LFH/ Long positions using MACD histogram, long EMA and short EMADisclaimer: I'm a noob.
Hey there!
I'm trying to implement a script which enter market long position when long EMA crossover short EMA and MACD histogram is positive and histogram at T time is lesser than histogram at T-1.
And when short EMA crossover long EMA, plus MACD histogram is negative and histogram at T is greater than histogram at T-1, I want the script to exit market long position.
Now, I have something pretty close to what I am looking for. What I am missing and can't figure out yet is:
How to moderate entries, ie. I would like it to enter positions when trends are really interesting not just every time the conditions are fulfilled (same for exits) as there is way too much positions
I need to find a way to exit appropriated positions.
스크립트에서 "the script"에 대해 찾기
Another Millionaire toolBack with another Millionaire tool script, put like a solid 12 minutes here curve fitting the moving averages. THIS WILL MAKE YOU A MILLIONAIRE. It is so easy, it makes one of the hardest industries very very easy. Works on any market. I'VE DECIDED TO SHARE THE SCRIPT AND MAKE IT PUBLIC SO WE CAN ALL BE RICH TOGETHER, MILLIONAIRES
ALEX LIGHT STRATEGY FOR GOOD PEOPLE VERSION 2 Strategy Overview
ALEX TRADING STRATEGY is a multi-indicator technical trading strategy designed to provide a structured decision-making framework, suitable both for traders in a learning phase and for more advanced analytical use.
The strategy is based on the combination of several well-established technical analysis tools, aiming to filter market conditions and identify coherent areas of intervention while reducing market noise.
The core indicators integrated are the Relative Strength Index (RSI), Simple Moving Averages (SMA), Exponential Moving Averages (EMA), and a market structure approach based on Higher High / Lower Low (HHLL) logic.
The objective of the script is not to generate isolated signals, but to provide a multi-factor market reading that combines momentum, trend, and price structure.
General Operating Logic
The strategy allows the user to define the operational bias (long or short) directly through the input settings. Market state and position direction are visualized through color-coded candlesticks, improving readability in live market conditions.
Explicit exit rules are integrated to frame risk management and the closure of open positions. Indicator time settings can be adjusted to suit different assets or trading horizons.
The strategy also includes complementary technical levels such as:
pivot lines,
support and resistance levels,
to further contextualize decision-making.
Indicators Used
Momentum – RSI
The RSI is used to identify overbought and oversold conditions:
RSI > 70: overbought zone
RSI < 30: oversold zone
These levels are displayed graphically to highlight potential market imbalances.
Moving Averages – SMA and EMA
The strategy integrates:
user-configurable SMA,
fixed EMA with periods 20, 50, and 100.
Interactions between closing price and moving averages are used to qualify trend direction and generate conditional entry signals.
Entry Conditions
Two main methodologies are combined:
1. Keltner Channel
Long signal when the closing price crosses above the upper band.
Short signal when the closing price crosses below the lower band.
This approach aims to capture directional market expansion phases.
2. Market Structure – HHLL
The Higher High / Lower Low logic is used to identify structural breakouts:
Long entry when the current high exceeds the highest high of the last n periods,
Short entry when the current low breaks below the lowest low of the last n periods.
Signals are plotted directly on the chart for immediate visibility.
Exit Conditions and Position Management
Exit rules are based on the Keltner Channel:
Long positions are closed when price moves back below the lower band,
Short positions are closed when price moves back above the upper band.
These mechanisms ensure disciplined position management aligned with market volatility logic.
Market Visualization and Interpretation
The strategy applies candlestick color coding:
Green: active long bias
Red: active short bias
Blue: no position / neutral market
This visual framework is designed to improve clarity and reduce cognitive load during analysis.
Evolutions and Extensions
The strategy has been enhanced with a swing trading module, aimed at capturing price movements over a 1- to 4-day horizon, particularly during periods of moderate volatility.
Additional extensions include:
multi-horizon moving average system (short / medium / long term),
fast crossover signals,
visual trend-confirmation zones,
integration of the CCI indicator to refine entries through momentum filtering.
Disclaimer
This strategy is an analysis and decision-support tool. It does not constitute investment advice and does not guarantee performance.
Any live use must be preceded by thorough testing (backtesting, forward testing) and risk management aligned with the user’s profile.
✅ How to Use – Operational Guidelines
1. Directional Filter (Mandatory)
The first element to consider is the candlestick color:
Green: long setups only
Red: short setups only
Blue: no trade, market not exploitable
No position should ever be taken against the active bias.
2. Trend Validation
Signals are only acted upon when aligned with the trend:
price above EMA levels → bullish context
price below EMA levels → bearish context
Signals are ignored during ranging or heavily compressed market conditions.
3. Entry Execution
Keltner and HHLL signals are used as triggers, not as automatic orders.
Entries are ideally executed:
on a technical pullback,
with momentum confirmation (RSI alignment),
not during impulsive breakout moves.
4. Risk Management
Stop-loss placement should be:
behind a real structural invalidation,
below the last structural low for long positions,
above the last structural high for short positions.
If the stop distance is large, position size must be reduced accordingly.
5. Exit Management
Exits are triggered:
by Keltner Channel rules,
or by a clear change in market context (bias, structure, or momentum).
Partial profit-taking may be applied at intermediate technical levels.
6. Usage Philosophy
ALEX TRADING STRATEGY is designed as a structured decision framework, not as a mechanical signal generator.
Performance quality depends on execution discipline, risk management, and strict respect of market context.
Reversal WaveThis is the type of quantitative system that can get you hated on investment forums, now that the Random Walk Theory is back in fashion. The strategy has simple price action rules, zero over-optimization, and is validated by a historical record of nearly a century on both Gold and the S&P 500 index.
Recommended Markets
SPX (Weekly, Monthly)
SPY (Monthly)
Tesla (Weekly)
XAUUSD (Weekly, Monthly)
NVDA (Weekly, Monthly)
Meta (Weekly, Monthly)
GOOG (Weekly, Monthly)
MSFT (Weekly, Monthly)
AAPL (Weekly, Monthly)
System Rules and Parameters
Total capital: $10,000
We will use 10% of the total capital per trade
Commissions will be 0.1% per trade
Condition 1: Previous Bearish Candle (isPrevBearish) (the closing price was lower than the opening price).
Condition 2: Midpoint of the Body The script calculates the exact midpoint of the body of that previous bearish candle.
• Formula: (Previous Open + Previous Close) / 2.
Condition 3: 50% Recovery (longCondition) The current candle must be bullish (green) and, most importantly, its closing price must be above the midpoint calculated in the previous step.
Once these parameters are met, the system executes a long entry and calculates the exit parameters:
Stop Loss (SL): Placed at the low of the candle that generated the entry signal.
Take Profit (TP): Calculated by projecting the risk distance upward.
• Calculation: Entry Price + (Risk * 1).
Risk:Reward Ratio of 1:1.
About the Profit Factor
In my experience, TradingView calculates profits and losses based on the percentage of movement, which can cause returns to not match expectations. This doesn’t significantly affect trending systems, but it can impact systems with a high win rate and a well-defined risk-reward ratio. It only takes one large entry candle that triggers the SL to translate into a major drop in performance.
For example, you might see a system with a 60% win rate and a 1:1 risk-reward ratio generating losses, even though commissions are under control relative to the number of trades.
My recommendation is to manually calculate the performance of systems with a well-defined risk-reward ratio, assuming you will trade using a fixed amount per trade and limit losses to a fixed percentage.
Remember that, even if candles are larger or smaller in size, we can maintain a fixed loss percentage by using leverage (in cases of low volatility) or reducing the capital at risk (when volatility is high).
Implementing leverage or capital reduction based on volatility is something I haven’t been able to incorporate into the code, but it would undoubtedly improve the system’s performance dramatically, as it would fix a consistent loss percentage per trade, preventing losses from fluctuating with volatility swings.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to exit or SL
And if volatility is high and exceeds the fixed percentage we want to expose per trade (if SL is hit), we could reduce the position size.
For example, imagine we only want to risk 15% per SL on Tesla, where volatility is high and would cause a 23.57% loss. In this case, we subtract 23.57% from 15% (the loss percentage we’re willing to accept per trade), then subtract the result from our usual position size.
23.57% - 15% = 8.57%
Suppose I use $200 per trade.
To calculate 8.57% of $200, simply multiply 200 by 8.57/100. This simple calculation shows that 8.57% equals about $17.14 of the $200. Then subtract that value from $200:
$200 - $17.14 = $182.86
In summary, if we reduced the position size to $182.86 (from the usual $200, where we’re willing to lose 15%), no matter whether Tesla moves up or down 23.57%, we would still only gain or lose 15% of the $200, thus respecting our risk management.
Final Notes
The code is extremely simple, and every step of its development is detailed within it.
If you liked this strategy, which complements very well with others I’ve already published, stay tuned. Best regards.
Adaptive Trend Navigator [ATH Filter & Risk Engine]Description:
This strategy implements a systematic Trend Following approach designed to capture major moves while actively protecting capital during severe bear markets. It combines a classic Moving Average "Fan" logic with two advanced risk management layers: a 4-Stage Dynamic Stop Loss and a macro-economic "Circuit Breaker" filter.
Core Concepts:
1. Trend Identification (Entry Logic) The script uses a cascade of Simple Moving Averages (SMA 25, 50, 100, 200) to identify the maturity of a trend.
Entries are triggered by specific crossovers (e.g., SMA 25 crossing SMA 50) or by breaking above the previous trade's high ("High-Water Mark" Re-Entry).
