All higher timeframe data requests use lookahead=barmerge.lookahead_off to prevent repainting. Pivot detection waits for full confirmation before registering structure breaks. All visual elements (tables, labels) update only on closed bars.
Alerts
Three alert conditions are available:
ChronoPulse Long Setup : Fires when all long entry conditions are met
ChronoPulse Short Setup : Fires when all short entry conditions are met
ChronoPulse QA Certification : Fires when Quality Assurance console reaches CERTIFIED status
Configure alerts with "Once Per Bar Close" delivery to match the non-repainting design.
Visual Elements
Structure Labels : CHOCH↑, CHOCH↓, BOS↑, BOS↓ markers on structure breaks
Directional EMA : Orange line showing trend bias
Trailing Stop Lines : Green (long) and red (short) trailing stop levels
Dashboard Panel : Real-time status display (structure, MACD, ATR, quality, PnL)
QA Console : Quality assurance monitoring panel
Integrity Suite Panel : Optional validation status display
Recommended Usage
Forward test with paper trading before live deployment
Monitor the QA console until it reaches CERTIFIED status
Adjust parameters based on your specific market and timeframe
Respect the trade discipline limits to avoid over-trading
Review quality scores and adjust threshold if needed
Use appropriate commission and slippage settings for your broker
Technical Implementation
The strategy uses Pine Script v6 with the following key features:
Multi-timeframe data requests with lookahead protection
Confirmed pivot detection for structure analysis
Dynamic trailing stop management
Real-time quality score calculation
Trade budgeting and cooldown enforcement
Comprehensive dashboard and monitoring panels
All source code is open and available for review and modification.
Disclaimer
This script is for educational and informational purposes only. It is not intended as financial, investment, or trading advice. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Always conduct your own research and consult with a qualified financial advisor before making any trading decisions. The author and TradingView are not responsible for any losses incurred from using this strategy.
ICT OTE Strategy Crypto PublicICT OTE Strategy Crypto Public
This strategy automates a classic ICT (Inner Circle Trader) setup specifically tailored for the high-volatility nature of cryptocurrency markets. It aims to enter a trade on a retracement after a confirmed Break of Structure (BOS), using a dual-swing detection method to validate the market's direction before looking for an entry.
The entire process is automated, from identifying the market structure to managing the trade with advanced risk management options. This version uses a percentage of equity for its order sizing, which is ideal for crypto trading.
How It Works
Dual Swing Detection: The strategy uses two different sets of swing strengths to analyze market structure for higher accuracy:
Entry Swings: Weaker, more sensitive swings used to define the immediate dealing range for a potential trade.
Validator Swings: Stronger, more significant swings used to confirm a true Break of Structure.
Break of Structure (BOS): A trade setup is only considered valid after a strong "Validator" swing breaks through a previous "Entry" swing. This confirms the market's intended direction and filters out weak or false moves.
Identify Retracement Leg: After a confirmed BOS, the strategy identifies the most recent "Entry Swing" price leg that led to the break.
Auto-Fibonacci: It automatically draws a Fibonacci retracement over this leg, from the start of the move (1.0) to the end (0.0).
Trade Entry: A limit order is placed at a user-defined Fibonacci level (defaulting to 0.618), anticipating a price pullback into a discount or premium array.
After a bullish BOS, it looks to BUY the retracement.
After a bearish BOS, it looks to SELL the retracement.
Risk Management:
Stop Loss is placed at the start of the leg (the 1.0 level).
Take Profit is placed at a user-defined level (defaulting to the 0.0 level, with extension options).
Includes an option to move the stop loss to break-even after the trade has moved a certain distance in profit.
How to Use
Asset Selection: This strategy is designed for cryptocurrency markets. Its use of percentage-based order sizing is not suitable for tick-based markets like futures.
Swing Settings: Adjust the "Entry Swing" and "Validator" strengths to match the volatility and timeframe of the asset you are trading. Higher numbers will result in fewer, more significant setups.
Backtest: Use the Strategy Tester to optimize the "FIB Entry Level," "Take Profit Level," and "Swing Sensitivity" to find the best settings for your specific market and timeframe.
ICT OTE Strategy Futures PublicICT OTE Strategy
This strategy automates a classic ICT (Inner Circle Trader) setup that aims to enter a trade on a retracement after a confirmed Break of Structure (BOS). It is designed to identify high-probability setups by waiting for the market to show its hand before looking for an entry within a "discount" or "premium" array.