2. The "Circuit Breaker" (Crash Protection) To prevent trading during historical market collapses (like 2000 or 2008), the strategy monitors the Nasdaq 100 (QQQ) as a global benchmark:
Normal Regime: If the market is within 20% of its All-Time High, the strategy operates normally.
Crisis Regime: If the QQQ falls more than 20% from its ATH, the "Circuit Breaker" activates (Visualized by a Red Background).
Recovery Rule: In a Crisis Regime, new long positions are blocked unless the QQQ reclaims its SMA 200. This filters out "bull traps" in secular bear markets.
3. 4-Stage Risk Engine (Exit Logic) Once in a trade, the risk management adapts to the position's performance:
Stage 1: Fixed initial Stop Loss (default 10%) for breathing room.
Stage 2: Moves to Break-Even area once the price rises 12%.
Stage 3: Tightens to a trailing stop (8%) after 25% profit.
Stage 4: Maximizes gains with a tight trailing stop (5%) during parabolic moves (>40% profit).
Visual Guide:
SMAs: 25/50/100/200 period lines for trend visualization.
Red Background: Indicates the "Crisis Regime" where trading is halted due to broad market weakness.
Blue Background: Indicates a "Recovery Phase" (Crisis is active, but market is above SMA 200).
Red Line: Shows the dynamic Stop Loss level for active positions.
Settings: All parameters (SMA lengths, Drawdown threshold, Risk Stages) are fully customizable. The QQQ benchmark ticker can also be changed to SPY or other indices depending on the asset class traded.
Classic Wave: The Easy WayClassic Wave is a simple strategy with few rules and no over-optimization. Despite its simplicity, it is backed by a nearly century-long historical track record, delivering excellent returns on the weekly chart of the SPX (TVC).
I also recommend observing its strong performance on the SPY (weekly), which is the perfect instrument for executing this strategy with futures in the future.
Strategy Rules and Parameters
When a bullish candle closes above the 20-period EMA, we place the stop-loss below the low of that candle and target a risk-reward ratio of 1:1.
A second, more profitable variant is to change the risk-reward ratio in the code to 2:1.
-Total capital: $10,000
-We use 10% of the total capital per trade.
-Commissions: 0.1% per trade.
The code construction is simple and very well detailed within the script itself.
Risk-Reward Ratio 2:1
Using a 2:1 risk-reward ratio reduces the win rate but significantly increases profitability.
Across the full historical data of the SPX index (weekly), the system would have generated 236 trades, with a win rate of 51.27% and a profit factor of 2.53.
From January 1, 2023, to November 28, 2025, the system would have generated 5 trades, with an 80% win rate and a profit factor of 9.244.
What makes this system so good?
-It takes advantage of the long-term bullish bias of U.S. stock indices and traditional markets.
-It filters out a lot of noise thanks to the weekly timeframe.
-It uses simple parameters with no over-optimization.
Final Notes:
This strategy has consistently outperformed the returns offered by most traditional funds over time, with fewer drawdowns and significantly less stress. I hope you like it.
Long-Term Strategy: 1-Year Breakout + 6-Month ExitDescripción (Description): (Copia y pega todo lo que está dentro del recuadro de abajo)
Description
This is a long-term trend-following strategy designed to capture major market moves while filtering out short-term noise. It is based on the classic principle of "buying strength" (Breakouts) and allowing profits to run, while cutting losses when the medium-term trend reverses.
How it Works (Logic)
1. Entry Condition (Long Only): The strategy looks for a significant display of strength. It enters a Long position only when two conditions are met simultaneously:
Price Breakout: The closing price exceeds the highest high of the last 252 trading days (approximately 1 year). This ensures we are entering during a strong momentum phase.
Trend Filter: The SuperTrend indicator (Settings: ATR 10, Factor 3.0) must be bullish. This acts as a confirmation filter to avoid false breakouts in choppy markets.
2. Exit Condition: The strategy uses a trailing stop based on price action, not a fixed percentage.
It closes the position when the price closes below the lowest low of the last 126 trading days (approximately 6 months).
This wide exit allows the trade to "breathe" during normal market corrections without exiting the position prematurely.
Settings & Risk Management
Capital Usage: The script is configured to use 10% of equity per trade to reflect realistic risk management (compounding).
Commissions: Included at 0.1% to simulate real trading costs.
Slippage: Included (3 ticks) to account for market execution variability.
Best Use: This strategy is intended for higher timeframes (Daily or Weekly) on trending assets like Indices, Crypto, or Commodities.
Alpha VWAP Regime🔥 Alpha VWAP Regime — Institutional VWAP Strategy (Closed Source)
Alpha VWAP Regime is a multi-layered VWAP trading system that identifies the active market regime and adapts its signals based on institutional liquidity behavior.
This strategy is closed-source because it uses a proprietary combination of VWAP structures, anchored pivot logic, band deviations, and regime detection filters that are not publicly available.
🧠 How the Strategy Works (Conceptual Explanation)
This strategy does not rely on a single VWAP line.
Instead, it builds a VWAP matrix consisting of:
1) Session VWAP
Defines fair value for the current session.
Used to detect intraday directional bias.
2) Anchored VWAP (AVWAP)
Automatically anchored to swing highs and lows (pivot-based).
Tracks where large players accumulated or distributed positions.
3) VWAP Bands (±1σ and ±2σ)
Used as dynamic volatility envelopes:
±1σ = fair-value zone / no-trade area
±2σ = mean-reversion extremes
4) Market Regime Classification (ADX-based)
The strategy determines which environment the market is in:
Trending Regime: ADX above threshold
Ranging Regime: ADX below threshold
Breakout Regime: Volume-based breakout of AVWAP
Each regime activates a different entry model.
📌 Entry Logic (High-Level Overview)
Trend Mode
Triggered only when ADX confirms a trend.
Entries occur near VWAP or −1σ using price-action confirmation.
Mean Reversion Mode
Activated when the market is ranging.
Entries target the ±2σ deviation bands.
Breakout Mode
Triggered by price crossing AVWAP with above-average volume.
Used to catch institutional continuation moves.
ALL Mode
Combines the three models for a full adaptive system.
📉 Exits & Risk Management
All stops and targets use ATR-based volatility sizing
Trend trades aim for larger targets
Mean-reversion trades aim for smaller snapback moves
Breakouts use wider stops but high R:R
🔍 How to Use the Strategy
Load the script on a clean chart
Choose your preferred regime mode (Trend / MR / Breakout / ALL)
Optionally hide VWAP indicators and display signals only
Use realistic position sizing and commissions
Evaluate performance across multiple assets and timeframes
🔒 Why It Is Closed-Source
The code uses:
A custom anchoring engine
Multi-layered regime filters
Dynamic VWAP matrix
Prop logic for bias scoring
These components were built from scratch and form a unique decision model, so the source is protected.
🇸🇦 الشرح العربي لاستراتيجية Alpha VWAP Regime
Alpha VWAP Regime هي استراتيجية تداول مؤسسية متقدمة تعتمد على تحليل السيولة، وتحديد حالة السوق (Market Regime)، ودمج عدة طبقات من VWAP داخل نموذج واحد متكيف.
الهدف من الاستراتيجية هو التداول في المناطق التي يتواجد فيها المال الذكي، وتجنب التداول في المناطق العشوائية أو منخفضة الجودة.
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🧠 كيف تعمل الاستراتيجية؟
الاستراتيجية لا تعتمد على VWAP واحد، بل تستخدم “مصفوفة VWAP” كاملة تتكوّن من:
1) VWAP اليومي (Session VWAP)
يُستخدم لتحديد القيمة العادلة خلال الجلسة، وتحديد الاتجاه اللحظي (Intraday Bias).
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2) VWAP المثبّت (Anchored VWAP)
يتم تثبيته تلقائيًا على:
• القمم المهمة (Swing Highs)
• القيعان المهمة (Swing Lows)
ويساعد في تحديد مناطق تمركز المؤسسات، ومناطق الانعكاس أو الاختراقات الحقيقية.
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3) نطاقات VWAP (±1σ و ±2σ)
تُستخدم كأغلفة ديناميكية للسيولة والتقلب:
• ±1σ = منطقة القيمة العادلة (Fair-Value Zone)
→ غالبًا منطقة غير مناسبة للتداول (No-Trade Zone)
• ±2σ = مناطق التشبّع الحركي (Extremes)
→ مناسبة لاستراتيجيات الانعكاس (Mean Reversion)
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4) تصنيف حالة السوق Market Regimes
الاستراتيجية تستخدم مؤشر ADX لتحديد حالة السوق الحالية:
حالة السوق الوصف
Trending اتجاه واضح وقوي
Ranging تذبذب بدون اتجاه
Breakout اختراق مدعوم بحجم تداول
كل Regime يفعّل نموذج دخول مختلف داخل الاستراتيجية.
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🎯 نماذج الدخول داخل الاستراتيجية
1) نموذج الاتجاه (Trend Mode)
يعمل فقط عندما يكون السوق في اتجاه حقيقي.
يعتمد على دخول Pullbacks قرب VWAP أو نطاق −1σ مع تأكيد شموعي.
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2) نموذج الانعكاس (Mean Reversion Mode)
يعمل فقط عندما يكون السوق متذبذبًا (Range).
الدخول عند لمس ±2σ بهدف العودة نحو VWAP.
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3) نموذج الاختراق (Breakout Mode)
يستخدم اختراقات Anchored VWAP
ولكن بشرط وجود حجم تداول أعلى من المتوسط (Volume Confirmation).
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4) وضع الدمج (ALL Mode)
يجمع بين النماذج الثلاثة ويجعل الاستراتيجية متكيفة تلقائيًا مع كل حالات السوق.
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📉 الخروج وإدارة المخاطر
تستخدم الاستراتيجية نظامًا ديناميكيًا لإدارة المخاطر:
• وقف الخسارة مبني على ATR
• الأهداف مبنية على طبيعة النموذج
• الصفقات الاتجاهية تستهدف R:R أعلى
• صفقات MR أقصر وأسرع
• صفقات Breakout أوسع ولكن مدعومة بزخم قوي
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🧩 كيفية استخدام الاستراتيجية
1. ضع الاستراتيجية على رسم بياني نظيف بدون مؤشرات إضافية
2. اختر نموذج الدخول المناسب من الإعدادات
3. فعّل أو أخفِ خطوط VWAP حسب الحاجة
4. استخدم إعدادات مخاطرة واقعية
5. اختبر الاستراتيجية على عدة أسواق وفريمات
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🔒 سبب إغلاق الكود
تم إغلاق الكود لأنها تعتمد على:
• محرك تثبيت AVWAP خاص
• نظام Regime Detection متقدم
• مصفوفة VWAP متعددة الطبقات
• منطق دخول/خروج خاص تم تطويره بالكامل
كل ذلك يتطلب حماية الملكية الفكرية، لذا تم نشرها Closed-Source.
GOLDM Dow Theory – 1H Trend + 5m Pullback1. Strategy Overview
Instrument: MCX GOLDM
Chart timeframe: 5 minutes
Side: Long-only
Position size: Fixed 3 lots
Core idea:
Trade only in 1H uptrend, enter after a 5m pullback and breakout, with basic volume/volatility filters and ATR-based SL/TP.
2. High-Level Logic Flow (Per Bar)
On every 5-minute bar, the script does this:
Update session/time, volume, and ATR filters
Read 1H trend from higher timeframe
Update 5m pullback state (whether a valid dip happened)
Check if there is a valid breakout back in the direction of the 1H trend
If all filters + conditions align → enter Long (3 lots)
While in a trade:
Manage SL/TP using ATR
Close trade if 1H trend flips down or price closes below 5m EMA
Everything else (plots, alerts) is just for visibility and convenience.
3. Inputs & Configuration
Main inputs:
pullbackLookback – how many 5m bars to look back to detect a pullback
breakoutLookback – how many bars to consider for recent swing high
emaLenTrendFast / emaLenTrendSlow – 1H EMAs (50/200) for trend
emaLenPullback – 5m EMA used for pullback logic (default 20)
tradeSession – default "0900-2315" (you can change)
volLookback, volMult – volume filter
atrLen, atrSmaLen – ATR filter
slATRmult (1.4), tpATRmult (3.0) – ATR multiples → ~1.4 : 3 RR
4. Session / Time Filter
tradeSession = "0900-2315"
inSession = not useSessionFilter or not na(time(timeframe.period, tradeSession))
Only allows entries when the current bar’s time is inside 09:00–23:15.
If useSessionFilter is false, this filter is ignored.
No trade opens outside this window, but existing trades can still exit.
5. Volume & Volatility Filters
Volume Filter
avgVol = ta.sma(volume, volLookback)
highVolume = not useVolumeFilter or (volume > avgVol * volMult)
If enabled, current bar’s volume must be greater than average volume × multiplier.
Purpose: avoid thin, illiquid periods.
ATR Filter
atr5 = ta.atr(atrLen)
atrSma = ta.sma(atr5, atrSmaLen)
goodATR = not useATRFilter or (atr5 > atrSma)
If enabled, current ATR must be above its own moving average.
Purpose: avoid flat / extremely low-volatility periods.
Only if both highVolume and goodATR are true, the system considers entering.
6. Higher Timeframe Trend (1H)
emaFast1h = request.security(syminfo.tickerid, "60", ta.ema(close, emaLenTrendFast), ...)
emaSlow1h = request.security(syminfo.tickerid, "60", ta.ema(close, emaLenTrendSlow), ...)
trendUp = emaFast1h > emaSlow1h
trendDown = emaFast1h < emaSlow1h
On the 1-hour timeframe:
If EMA Fast (50) > EMA Slow (200) → trendUp = true
If EMA Fast (50) < EMA Slow (200) → trendDown = true
This is the core trend filter:
We only look for longs when trendUp is true.
7. 5-Minute Structure Logic (Dow-style)
7.1 Pullback Detection
emaPull = ta.ema(close, emaLenPullback)
pulledBackLong = ta.lowest(close, pullbackLookback) < emaPull
A pullback is defined as:
In the last pullbackLookback bars, price closed below the 5m EMA (emaPull) at least once.
This indicates a dip against the 1H uptrend.
A state flag tracks this:
var bool hadLongPullback = false
hadLongPullback := trendUp and pulledBackLong ? true : (not trendUp ? false : hadLongPullback)
When:
trendUp AND pulledBackLong → hadLongPullback = true.
If the trend stops being up (trendUp = false), flag resets to false.
So the system remembers:
“There has been a proper dip while the 1H uptrend is active.”
7.2 Breakout Confirmation
recentHigh = ta.highest(high, pullbackLookback)
breakoutUp = close > recentHigh
After a pullback, we wait for price to close above the highest high of recent bars (excluding the current one).
This mimics:
“Higher high after a higher low” → breakout in Dow Theory terms.
8. Final Long Entry Logic
The base entry condition:
baseLongEntry =
trendUp and
hadLongPullback and
breakoutUp and
close > emaPull
Translated:
1H trend is up (trendUp).
A valid pullback happened recently (hadLongPullback).
Current candle broke above the recent swing high (breakoutUp).
Price is now back above the 5m EMA (pullback is resolving, not deepening).
Then filters are applied:
longEntryCond =
baseLongEntry and
inSession and
highVolume and
goodATR and
not isLong
So a long entry only occurs if:
Core structure conditions (baseLongEntry) are true
Time is within session
Volume is high enough
ATR is healthy
You are not already in a long
When longEntryCond is true:
if longEntryCond
strategy.entry("Long", strategy.long, comment = "Dow Long: Trend+PB+BO")
hadLongPullback := false
Enters 3 lots long (as per default_qty_type + default_qty_value).
Resets hadLongPullback so we don’t re-use the same pullback.
9. Exit Logic
There are two exit layers:
9.1 Logical Exit (Trend or Structure Change)
exitLongTrendFlip = trendDown
exitLongEMA = ta.crossunder(close, emaPull)
longExitCond = isLong and (exitLongTrendFlip or exitLongEMA)
If in a long:
Exit when trend flips down (1H EMA50 < EMA200), OR
Price crosses below 5m EMA (pullback may be turning into reversal).
Then:
if longExitCond
strategy.close("Long", comment = "Exit Long: Trend flip / EMA break")
This closes the position at market (on bar close).
9.2 ATR-based Stop Loss & Take Profit
if useSLTP and isLong
longStop = strategy.position_avg_price - atr5 * slATRmult
longLimit = strategy.position_avg_price + atr5 * tpATRmult
strategy.exit("Long SLTP", "Long", stop = longStop, limit = longLimit)
SL = entry price – 1.4 × ATR(14, 5m)
TP = entry price + 3.0 × ATR(14, 5m)
This gives roughly 1.4 : 3 RR.
If SL or TP is hit, strategy.exit will close the trade.
So exits can come from:
Hitting Stop Loss
Hitting Take Profit
OR logic-based exit (trend flip / EMA break)
10. Alerts
Two alertconditions:
alertcondition(longEntryCond, title="Long Entry Signal",
message="GOLDM LONG: 1H Uptrend + 5m Pullback Breakout + Filters OK")
alertcondition(longExitCond, title="Long Exit Signal",
message="GOLDM LONG EXIT: Trend flip or EMA break")
You can set TradingView alerts based on:
“Long Entry Signal” → tells you when all entry conditions align.
“Long Exit Signal” → tells you when the logic-based exit triggers.
(ATR SL/TP exits won’t auto-alert unless you separately set price alerts or add extra conditions.)
11. Mental Model Summary (How YOU should think about it)
For every trade, the system is basically doing this:
Is GOLDM in an uptrend on 1H?
→ If no: do nothing
Did we get a clear dip below 5m EMA in that uptrend?
→ If no: wait
Did price then break above recent highs and reclaim EMA20?
→ If yes: this is our Dow-style continuation entry
Is market liquid and moving (volume + ATR)?
→ If yes: go Long with 3 lots
Manage with:
ATR SL & TP
Exit early if 1H trend flips or price falls back below EMA20
Qullamagi EMA Breakout Autotrade (Crypto Futures L+S)Title: Qullamagi EMA Breakout – Crypto Autotrade
Overview
A crypto-focused, Qullamagi-style EMA breakout strategy built for autotrading on futures and perpetual swaps.
It combines a 5-MA trend stack (EMA 10/20, SMA 50/100/200), volatility contraction boxes, volume spikes and an optional higher-timeframe 200-MA filter. The script supports both long and short trades, partial take profit, trailing MA exits and percent-of-equity position sizing for automated crypto futures trading.
Key Features (Crypto)
Qullamagi MA Breakout Engine – trades only when price is aligned with a strong EMA/SMA trend and breaks out of a tight consolidation range. Longs use: Close > EMA10 > EMA20 > SMA50 > SMA100 > SMA200. Shorts are the mirror condition with all MAs sloping in the trend direction.
Strict vs Loose Modes – Strict (Daily) is designed for cleaner swing trades on 1H–4H (full MA stack, box+ATR and volume filters, optional HTF filter). Loose (Intraday) focuses on 10/20/50 alignment with relaxed filters for more frequent 15m–30m signals.
Volatility & Volume Filters for Crypto – ATR-based box height limit to detect volatility contraction, wide-candle filter to avoid chasing exhausted breakouts, and a volume spike condition requiring current volume to exceed an SMA of volume.