The entire process is automated, from identifying the market structure to managing the trade with a dynamic stop loss.
How It Works
Break of Structure (BOS): The strategy first waits for a strong, validated swing to break a previous, weaker swing high or low. This confirms the market's intended direction.
Identify Retracement Leg: After a BOS, the strategy identifies the most recent price leg that led to the break.
Auto-Fibonacci: It automatically draws a Fibonacci retracement over this leg, from the start of the move (1.0) to the end (0.0).
Trade Entry: A limit order is placed at a user-defined Fibonacci level (defaulting to 0.508), anticipating a price pullback.
After a bullish BOS, it looks to BUY the retracement.
After a bearish BOS, it looks to SELL the retracement.
Risk Management:
Stop Loss is placed at the start of the leg (the 1.0 level).
Take Profit is placed at a user-defined level (defaulting to the 0.0 level).
Includes an option to move the stop loss to break-even after the trade has moved a certain distance in profit.
How to Use
Swing Settings: Adjust the "Entry Swing" and "Validator" strengths to match the volatility and timeframe of the asset you are trading. Higher numbers will result in fewer, more significant setups.
Session Filter: Use the "Trading Sessions" filter to align the strategy with ICT's "killzone" concept, ensuring trades are only taken during high-volume periods like the New York session.
Backtest: Use the Strategy Tester to optimize the "FIB Entry Level," "Take Profit Level," and "Min Trade Range" to find the best settings for your specific market and timeframe.
QuantBuilder | FractalystWhat's the strategy's purpose and functionality?
QuantBuilder is designed for both traders and investors who want to utilize mathematical techniques to develop profitable strategies through backtesting on historical data.
The primary goal is to develop profitable quantitive strategies that not only outperform the underlying asset in terms of returns but also minimize drawdown.
For instance, consider Bitcoin (BTC), which has experienced significant volatility, averaging an estimated 200% annual return over the past decade, with maximum drawdowns exceeding -80%. By employing this strategy with diverse entry and exit techniques, users can potentially seek to enhance their Compound Annual Growth Rate (CAGR) while managing risk to maintain a lower maximum drawdown.
While this strategy employs quantitative techniques, including mathematical methods such as probabilities and positive expected values, it demonstrates exceptional efficacy across all markets. It particularly excels in futures, indices, stocks, cryptocurrencies, and commodities, leveraging their inherent trending behaviors for optimized performance.
In both trending and consolidating market conditions, QuantBuilder employs a combination of multi-timeframe probabilities, expected values, directional biases, moving averages and diverse entry models to identify and capitalize on bullish market movements.
How does the strategy perform for both investors and traders?
The strategy has two main modes, tailored for different market participants: Traders and Investors.
1. Trading:
- Designed for traders looking to capitalize on bullish markets.
- Utilizes a percentage risk per trade to manage risk and optimize returns.
- Suitable for both swing and intraday trading with a focus on probabilities and risk per trade approach.
2. Investing:
- Geared towards investors who aim to capitalize on bullish trending markets without using leverage while mitigating the asset's maximum drawdown.
- Utilizes pre-define percentage of the equity to buy, hold, and manage the asset.
- Focuses on long-term growth and capital appreciation by fully/partially investing in the asset during bullish conditions.
How does the strategy identify market structure? What are the underlying calculations?
The strategy utilizes an efficient logic with for loops to pinpoint the first swing candle featuring a pivot of 2, establishing the point at which the break of structure begins.
What entry criteria are used in this script? What are the underlying calculations?
The script utilizes two entry models: BreakOut and fractal.
Underlying Calculations:
Breakout: The script assigns the most recent swing high to a variable. When the price closes above this level and all other conditions are met, the script executes a breakout entry (conservative approach).
Fractal: The script identifies a swing low with a period of 2. Once this condition is met, the script executes the trade (aggressive approach).
How does the script calculate probabilities? What are the underlying calculations?
The script calculates probabilities by monitoring price interactions with liquidity levels. Here’s how the underlying calculations work:
Tracking Price Hits: The script counts the number of times the price taps into each liquidity side after the EQM level is activated. This data is stored in an array for further analysis.
Sample Size Consideration: The total number of price interactions serves as the sample size for calculating probabilities.
Probability Calculation: For each liquidity side, the script calculates the probability by taking the average of the recorded hits. This allows for a dynamic assessment of the likelihood that a particular side will be hit next, based on historical performance.