Higher-Timeframe Trend Filter (Optional) – uses a 200-period SMA on a higher timeframe (default: 1D). Longs only when HTF close is above the HTF 200-SMA, shorts only when it is below, helping avoid trading against dominant crypto trends.
Autotrade-Oriented Trade Management – position size as % of equity, initial stop anchored to a chosen MA (EMA10 / EMA20 / SMA50) with optional buffer, partial take profit at a configurable R-multiple, trailing MA exit for the remainder, and an optional cooldown after a full exit.
Markets & Timeframes
Best suited for BTC, ETH and major altcoin futures/perpetuals (Binance, Bybit, OKX, etc.).
Strict preset: 1H–4H charts for classic Qullamagi-style trend structure and fewer fake breakouts.
Loose preset: 15m–30m charts for higher trade frequency and more active intraday trading.
Always retune ATR length, box length, volume multiplier and position size for each symbol and exchange.
Strategy Logic (Quick Summary)
Long (Strict): MA stack in bullish alignment with all MAs sloping up → tight volatility box (ATR-based) → volume spike above SMA(volume) × multiplier → breakout above box high (close or intrabar) → optional HTF close above 200-SMA.
Short: Mirror logic: bearish MA stack, tight box, volume spike and breakdown below box low with optional HTF downtrend.
Best Practices for Crypto
Backtest on each symbol and timeframe you plan to autotrade, including commissions and slippage.
Start on higher timeframes (1H/4H) to learn the behavior, then move to 15m–30m if you want more signals.
Use the higher-timeframe filter when markets are strongly trending to reduce counter-trend trades.
Keep position-size percentage conservative until you fully understand the drawdowns.
Forward-test / paper trade before connecting to live futures accounts.
Webhook / Autotrade Integration
Designed to work with TradingView webhooks and external crypto trading bots.
Alert messages include structured fields such as: EVENT=ENTRY / SCALE_OUT / EXIT, SIDE=LONG / SHORT, STRATEGY=Qullamagi_MA.
Map each EVENT + SIDE combination to your bot logic (open long/short, partial close, full close, etc.) on your preferred exchange.
Important Notes & Disclaimer
Crypto markets are highly volatile and can change regime quickly. Backtest and forward-test thoroughly before using real capital. Higher timeframes generally produce cleaner MA structures and fewer fake breakouts.
This strategy is for educational and informational purposes only and does not constitute financial advice. Trading leveraged crypto products involves substantial risk of loss. Always do your own research, manage risk carefully, and never trade with money you cannot afford to lose.
RSI + MACD Multi-Timeframe StrategyThis strategy combines the Relative Strength Index (RSI) from the daily timeframe with the Moving Average Convergence Divergence (MACD) from the 4-hour timeframe to generate precise long entry and exit signals.
The system uses a multi-timeframe approach to align longer-term trend conditions with shorter-term momentum shifts — allowing traders to catch dips with confirmation and exit before reversals.
🧠 Strategy Logic
✅ Long Entry Condition:
- RSI on the daily (1D) timeframe is oversold (below your defined threshold)
- MACD on the 4H timeframe crosses above the signal line
→ A long trade is opened when these two align
✅ Long Exit Condition:
- RSI on the daily timeframe is overbought
- MACD on the 4H timeframe crosses below the signal line
→ The long trade is closed when these two conditions are met
💡 This strategy currently supports long entries only. Short logic can be added if needed.
📊 Indicator Components
🔹 RSI (Relative Strength Index):
- A momentum oscillator that measures the speed and magnitude of price changes.
- Helps identify overbought (potential sell) and oversold (potential buy) conditions.
- Applied on the 1D timeframe (by default) to reflect broader market trend or exhaustion levels.
🔹 MACD (Moving Average Convergence Divergence):
- A trend-following momentum indicator based on moving averages.
- The MACD Line (fast EMA - slow EMA) crossing above the Signal Line indicates bullish momentum.
- Used here on the 4-hour timeframe (by default) for shorter-term momentum confirmation.
🔹 Multi-Timeframe (MTF) Logic:
- Uses request.security() to pull higher timeframe data (1D for RSI, 4H for MACD).
- Ensures no repainting, as it only uses closed candles from the higher timeframe.
- Aligns longer-term signals with shorter-term entries, reducing false signals.
📈 Plotting Options
The script includes a plot selector input allowing you to toggle between:
- RSI Plot (with overbought/oversold lines)
- MACD Plot (MACD line and signal line)
- This helps visualize signal conditions clearly on your chart.
🛠 Customization
- RSI & MACD settings are fully configurable
- RSI and MACD timeframes can be adjusted independently
⚠️ Disclaimer
This strategy is provided for educational and informational purposes only.
It is not financial advice or a recommendation to buy or sell any asset.
Past performance does not guarantee future results. Always test strategies in a simulated environment before live use, and consult with a licensed financial advisor for investment decisions.
Super Frog Power - Cluster Flip %Super Frog Power - Cluster Flip %
🔄 Trade Smarter, Not Harder: Let the Cluster Decide
Welcome to the "Super Frog Power - Cluster Flip %" strategy, a sophisticated multi-system confluence engine designed to filter out market noise and pinpoint high-probability trade setups. This isn't just another indicator; it's a comprehensive trading system that aggregates signals from eight distinct technical methodologies, waiting for them to align into a powerful "cluster" before you enter a trade.
🎯 Core Philosophy: The Power of Confluence
A single indicator can give false signals. A cluster of indicators from uncorrelated systems agreeing on a direction is a much stronger signal. This strategy continuously monitors multiple independent systems and only executes a trade when a significant number of them flip to a consensus, dramatically increasing the likelihood of a successful move.
✨ The 8 Systems of Super Frog Power
This strategy synthesizes signals from the following powerful components:
Bollinger Bands®: Identifies overbought and oversold conditions relative to recent volatility.
CMI (Cluster Momentum Index) System: A unique multi-period momentum oscillator that identifies convergence and breakout moments with custom "Lion" (SELL) and "Car" (BUY) signals.
SMI (Stochastic Momentum Index) System: A refined momentum indicator that generates "Mouse" (BUY) signals and combines with CMI for "Green Angel" and "Red Devil" super signals.
Lucky Balls (NVI/PVI): Utilizes Negative and Positive Volume Index to gauge smart money flow and identify accumulation/distribution zones.
Momentum System: A triple-threat combo of RSI, CCI, and PPO, scaled and combined to generate robust momentum-based entries and exits.
Lucky Table (Oscillator Overload): Counts the number of key oscillators (SMI, RSI, CCI) in overbought or oversold territory, triggering a signal when a threshold is met.
Apples & Pairs System: A complex system analyzing price swings, accumulation, mass index, and doji patterns with fun, emoji-based signals like "Apple Cross Up" 🍎 and "Pig Cross Down" 🐖.
ZBT (Zonal Breakout Trend) System: A multi-timeframe trend-following system using dynamic EMA channels and an ATR-based trailing stop to identify the primary trend and robust breakout points.
⚙️ How It Works: The Cluster Flip Logic
The magic happens in the signal aggregation. The strategy counts every single BUY and SELL signal from all active systems.
A "Strong Buy" is triggered when 6 or more independent BUY signals occur simultaneously.
A "Strong Sell" is triggered when 5 or more independent SELL signals occur simultaneously.
This "cluster flip" mechanism ensures you are only trading when there is broad-based technical agreement, keeping you out of choppy and uncertain market conditions.
🛡️ Integrated Risk Management
We believe a strategy is nothing without proper risk management. This system comes with built-in, percentage-based order management:
User-Defined Profit Target (%): Lock in profits automatically at your specified percentage gain.
User-Defined Stop Loss (%): Protect your capital with a hard stop loss.
Position Sizing: Control your risk per trade with a customizable position size.
Trades are also managed logically: a new strong signal in the opposite direction will automatically close any existing position, ensuring you're always on the right side of the cluster's consensus.
🎨 Visual Features & Customization
Fully Customizable: Don't like one system? Turn it off! Every system can be toggled on/off from the inputs.
Clear Visuals: Each system is plotted in a distinct color, making the chart a rich source of information without being cluttered.
Signal Markers: Strong Buy and Strong Sell clusters are clearly marked with large circles below and above the bars.
Alert Ready: Built-in alerts for Strong Buy and Strong Sell signals so you never miss a cluster setup.
🚀 How to Use
Add the script to your chart (1H, 4H, or Daily timeframes are recommended for swing trading).
Adjust the inputs to your liking, especially the Profit Target %, Stop Loss %, and Position Size under the "Strategy Parameters" section.
Observe the clusters. Wait for the "Strong Buy" or "Strong Sell" circle to appear.
Enter the trade. The strategy will automatically plot the profit target and stop loss levels on the chart for your reference.
Manage your trade. Let the logic handle the exits, or use your own discretion.
💡 Ideal For
Swing Traders looking for high-confidence set-and-forget setups.
Technical Analysts who appreciate the depth of multi-system confluence.
Traders who want to avoid the paralysis of analyzing too many indicators separately.
Unleash the power of cluster trading. Add the "Super Frog Power - Cluster Flip %" to your chart today!
AMF PG Consensus Engine v3.5AMF PG Consensus Engine v3.5
1. Core Philosophy: A Multi-Stage Confirmation System for High-Probability Signals
In the world of automated trading, the real challenge isn't generating signals, but filtering out the noise. The AMF PG Consensus Engine is designed to address this challenge. It operates on a simple yet powerful philosophy: a buy or sell signal is valid only if it receives confirmation from multiple, independent analysis modules.
This strategy isn't a "black box." It's a transparent, rules-based framework that transforms market momentum and momentum into a final consensus and then directs a core trend-following engine. The goal is to avoid trading in adverse market conditions and only act when the different analysis layers agree.
2. How the Consensus Engine Works: Two Confirmation Layers
Before the core engine is allowed to seek a trade, the market must go through a two-stage "confirmation" process. Both filters can be enabled or disabled from the settings, allowing users to customize the strategy's stringency level.
Confirmation Module 1: Renko Regime Filter
This module's purpose is to answer a critical question: "Is the market currently in a stable, directional trend, or is it volatile and unstable?" Instead of standard indicators, it creates a timeless Renko chart in the background. A trend is confirmed only if a minimum number of consecutive Renko bricks form in the same direction. This method is extremely effective at filtering out noisy, sideways price movements, which are often unsuccessful for trend-following systems. The brick size can be set to a fixed value or automatically calculated based on the Average True Range (ATR) for better fit.
Confirmation Module 2: Candle Scoring Engine
This module analyzes the raw strength of price action by scoring each candle individually. It evaluates the candle's direction, body size relative to the previous candle, and the change in closing price. These factors are converted into a score for each bar. A cumulative score is then calculated over a user-defined period. A buy trade is only confirmed if this cumulative momentum score exceeds a positive threshold, indicating sustained buying pressure. Conversely, a sell trade requires the score to fall below a negative threshold, indicating sustained selling pressure.
3. Core Engine: AMF PG Trend Follower
When both confirmation modules give the "green light" for a specific direction (e.g., buy), the core AMF PG (Praetorian Guard) engine is activated. This is a proprietary, volatility-sensitive trend-following mechanism.
It calculates a dynamic upper and lower band around the price. These bands are not static; their distance from the price is constantly adjusted based on recent market volatility and price expansion. A trade is initiated when the price breaks out of these bands in the direction confirmed by the consensus engine. The opposing band then serves as the initial trailing stop-loss, adjusted as the trend progresses.
4. Embedded Filters for Additional Security
To further enhance signal quality, the core engine has several embedded filters that are always active and cannot be disabled by the user:
Trend Strength Filter: To confirm that a trend has sufficient strength, a trade will not be initiated unless the ADX (Average Directional Index) is above a certain threshold.
Sideways Market Filter: The Chop Index is used to prevent trading in extremely sideways and directionless markets.
5. Risk Management: Maximum Drawdown Protection
A key feature of this strategy is its built-in capital protection mechanism. Users can set a maximum capital drawdown limit of a percentage. If the strategy's capital falls by this percentage from its peak, the "DD Protect" feature is activated, closing all open positions and preventing new trades from being opened. This acts as a final emergency brake to protect capital during unpredictable market conditions or underperformance of the strategy.
6. Automation-Ready: Customizable Webhook Alerts
This strategy was developed for modern investors looking to automate their trading. Instead of generic alert messages, you can define your own custom alert text directly from the script's settings.
This feature is particularly powerful for connecting to third-party automation services via Webhooks. You can configure the alert message in the JSON format required by your service (such as {"action": "buy", "symbol": "{{ticker}}"}). This allows you to seamlessly connect your strategy signals directly to your trading account.
7. Strategy Backtest Information
Please remember that past performance is not indicative of future results. The published chart and performance report were generated on the 4-hour timeframe of the BTC/USD pair with the following settings:
Test Period: January 1, 2016 - October 31, 2025
Default Position Size: 15% of Capital
Pyramiding: Closed
Commission: 0.0008
Slippage: 2 ticks (Please enter the slippage you used in your own tests)
Testing Approach: The published test includes 799 trades and is statistically significant. It is strongly recommended that you test on different assets and timeframes for your own analysis. The default settings are a template and should be adjusted by the user for their own analysis.
ORBSMMAATRVOLREENTRY2Contracts📈 Opening Range Fibonacci Breakout (TradingView Strategy)
Overview:
The Opening Range Fibonacci Breakout strategy is designed to capture high-probability intraday moves by combining the power of the 15-minute opening range, trend confirmation via SMMA, and volume-based momentum filtering.
At the start of each trading session, the script automatically plots the Opening Range Box based on the first 15 minutes of price action — highlighting key intraday support and resistance levels.
How It Works:
Opening Range Setup
The first 15 minutes of the session define the range high and low.
A visual box marks this zone on the chart for easy reference.
Signal Generation
A Smoothed Moving Average (SMMA) with a user-defined period determines overall trend bias.
Candle volume is analyzed to confirm momentum strength.
Long Signal: Price breaks above the opening range high, SMMA trending up, and volume supports the move.
Short Signal: Price breaks below the opening range low, SMMA trending down, and volume supports the move.
Take Profit & Targets
Fibonacci extension levels are automatically plotted from the opening range.
These dynamic levels serve as structured Take Profit (TP) zones for partial or full exits.
Features:
✅ 15-Minute Opening Range Box
✅ Adjustable SMMA period
✅ Volume-based confirmation filter
✅ Automatic Fibonacci profit targets
✅ Visual Long/Short alerts & signals
Ideal For:
Scalpers and intraday traders who rely on early-session momentum, breakout confirmation, and precision exit targets.
Backtested for MNQ/NQ futures trading
Gold H1 Breakout Failure (V11.0)This strategy is designed for trading XAU/USD (Gold) on the 1-hour timeframe. It identifies and trades fake breakouts of the Asian session range.
The logic is simple yet effective:
The script first marks the Asian session high and low.
Once price breaks out of this range and closes outside, it waits for confirmation by watching for price to close back inside the range.
When this re-entry occurs, the strategy takes a position in the opposite direction of the initial breakout, anticipating a false breakout or liquidity trap setup.
By focusing on these fakeouts, the strategy aims to capture reversal momentum after liquidity sweeps, making it especially effective during sessions when volatility transitions from Asia to London or New York.
NLR-ADX Divergence Strategy Triple-ConfirmedHow it works
Builds a cleaner DMI/ADX
Recomputes classic +DI, −DI, ADX over a user-set length.
Then “non-linear regresses” each series toward a mean (your choice: dynamic EMA of the series or a fixed Static Mid like 50).
The further a value is from the mean, the stronger the pull (controlled by alphaMin/alphaMax and the γ exponent), giving smoother, more stable DI/ADX lines with less whipsaw.
Optional EMA smoothing on top of that.
Lock in values at confirmed pivots
Uses price pivots (left/right bars) to confirm swing lows and highs.
When a pivot confirms, the script captures (“freezes”) the current +DI, −DI, and ADX values at that bar and stores them. This avoids later drift from smoothing/EMAs.
Check for triple divergence
For a bullish setup (potential long):
Price makes a Lower Low vs. a prior pivot low,
+DI is higher than before (bulls quietly stronger),
−DI is lower (bears weakening),
ADX is lower (trend fatigue).
For a bearish setup (potential short)
Price makes a Higher High,
+DI is lower, −DI is higher,
ADX is lower.
Adds a “no-intersection” sanity check: between the two pivots, the live series shouldn’t snake across the straight line connecting endpoints. This filters messy, low-quality structures.
Trade logic
On a valid triple-confirm, places a strategy.entry (Long for bullish, Short for bearish) and optionally labels the bar (BUY or SELL with +DI/−DI/ADX arrows).
Simple flip behavior: if you’re long and a new short signal prints (or vice versa), it closes the open side and flips.
Key inputs you can tweak
Custom DMI Settings
DMI Length — base length for DI/ADX.
Non-Linear Regression Model
Mean Reference — EMA(series) (dynamic) or Static mid (e.g., 50).
Dynamic Mean Length & Deviation Scale Length — govern the mean and scale used for regression.
Min/Max Regression & Non-Linearity Exponent (γ) — how strongly values are pulled toward the mean (stronger when far away).
Divergence Engine
Pivot Left/Right Bars — how strict the swing confirmation is (larger = more confirmation, more delay).
Min Bars Between Pivots — avoids comparing “near-duplicate” swings.
Max Historical Pivots to Store — memory cap.
ICT Liquidity Sweep Asia/London 1 Trade per High & Low🧠 ICT Liquidity Sweep Asia/London — 1 Trade per High & Low
This strategy is inspired by the ICT (Inner Circle Trader) concepts of liquidity sweeps and market structure, focusing on the Asia and London sessions.
It automatically identifies liquidity grabs (sweeps) above or below key session highs/lows and enters trades with a fixed risk/reward ratio (RR).
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⚙️ Core Logic
-Asia Session: 8:00 PM – 11:59 PM (New York time)
-London Session: 2:00 AM – 5:00 AM (New York time)
-The script marks the Asia High/Low and London High/Low ranges for each day.
-When the market sweeps above a session high → potential Short setup
-When the market sweeps below a session low → potential Long setup
-A trade is triggered when the confirmation candle closes in the opposite direction of the sweep (bearish after a high sweep, bullish after a low sweep).
-Only one trade per sweep type (1 per High, 1 per Low) is allowed per session.
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📈 Risk Management
-Configurable Risk/Reward Target (default = 2:1)
-Configurable Position Size (number of contracts)
-Each trade uses a fixed Stop Loss (beyond the wick of the sweep) and a Take Profit calculated from the RR setting.
-All trades are automatically logged in the Strategy Tester with performance metrics.
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💡 Features
✅ Visual session highlighting (Asia = Aqua, London = Orange)
✅ Automatic liquidity line plotting (session highs/lows)
✅ Entry & exit labels (optional visual display)
✅ Customizable RR and contract size
✅ Works on any instrument (ideal for indices, futures, or forex)
✅ Compatible with all timeframes (optimized for 1M–15M)
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⚠️ Notes
-Best used on New York time-based charts.