Dynamic Adjustment: As new price data comes in, the probabilities are recalculated, providing real-time aduptive insights into market behavior.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
How does the script calculate expected values? What are the underlying calculations?
The script calculates expected values by leveraging the probabilities of winning and losing trades, along with their respective returns. The process involves the following steps:
This quantitative methodology provides a robust framework for assessing the expected performance of trading strategies based on historical data and backtesting results.
How is the contextual bias calculated? What are the underlying calculations?
The contextual bias in the QuantBuilder script is calculated through a structured approach that assesses market structure based on swing highs and lows. Here’s how it works:
Identification of Swing Points: The script identifies significant swing points using a defined pivot logic, focusing on the first swing high and swing low. This helps establish critical levels for determining market structure.
Break of Structure (BOS) Assessment:
Bullish BOS: The script recognizes a bullish break of structure when a candle closes above the first swing high, followed by at least one swing low.
Bearish BOS: Conversely, a bearish break of structure is identified when a candle closes below the first swing low, followed by at least one swing high.
Bias Assignment: Based on the identified break of structure, the script assigns directional biases:
A bullish bias is assigned if a bullish BOS is confirmed.
A bearish bias is assigned if a bearish BOS is confirmed.
Quantitative Evaluation: Each identified bias is quantitatively evaluated, allowing the script to assign numerical values representing the strength of each bias. This quantification aids in assessing the reliability of market sentiment across multiple timeframes.
What's the purpose of using moving averages in this strategy? What are the underlying calculations?
Using moving averages is a widely-used technique to trade with the trend.
The main purpose of using moving averages in this strategy is to filter out bearish price action and to only take trades when the price is trading ABOVE specified moving averages.
The script uses different types of moving averages with user-adjustable timeframes and periods/lengths, allowing traders to try out different variations to maximize strategy performance and minimize drawdowns.
By applying these calculations, the strategy effectively identifies bullish trends and avoids market conditions that are not conducive to profitable trades.
The MA filter allows traders to choose whether they want a specific moving average above or below another one as their entry condition.
What type of stop-loss identification method are used in this strategy? What are the underlying calculations?
- Initial Stop-loss:
1. ATR Based:
The Average True Range (ATR) is a method used in technical analysis to measure volatility. It is not used to indicate the direction of price but to measure volatility, especially volatility caused by price gaps or limit moves.
Calculation:
- To calculate the ATR, the True Range (TR) first needs to be identified. The TR takes into account the most current period high/low range as well as the previous period close.
The True Range is the largest of the following:
- Current Period High minus Current Period Low
- Absolute Value of Current Period High minus Previous Period Close
- Absolute Value of Current Period Low minus Previous Period Close
- The ATR is then calculated as the moving average of the TR over a specified period. (The default period is 14)
2. ADR Based:
The Average Day Range (ADR) is an indicator that measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days.
Calculation:
- To calculate the ADR for a particular day:
- Calculate the average of the high prices over a specified number of days.
- Calculate the average of the low prices over the same number of days.
- Find the difference between these average values.
- The default period for calculating the ADR is 14 days. A shorter period may introduce more noise, while a longer period may be slower to react to new market movements.
3. PL Based:
This method places the stop-loss at the low of the previous candle.
If the current entry is based on the hunt entry strategy, the stop-loss will be placed at the low of the candle that wicks through the lower FRMA band.
Example:
If the previous candle's low is 100, then the stop-loss will be set at 100.
This method ensures the stop-loss is placed just below the most recent significant low, providing a logical and immediate level for risk management.
- Trailing Stop-Loss:
One of the key elements of this strategy is its ability to detect structural liquidity and structural invalidation levels across multiple timeframes to trail the stop-loss once the trade is in running profits.
By utilizing this approach, the strategy allows enough room for price to run.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance.
What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
For TP1 (Take Profit 1):
- You can choose to set a take profit level at which your position gets fully closed or 50% if the TP2 boolean is enabled.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
For TP2 (Take Profit 2):
- You can choose to set a take profit level at which your position gets fully closed.
- As with break-even and TP1, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP2 level as a percentage amount above the entry price or based on RR.
What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
To facilitate studying historical data, all conditions and filters can be applied to your charts. By plotting background colors on your charts, you'll be able to identify what worked and what didn't in certain market conditions.
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Quantitive Strategy Builder to Create a Profitable Edge and System?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What makes this strategy original?