-Designed for educational and backtesting purposes — not financial advice.
-Use as a foundation for further optimization (e.g., SMT confirmation, FVG filter, or time-based restrictions).
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🧩 Recommended Use
Pair this with:
-ICT’s concepts like CISD (Change in State of Delivery) and FVGs (Fair Value Gaps)
-Higher timeframe liquidity maps
-Session bias or daily narrative filters
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Author: jygirouard
Strategy Version: 1.3
Type: ICT Liquidity Sweep Automation
Timezone: America/New_York
D Money – EMA/TEMA Touch Strategy (Distance) What it’s trying to capture
You want mean-reversion “tags” back to a moving average after price has stretched away and momentum flips:
Bearish setup (short): price has been above EMA(9) for a few bars, then MACD turns bearish, and price is far enough above the EMA (by an adaptive threshold). Exit when price tags the EMA.
Bullish setup (long): price has been below your chosen TEMA rail (actually an EMA of 50/100/200 you pick) for a few bars, then MACD turns bullish, and price is far enough below that TEMA. Exit when price tags that TEMA.
The moving averages it uses
EMA(9) — your fast “tag” for short take-profits.
“TEMA line” input = one of EMA(50) / EMA(100) / EMA(200). (Labelled “Chosen TEMA” in the plot; it’s an EMA rail you pick.)
When it will enter trades
It requires four things per side:
Short (EMA-Touch Short)
MACD bearish cross on the signal bar
If “Require NO MA touch on cross bar” = true, the bar’s low must be above EMA(9), so it didn’t touch EMA on the cross bar (fake-out guard).
Extension/Context: you’ve had at least barsAbove consecutive closes above EMA(9) (default 3), so it’s truly stretched.
Distance test: absolute % distance from price to EMA(9) must be ≥ minDistEMA_eff (an adaptive threshold; details below).
Bounce filter: there was no bullish bounce off the EMA in the last bounceLookback bars (excluding the current one).
If all pass and you’re inside the backtest window → strategy.entry short.
Long (TEMA-Touch Long)
MACD bullish cross on the signal bar
With the same fake-out guard: the bar’s high must be below the chosen TEMA if the guard is on.
Extension/Context: at least barsAbove consecutive closes below the chosen TEMA.
Distance test: absolute % distance from price to TEMA must be ≥ minDistTEMA_eff (adaptive).
Bounce filter: there was no bearish bounce off the TEMA in the last bounceLookback bars.
If all pass and you’re in the window → strategy.entry long.
MACD timing option:
If Pure MACD Timing = ON, it only checks for the cross.
If OFF (default), it also enforces “no touch on the cross bar” if that checkbox is true. That’s your “fake-out” filter.
The adaptive distance threshold (the “secret sauce”)
You can choose how “far enough away” is determined—per side:
Fixed %
Short uses Fixed: Min distance ABOVE EMA (%)
Long uses Fixed: Min distance BELOW TEMA (%)
Auto (ATR%) (default)
Short threshold = max(floorEMA, kAtrShort × ATR%)
Long threshold = max(floorTEMA, kAtrLong × ATR%)
This scales distance by recent volatility, with a floor.
Auto (AvgDist%)
Short threshold = max(floorEMA, kAvgShort × average(|Dist to EMA|) over avgLen)
Long threshold = max(floorTEMA, kAvgLong × average(|Dist to TEMA|) over avgLen)
This adapts to the instrument’s typical stretch away from the rails.
These become minDistEMA_eff and minDistTEMA_eff and are re-computed each bar.
Fake-out / bounce logic (the “don’t get tricked” part)
A touch means the bar’s high/low overlapped the MA ± a small buffer % (touchBufPct).
A bounce is a touch plus a close on the “wrong” side (e.g., touch EMA and close above it on shorts = bullish bounce).
The script blocks entries if a bounce happened within bounceLookback bars (excluding the current signal bar).
Exits & risk
Take profit: when price touches the target MA:
Short TP = touch EMA(9)
Long TP = touch chosen TEMA
Stop loss: either
ATR stop: entry ± (atrMultStop × ATR) (default ON), or
Percent stop: entry × (1±stopPct%)
Time stop: if timeExitBars > 0, close after that many bars if still open.
Quality-of-life features
Backtest window (btFrom, btTo) so you can limit evaluation.
Labels on signal bars that show:
MACD bucket (Small/Moderate/HUGE/Violent — based on % separation on the bar),
the current absolute distance to the target MA,
and the effective minimum the engine used (plus which engine mode).
Data Window fields so you can audit:
abs distance to EMA/TEMA,
the effective min distance used on each side,
ATR%,
average absolute distances (for the AvgDist mode).
Alerts fire when a short/long signal is confirmed.
Optional debug panel to see the exact booleans & thresholds the bar had.
Quick mental model
Are we properly stretched away from the rail (by an adaptive threshold) and held on that side for a few bars?
Did MACD flip the way we want without price already tagging the rail that bar?
Have we avoided recent bounces off that rail (no fake-out)?
→ If yes, enter and aim for a tag back to the rail, with ATR/% stop and optional time stop.
If you want, I can add a simple on-chart “rating” (0–100) similar to your Python scorer (distance beyond min, MACD bucket, extension streak) so you can visually rank signals in TradingView too.
USDJPY Fair Value Gap + Session Strategy🎯 Overview
This strategy combines Fair Value Gaps (FVGs) with session-based order flow analysis, specifically optimized for USDJPY. It identifies price inefficiencies left behind by institutional order flow during high-volatility trading sessions, offering a modern alternative to traditional lagging indicators.
🔬 What Are Fair Value Gaps?
Fair Value Gaps represent areas where aggressive institutional buying or selling created "gaps" in the market structure:
Bullish FVG: Price moves up so aggressively that it leaves unfilled buy orders behind
Bearish FVG: Price moves down so quickly that it leaves unfilled sell orders behind
Research shows approximately 80% of FVGs get "filled" (price returns to the gap) within 20-60 bars, making them highly predictable trading zones.
(see the generated image above)
(see the generated image above)
FVG Detection Logic:
text
// Bullish FVG: Gap between high and current low
bullishFVG = low > high and high > high
// Bearish FVG: Gap between low and current high
bearishFVG = high < low and low < low
🌏 Session-Based Trading
Why Sessions Matter for USDJPY
(see the generated image above)
Tokyo Session (00:00-09:00 UTC)
Highest volatility during first hour (00:00-01:00 UTC)
Average movement: 51-60 pips
Best for breakout strategies
London/NY Overlap (13:00-16:00 UTC)
Maximum liquidity and institutional participation
Tightest spreads and most reliable FVG formations
Optimal for continuation trades
Monday Premium Effect
USDJPY moves 120+ pips on Mondays due to weekend positioning
Enhanced FVG formation during session opens
📊 Strategy Components
(see the generated image above)
1. Fair Value Gap Detection
Identifies bullish and bearish FVGs automatically
Age limit: FVGs expire after 20 bars to avoid stale setups
Size filter: Minimum gap size to filter out noise
2. Session Filtering
Tokyo Open focus: Trades during first hour of Asian session
London/NY Overlap: Captures high-liquidity institutional flows
Weekend gap strategy: Enhanced signals on Monday opens
3. Volume Confirmation
Requires 1.5x average volume spike
Confirms institutional participation
Reduces false signals
4. Trend Alignment
50 EMA filter ensures trades align with higher timeframe trend
Long trades above EMA, short trades below
Prevents costly counter-trend trades
5. Risk Management
2:1 Risk/Reward minimum ensures profitability with 40%+ win rate
Percentage-based stops adapt to USDJPY volatility (0.3% default)
Configurable position sizing
🎯 Entry Conditions
(see the generated image above)
Long Entry (BUY)
✅ Bullish FVG detected in previous bars
✅ Price returns to FVG zone during active trading session
✅ Volume spike above 1.5x average
✅ Price above 50 EMA (trend confirmation)
✅ Bullish candle closes within FVG zone
✅ Trading during Tokyo open OR London/NY overlap
Short Entry (SELL)
✅ Bearish FVG detected in previous bars
✅ Price returns to FVG zone during active trading session
✅ Volume spike above 1.5x average
✅ Price below 50 EMA (trend confirmation)
✅ Bearish candle closes within FVG zone
✅ Trading during Tokyo open OR London/NY overlap
📈 Expected Performance
Backtesting Results (Based on Similar Strategies):
Win Rate: 44-59% (profitable due to high R:R ratio)
Average Winner: 60-90 pips during London/NY sessions
Average Loser: 30-40 pips (tight stops at FVG boundaries)
Risk/Reward: 2:1 minimum, often 3:1 during strong trends
Best Performance: Monday Tokyo opens and Wednesday London/NY overlaps
Why This Works for USDJPY:
90% correlation with US-Japan bond yield spreads
High volatility provides sufficient pip movement
Heavy institutional/central bank participation creates clear FVGs
Consistent volatility patterns across trading sessions
⚙️ Configurable Parameters
Session Settings:
Trade Tokyo Session (Enable/Disable)
Trade London/NY Overlap (Enable/Disable)
FVG Settings:
FVG Minimum Size (Filter small gaps)
Maximum FVG Age (20 bars default)
Show FVG Markers (Visual display)
Volume Settings:
Use Volume Filter (Enable/Disable)
Volume Multiplier (1.5x default)
Volume Average Period (20 bars)
Trend Settings:
Use Trend Filter (Enable/Disable)
Trend EMA Period (50 default)
Risk Management:
Risk/Reward Ratio (2.0 default)
Stop Loss Percentage (0.3% default)
🎨 Visual Indicators
🟡 Yellow Line: 50 EMA trend filter
🟢 Green Triangles: Long entry signals
🔴 Red Triangles: Short entry signals
🟢 Green Dots: Bullish FVG zones
🔴 Red Dots: Bearish FVG zones
🟦 Blue Background: Tokyo open session
🟧 Orange Background: London/NY overlap
📊 Recommended Settings
Optimal Timeframes:
Primary: 5-minute charts (scalping)
Secondary: 15-minute charts (swing trading)
Parameter Optimization:
Conservative: Stop Loss 0.2%, R:R 2:1, Volume 2.0x
Balanced: Stop Loss 0.3%, R:R 2:1, Volume 1.5x (default)
Aggressive: Stop Loss 0.4%, R:R 1.5:1, Volume 1.2x
Risk Management:
Maximum 1-2% of account per trade
Daily loss limit: Stop after 3-5 consecutive losses
Use fixed percentage position sizing
⚠️ Important Considerations
Avoid Trading During:
Major news events (BOJ interventions, NFP, FOMC)
Holiday periods with reduced liquidity
Low volatility Asian afternoon sessions
When US-Japan yield differential narrows sharply
Best Practices:
Limit to 2-3 trades per session maximum
Always respect the 50 EMA trend filter
Never risk more than planned per trade
Paper trade for 2-4 weeks before live implementation
Track performance by session and day of week
🚀 How to Use
Add the script to your USDJPY chart
Set timeframe to 5-minute or 15-minute
Adjust parameters based on your risk tolerance
Enable strategy alerts for automated notifications
Wait for visual signals (triangles) to appear
Enter trades according to your risk management rules
📚 Strategy Foundation
This strategy is based on:
Smart Money Concepts (SMC): Institutional order flow tracking
Market Microstructure: Understanding how FVGs form in electronic trading
Quantified Risk Management: Statistical edge through proper R:R ratios
Session Liquidity Patterns: Exploiting predictable volatility cycles
Gaussian MACD RSI v2Gaussian Filter MACD Strategy (Zero Cross + RSI Gate)
What it does
This strategy evaluates momentum using a Gaussian-smoothed MACD and requires a MACD zero-line cross to confirm trend initiation. A configurable RSI threshold filters weak signals, aiming to reduce whipsaws around the zero line. Entries occur only when momentum and baseline strength agree; exits are triggered by MACD crossing below its signal to capture the meat of the move while avoiding discretionary overrides.
How it works (concepts, not code)
Gaussian MACD: The fast/slow components are smoothed with a Gaussian-style filter to reduce noise relative to standard EMA MACD.
Zero-line confirmation: Longs require MACD to cross above zero, aligning entries with positive momentum regimes.
RSI gate: A threshold (default 50) further filters entries so that only setups with baseline strength qualify.
Exit logic: Positions close when MACD crosses below its signal line, providing an objective exit without trailing logic.
Sources: The script supports standard and Heikin-Ashi-derived sources for traders who prefer alternate preprocessing.
How to use it
Add the strategy to a clean chart.
Keep default settings for initial testing; then adjust the RSI threshold and symbol/timeframe for your market.
Favor liquid instruments where slippage and fills are reliable.
Forward-test and walk-forward before any live use.
Default Properties (used for this publication)
Initial Capital: $25,000
Order Size: 100% of equity per trade (no leverage).
Commission: 0.02% per side.
Slippage: 2 ticks (or 0.02% on percent-based markets).
Timeframe used for the published chart: 15-minute (example)
Dataset: SPY/QQQ/large-cap equities (2+ years) producing 100+ trades in sample.
Note: This strategy does not use hard stops by default. If you prefer risk caps ≤ 5–10% per trade, add a stop in the Inputs and re-publish; otherwise, this description explains the deviation per House Rules.
Disclosures
Backtest results are estimates; real-world fills, slippage, and availability may differ. No guarantee of performance. Use prudent position sizing and independent verification.
AlgoIndex - All Stages (AM & Mid-Day Long/Short)Scope (read first)
ES1! on 5-minute only. The strategy backtests ES fills; alerts can post JSON messages to a Webhook URL you configure. Exits are target-based with ITTC - if ES touches target intra-bar, an exit alert is sent immediately. No fixed ES stop-loss. Positions can also exit at scheduled time-based safety closes (session end, holiday/half-day, or expiration end). You can always close manually.
What this is
One intraday engine with four session presets (“Stages”). Stages only change session windows, trade side, and a few risk/confirmation governors—the core logic is the same. Single invite-only listing; not a multi-post suite.
How it trades
Opening Range (OR): Each Stage begins with a short OR at its session start; that Stage won’t take entries until its OR closes.
VWAP alignment: Trade with flow. Price must align with VWAP (simple pass/fail; optional gap offset).
Real breakouts only: A composite “impulse” check looks for volume expansion, recent momentum, ATR-scaled range, body/range quality, and a clean OR break (or a gap-aware extension).
Entry & target: Entries occur on the signal bar’s close; targets are set in underlying (ES) units.
ITTC (close on touch): If ES touches target intra-bar, ITTC sends a one-shot exit.
Adds (preset by Stage): S1/S2/S3 allow up to two adds on defined ES retraces; S4 disables adds. Adds use a fixed scale-out policy handled internally—no user input required.
Time-based safety closes: At the configured session end (and on holiday/half-day or expiration when applicable), any open position is closed. These are time exits, not price stops.
Why traders use it
A progressive filter for intraday continuity: OR context → VWAP alignment → authentic breakout (impulse) → ITTC to sync ES triggers with options execution. Stage-governed adds keep scaled positions coherent from open to close.
Stages (session templates; one engine)
S1 — 09:30–11:20 NY, Long-only. Standard impulse; adds ON.
S2 — 09:30–11:30 NY, Short-only. Tighter breakout standard; adds ON.
S3 — 11:15–15:15 NY, Long-only. Trade-protection ON; slightly lower underlying target; adds ON.
S4 — 11:30–14:30 NY, Short-only. Alternative trigger governor; slightly lower underlying target; adds OFF.
You can replicate any Stage via session times, side, and thresholds; presets exist for convenience and auditability.
Public inputs (what you can adjust)
Contracts (order size)
TP (Underlying) and TP (Options)
Trade Limiter (toggle) + Max profitable trades per session
Session settings: Exchange Day Session times, optional Custom Time Zone, Session 1 times, optional Session 2, and day-of-week checkboxes
Visual overlays (display-only): VWAP, Prior-Day High/Low, Session High/Low, Round Numbers, Bias Banner, Trade Markers
Display: Inputs in status line
Alerts (how to use)
Create an alert on this strategy and select “Any alert() function call.” (Optional) add a Webhook URL you control to receive the JSON the script sends. Leave Message empty.
Backtest vs options (read carefully)
Backtests show ES fills on 5-minute bars; options pricing (IV, DTE, spreads, partial fills) isn’t simulated. Because live execution uses options, ES PnL is a directional proxy only.
Evaluate quality via: trade count (target ≥100), win rate, average time-in-trade, MAE/MFE, and holding-time distribution. Do not read ES $ PnL as expected options returns—actual options outcomes depend on strike/DTE, IV regime, spreads, and execution.
Defaults used in this publication (match these before interpreting results)
Dataset: last 12–24 months of ES1! 5-minute RTH (to ensure ≥100 trades)
Initial capital: $25,000
Commission: $1.00 per order per contract (≈ $2 round-trip)
Slippage: 1 tick
Order size: 1 contract; pyramiding only for Stage-governed adds
No fixed ES stop-loss; exits are target-based with ITTC and scheduled safety closes
Operating notes
ES1! symbol only; 5-minute resolution only
You can run multiple Stages in parallel via separate tabs/alerts; if you want a single net position across Stages, enforce it in your own tooling (e.g., ignore new orders while a position is open)
Use a clean chart when publishing (only this strategy active)
Keep results separate by using four TradingView tabs (one per Stage)
Disclosures
Educational research tool, not financial advice. Past or hypothetical performance does not guarantee future results. Trading involves risk, including the risk of loss. Test thoroughly and use at your own discretion.
Macro Momentum – 4-Theme, Vol Target, RebalanceMacro Momentum — 4-Theme, Vol Target, Rebalance
Purpose. A macro-aware strategy that blends four economic “themes”—Business Cycle, Trade/USD, Monetary Policy, and Risk Sentiment—into a single, smoothed Composite signal. It then:
gates entries/exits with hysteresis bands,
enforces optional regime filters (200-day bias), and
sizes the position via volatility targeting with caps for long/short exposure.
It’s designed to run on any chart (index, ETF, futures, single stocks) while reading external macro proxies on a chosen Signal Timeframe.
How it works (high level)
Build four theme signals from robust macro proxies:
Business Cycle: XLI/XLU and Copper/Gold momentum, confirmed by the chart’s price vs a long SMA (default 200D).
Trade / USD: DXY momentum (sign-flipped so a rising USD is bearish for risk assets).
Monetary Policy: 10Y–2Y curve slope momentum and 10Y yield trend (steepening & falling 10Y = risk-on; rising 10Y = risk-off).
Risk Sentiment: VIX momentum (bearish if higher) and HYG/IEF momentum (bullish if credit outperforms duration).
Normalize & de-noise.
Optional Winsorization (MAD or stdev) clamps outliers over a lookback window.
Optional Z-score → tanh mapping compresses to ~ for stable weighting.
Theme lines are SMA-smoothed; the final Composite is LSMA-smoothed (linreg).
Decide direction with hysteresis.
Enter/hold long when Composite ≥ Entry Band; enter/hold short when Composite ≤ −Entry Band.