QuantBuilder stands out due to its unique combination of quantitative techniques and innovative algorithms that leverage historical data for real-time trading decisions. Unlike most algorithmic strategies that work based on predefined rules, this strategy adapts to real-time market probabilities and expected values, enhancing its reliability. Key features include:
Mathematical Framework: The strategy integrates advanced mathematical concepts, such as probabilities and expected values, to assess trade viability and optimize decision-making.
Multi-Timeframe Analysis: By utilizing multi-timeframe probabilities, QuantBuilder provides a comprehensive view of market conditions, enhancing the accuracy of entry and exit points.
Dynamic Market Structure Identification: The script employs a systematic approach to identify market structure changes, utilizing a blend of swing highs and lows to detect contextual/direction bias of the market.
Built-in Trailing Stop Loss: The strategy features a dynamic trailing stop loss based on multi-timeframe analysis of market structure. This allows traders to lock in profits while adapting to changing market conditions, ensuring that exits are executed at optimal levels without prematurely closing positions.
Robust Performance Metrics: With detailed performance tables and visualizations, users can easily evaluate strategy effectiveness and adjust parameters based on historical performance.
Adaptability: The strategy is designed to work across various markets and timeframes, making it versatile for different trading styles and objectives.
Suitability for Investors and Traders: QuantBuilder is ideal for both investors and traders looking to rely on mathematically proven data to create profitable strategies, ensuring that decisions are grounded in quantitative analysis.
These original elements combine to create a powerful tool that can help both traders and investors to build and refine profitable strategies based on algorithmic quantitative analysis.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Stratégie SMC V18.2 (BTC/EUR FINAL R3 - Tendance)This strategy is an automated implementation of Smart Money Concepts (SMC), designed to operate on the Bitcoin/Euro (BTC/EUR) chart using the 15-minute Timeframe (M15).It focuses on identifying high-probability zones (Order Blocks) after a confirmed Break of Structure (BOS) and a Liquidity Sweep, utilizing an H1/EMA 200 trend filter to only execute trades in the direction of the dominant market flow.Risk management is strict: every trade uses a fixed Risk-to-Reward Ratio (R:R) of 1:3.🧱 Core Logic Components
1. Trend Filter (H1/EMA 200)Objective: To avoid counter-trend entries, which has allowed the success rate to increase to nearly $65\%$ in backtests.Mechanism: A $200$-period EMA is plotted on a higher timeframe (Default: H1/60 minutes).Long (Buy): Entry is only permitted if the current price (M15) is above the trend EMA.Short (Sell): Entry is only permitted if the current price (M15) is below the trend EMA.
2. Order Block (OB) DetectionA potential Order Block is identified on the previous candle if it is
accompanied by an inefficiency (FVG - Fair Value Gap).
3. Advanced SMC ValidationBOS (Break of Structure): A recent BOS must be confirmed by breaking the swing high/low defined by the swing length (Default: 4 M15 candles).Liquidity (Liquidity Sweep): The Order Block zone must have swept recent liquidity (defined by the Liquidity Search Length) within a certain tolerance (Default: $0.1\%$).Point of Interest: The OB must form in a premium zone (for shorts) or a discount zone (for longs) relative to the current swing range (above or below the $50\%$ level of the range).
4. Execution and Risk ManagementEntry: The trade is triggered when the price touches the active Order Block (mitigation).Stop Loss (SL): The SL is fixed at the low of the OB (for longs) or the high of the OB (for shorts).Take Profit (TP): The TP is strictly set at a level corresponding to 3 times the SL distance (R:R 1:3).Lot Sizing: The trade quantity is calculated to risk a fixed amount (Default: 2.00 Euros) per transaction, capped by a Lot Max and Lot Min defined by the user.
Input Parameters (Optimized for BTC/EUR M15)Users can adjust these parameters to modify sensitivity and risk profile. The default values are those optimized for the high-performing backtest (Profit Factor $> 3$).ParameterDescriptionDefault Value (M15)Long. Swing (BOS)Candle length used to define the swing (and thus the BOS).4Long. Recherche Liq.Number of candles to scan to confirm a liquidity sweep.7Tolérance Liq. (%)Price tolerance to validate the liquidity sweep (as a percentage of price).0.1Timeframe TendanceChart timeframe used for the EMA filter (e.g., 60 = H1).60 (H1)Longueur EMA TendancePeriods used for the trend EMA.200Lot Max (Quantité Max BTC)Maximum quantity of BTC the strategy is allowed to trade.0.01Lot Min Réel (Exigence Broker)Minimum quantity required by the broker/exchange.0.00001