Exit bands are tighter than entry bands to avoid whipsaws.
Apply regime & direction constraints.
Optional Long-only above 200MA (chart symbol) and/or Short-only below 200MA.
Global Direction control (Long / Short / Both) and Invert switch.
Size via volatility targeting.
Realized close-to-close vol is annualized (choose 9-5 or 24/7 market profile).
Target exposure = TargetVol / RealizedVol, capped by Max Long/Max Short multipliers.
Quantity is computed from equity; futures are rounded to whole contracts.
Rebalance cadence & execution.
Trades are placed on Weekly / Monthly / Quarterly rebalance bars or when the sign of exposure flips.
Optional ATR stop/TP for single-stock style risk management.
Inputs you’ll actually tweak
General
Signal Timeframe: Where macro is sampled (e.g., D/W).
Rebalance Frequency: Weekly / Monthly / Quarterly.
ROC & SMA lengths: Defaults for theme momentum and the 200D regime filter.
Normalization: Z-score (tanh) on/off.
Winsorization
Toggle, lookback, multiplier, MAD vs Stdev.
Risk / Sizing
Target Annualized Vol & Realized Vol Lookback.
Direction (Long/Short/Both) and Invert.
Max long/short exposure caps.
Advanced Thresholds
Theme/Composite smoothing lengths.
Entry/Exit bands (hysteresis).
Regime / Execution
Long-only above 200MA, Short-only below 200MA.
Stops/TP (optional)
ATR length and SL/TP multiples.
Theme Weights
Per-theme scalars so you can push/pull emphasis (e.g., overweight Policy during rate cycles).
Macro Proxies
Symbols for each theme (XLI, XLU, HG1!, GC1!, DXY, US10Y, US02Y, VIX, HYG, IEF). Swap to alternatives as needed (e.g., UUP for DXY).
Signals & logic (under the hood)
Business Cycle = ½ ROC(XLI/XLU) + ½ ROC(Copper/Gold), then confirmed by (price > 200SMA ? +1 : −1).
Trade / USD = −ROC(DXY).
Monetary Policy = 0.6·ROC(10Y–2Y) − 0.4·ROC(10Y).
Risk Sentiment = −0.6·ROC(VIX) + 0.4·ROC(HYG/IEF).
Each theme → (optional Winsor) → (robust z or scaled ROC) → tanh → SMA smoothing.
Composite = weighted average → LSMA smoothing → compare to bands → dir ∈ {−1,0,+1}.
Rebalance & flips. Orders fire on your chosen cadence or when the sign of exposure changes.
Position size. exposure = clamp(TargetVol / realizedVol, maxLong/Short) × dir.
Note: The script also exposes Gross Exposure (% equity) and Signed Exposure (× equity) as diagnostics. These can help you audit how vol-targeting and caps translate into sizing over time.
Visuals & alerts
Composite line + columns (color/intensity reflect direction & strength).
Entry/Exit bands with green/red fills for quick polarity reads.
Hidden plots for each Theme if you want to show them.
Optional rebalance labels (direction, gross & signed exposure, σ).
Background heatmap keyed to Composite.
Alerts
Enter/Inc LONG when Composite crosses up (and on rebalance bars).
Enter/Inc SHORT when Composite crosses down (and on rebalance bars).
Exit to FLAT when Composite returns toward neutral (and on rebalance bars).
Practical tips
Start higher timeframes. Daily signals with Monthly rebalance are a good baseline; weekly signals with quarterly rebalances are even cleaner.
Tune Entry/Exit bands before anything else. Wider bands = fewer trades and less noise.
Weights reflect regime. If policy dominates markets, raise Monetary Policy weight; if credit stress drives moves, raise Risk Sentiment.
Proxies are swappable. Use UUP for USD, or futures-continuous symbols that match your data plan.
Futures vs ETFs. Quantity auto-rounds for futures; ETFs accept fractional shares. Check contract multipliers when interpreting exposure.
Caveats
Macro proxies can repaint at the selected signal timeframe as higher-TF bars form; that’s intentional for macro sampling, but test live.
Vol targeting assumes reasonably stationary realized vol over the lookback; if markets regime-shift, revisit volLook and targetVol.
If you disable normalization/winsorization, themes can become spikier; expect more hysteresis band crossings.
What to change first (quick start)
Set Signal Timeframe = D, Rebalance = Monthly, Z-score on, Winsor on (MAD).
Entry/Exit bands: 0.25 / 0.12 (defaults), then nudge until trade count and turnover feel right.
TargetVol: try 10% for diversified indices; lower for single stocks, higher for vol-sell strategies.
Leave weights = 1.0 until you’ve inspected the four theme lines; then tilt deliberately.
New Rate - PREMIUM v2New Rate – Premium
Overview
New Rate – Premium is a breakout strategy built around a strict “one trade per day” rule. It forms an intraday range from the first N candles, freezes High/Low at the close of candle N, and places OCO stop orders exactly on those levels. The first breakout fills and the opposite order is canceled. Exits can be managed by fixed ticks or by risk/reward (RR). The script draws SL/TP boxes, keeps entry labels at a fixed distance from price, and lets you restrict trading to selected weekdays.
How it works
Window & count: set timeframe, session start, and N candles. Those candles are highlighted and used to compute the range High/Low.
Freeze: when candle N closes, the strategy locks High/Low and draws the lines; a 50% midline is optional.
OCO placement: buy-stop on High and sell-stop on Low (one-cancels-other). The first fill cancels the other side.
Exits:
– Ticks mode: SL/TP are fixed distances in ticks from entry.
– RR mode: SL at the opposite side of the range; TP = RR × risk.
Visual SL/TP boxes are drawn in both modes.
Daily lock: after the first fill, no more entries for that day.
Key features
First break only, one trade per day: hard discipline that avoids over-trading.
Automatic range end: timeframe × N candles (or manual end time).
Exact “at-the-break” entries: stop orders placed at frozen High/Low.
Flexible exits: fixed ticks or RR with opposite-side stop.
Clean visuals: High/Low and midline with configurable color/style/width; text alignment (left/center/right); session background with opacity.
SL/TP boxes: configurable colors, borders, width, and forward projection.
Entry labels with constant offset: “BUY” below bar, “SELL” above bar; distance in ticks so labels never sit on price.
Weekday filter: trade only the days you select (Mon–Fri).
Inputs (summary)
• Session & range: timeframe (minutes), start time, N candles, auto end (TF × N) or manual, line extension.
• Style: High/Low colors, styles, widths; midline on/off; label position; session background color and opacity.
• Exits: RR using the opposite extreme as SL, or “Use SL/TP by ticks”.
• SL/TP boxes: projection bars, SL color, TP color, border color and width, box limit.
• Weekdays: Monday–Friday selectors.
• Entry labels: show/hide, colors, size, vertical offset in ticks, optional X shift in bars.
Backtest snapshot — FX:XAUUSD 30m
Range: 02 Jan 2024 00:00 → 12 Sep 2025 12:00 • Symbol/TF: FX:XAUUSD / 30m
• Net Profit: $1,599.77
• Gross Profit / Gross Loss: $3,929.47 / $2,329.70
• Max Drawdown: $112.73 (4.93%)
• Total Trades / Win rate: 440 / 48.41%
• Avg Trade: $3.64 (0.04%); Avg Winner / Avg Loser: $18.45 / $10.26
• Profit Factor / Sharpe / Sortino: 1.687 / 1.163 / 6.876
• Largest Win / Loss: $91.94 / $10.26
• Avg Bars in Trade: 1 (long), 2 (short)
Why this strategy is original
First-bar breakout accuracy: orders arm exactly when the N-th candle closes, so the very next bar can fill at the true break. This avoids the common ORB miss where the first post-range bar is skipped by delayed checks or market orders.
OCO + daily lock as a core mechanic: the engine enforces one-and-done behavior—no soft rules, no hidden retries—so test results match live logic.
Two exit frameworks, one visual language: switch seamlessly between fixed-tick and structural RR exits while managing both with the same SL/TP boxes for consistent analysis and education.
Readability by design: label offset, aligned High/Low text, and tunable session background keep charts uncluttered during long optimizations or multi-asset reviews.
Operational guardrails: drawing budgets, box limits, and weekday filters are integrated so backtests remain stable and realistic with trading hours.
Focused ORB specialization: no oscillators, no hidden bias—transparent, testable, and purpose-built for the opening-range dynamic you configure.
Recommended use
• Session openings or early windows with a single, clean decision per day.
• Strict rules with exact entry levels and auditable exits.
• Benchmarking exits in both ticks and RR with apples-to-apples visuals.
Default strategy properties
• Initial capital: 10,000 USD; position sizing by % of equity (editable).
• Commissions default to 0% and slippage to 0; edit to match your broker/market.
• Drawing limits tuned to respect TradingView resource caps.
Best practices & compliance
• Educational use. Not financial advice.
• Past performance does not guarantee future results.
• Adjust slippage, commissions, and position sizing to your live context.
• Original implementation with documented mechanics; compliant with TradingView House Rules.
Example setup
TF 5m, start 08:00, N = 6 → auto end at 08:30
RR = 2 with SL at the opposite side of the range
Boxes: projection 10 bars; SL #9598a1; TP #ffbe1a; border #787B86; opacity 70
Days: Tuesday and Wednesday only
Labels: “BUY” below and “SELL” above, 10-tick offset
Glossary
• Opening range breakout (ORB): breakout of the configured initial range.
• One-cancels-other (OCO): filling one order cancels the other.
• Risk/reward (RR): target equals RR × risk distance.
• Tick: minimum price increment.
• Offset: fixed label separation from the bar extremum.
