US Market Long Horizon Momentum Summary in one paragraph
US Market Long Horizon Momentum is a trend following strategy for US index ETFs and futures built around a single eighteen month time series momentum measure. It helps you stay long during persistent bull regimes and step aside or flip short when long term momentum turns negative.
Scope and intent
• Markets. Large cap US equity indices, liquid US index ETFs, index futures
• Timeframes. 4h/ Daily charts
• Default demo used in the publication. SPY on 4h timeframe chart
• Purpose. Provide a minimal long bias index timing model that can reduce deep drawdowns and capture major cycles without parameter mining
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. One unscaled multiple month log return of an external benchmark symbol drives all entries and exits, with optional volatility targeting as a single risk control switch.
• Failure mode addressed. Fully passive buy and hold ignores the sign of long horizon momentum and can sit through multi year drawdowns. This script offers a way to step down risk in prolonged negative momentum without chasing short term noise.
• Testability. All parameters are visible in Inputs and the momentum series is plotted so users can verify every regime change in the Tester and on price history.
• Portable yardstick. The log return over a fixed window is a unit that can be applied to any liquid symbol with daily data.
Method overview in plain language
The method looks at how far the benchmark symbol has moved in log return terms over an eighteen month window in our example. If that long horizon return is positive the strategy allows a long stance on the traded symbol. If it is negative and shorts are enabled the strategy can flip short, otherwise it goes flat. There is an optional realised volatility estimate on the traded symbol that can scale position size toward a target annual volatility, but in the default configuration the model uses unit leverage and only the sign of momentum matters.
Base measures
Return basis. The core yardstick is the natural log of close divided by the close eighteen months ago on the benchmark symbol. Daily log returns of the traded symbol feed the realised volatility estimate when volatility targeting is enabled.
Components
• Component one Momentum eighteen months. Log of benchmark close divided by its close mom_lookback bars ago. Its sign defines the trend regime. No extra smoothing is applied beyond the long window itself.
• Component two Realised volatility optional. Standard deviation of daily log returns on the traded symbol over sixty three days. Annualised by the square root of 252. Used only when volatility targeting is enabled.
• Optional component Volatility targeting. Converts target annual volatility and realised volatility into a leverage factor clipped by a maximum leverage setting.
Fusion rule
The model uses a simple gate. First compute the sign of eighteen month log momentum on the benchmark symbol. Optionally compute leverage from volatility. The sign decides whether the strategy wants to be long, short, or flat. Leverage only rescales position size when enabled and does not change direction.
Signal rule
• Long suggestion. When eighteen month log momentum on the benchmark symbol is greater than zero, the strategy wants to be long.
• Short suggestion. When that log momentum is less than zero and shorts are allowed, the strategy wants to be short. If shorts are disabled it stays flat instead.
• Wait state. When the log momentum is exactly zero or history is not long enough the strategy stays flat.
• In position. In practice the strategy sits IN LONG while the sign stays positive and flips to IN SHORT or flat only when the sign changes.
Inputs with guidance
Setup
• Momentum Lookback (months). Controls the horizon of the log return on the benchmark symbol. Typical range 6 to 24 months. Raising it makes the model slower and more selective. Lowering it makes it more reactive and sensitive to medium term noise.
• Symbol. External symbol used for the momentum calculation, SPY by default. Changing it lets you time other indices or run signals from a benchmark while trading a correlated instrument.
Logic
• Allow Shorts. When true the strategy will open short positions during negative momentum regimes. When false it will stay flat whenever momentum is negative. Practical setting is tied to whether you use a margin account or an ETF that supports shorting.
Internal risk parameters (not exposed as inputs in this version) are:
• Target Vol (annual). Target annual volatility for volatility targeting, default 0.2.
• Vol Lookback (days). Window for realised volatility, default 63 trading days.
• Max Leverage. Cap on leverage when volatility targeting is enabled, default 2.
Usage recipes
Swing continuation
• Signal timeframe. Use the daily chart.
• Benchmark symbol. Leave at SPY for US equity index exposure.
• Momentum lookback. Eighteen months as a default, with twelve months as an alternative preset for a faster swing bias.
Properties visible in this publication
• Initial capital. 100000
• Base currency. USD
• Default order size method. 5% of the total capital in this example
• Pyramiding. 0
• Commission. 0.03 percent
• Slippage. 3 ticks
• Process orders on close. On
• Bar magnifier. Off
• Recalculate after order is filled. Off
• Calc on every tick. Off
• All request.security calls use lookahead = barmerge.lookahead_off
Realism and responsible publication
The strategy is for education and research only. It does not claim any guaranteed edge or future performance. All results in Strategy Tester are hypothetical and depend on the data vendor, costs, and slippage assumptions. Intrabar motion is not modeled inside daily bars so extreme moves and gaps can lead to fills that differ from live trading. The logic is built for standard candles and should not be used on synthetic chart types for execution decisions.
Performance is sensitive to regime structure in the US equity market, which may change over time. The strategy does not protect against single day crash risk inside bars and does not model gap risk explicitly. Past behavior of SPY and the momentum effect does not guarantee future persistence.
Honest limitations and failure modes
• Long sideways regimes with small net change over eighteen months can lead to whipsaw around the zero line.
• Very sharp V shaped reversals after deep declines will often be missed because the model waits for momentum to turn positive again.
• The sample size in a full SPY history is small because regime changes are infrequent, so any test must be interpreted as indicative rather than statistically precise.
• The model is highly dependent on the chosen lookback. Users should test nearby values and validate that behavior is qualitatively stable.
Legal
Education and research only. Not investment advice. You are responsible for your own decisions. Always test on historical data and in simulation with realistic costs before any live use.
Pesquisar nos scripts por "range"
Adaptive Alligator - Asymmetric MH (Entry Only)
Adaptive Alligator – Asymmetric Mexican Hat (Entry Only)
This strategy combines adaptive cycle detection (wavelet + autocorrelation), directional entropy, and a Mexican Hat filter to generate highly selective LONG entry signals. Exits are based solely on the Alligator structure. The system is designed to detect asymmetric, strong, and accelerating bullish phases while filtering out market noise.
1. Adaptive Cycle Detection: The strategy analyzes the median price using wavelet decomposition (Haar, Daubechies D4/D6, Symlet 4), wavelet detail energy, and autocorrelation. It also incorporates the ratio of short-term to long-term ATR volatility. Based on these components, it computes a dominant_cycle value, which dynamically controls the lengths of the Alligator lines (Jaw, Teeth, Lips). This adaptive behavior allows the Alligator to speed up during trending phases and slow down during noise or consolidation.
2. Directional Entropy: Entropy is measured separately for upward and downward movements within the selected lookback window. The entropy difference: e_diff = entropy_down - entropy_up represents the directional bias of the market. When e_diff > 0, the market shows an organized bullish pressure; when < 0, bearish dominance.
3. Mexican Hat Filter: The Mexican Hat (Ricker Wavelet) acts as a second-derivative filter, detecting local maxima in the acceleration of directional entropy. The filtered output (mh_out) is compared against an adaptive noise level computed as SMA(|mh_out|). A signal is considered strong only when: – mh_out exceeds the adaptive noise level, – mh_out is rising relative to the previous bar. This step is critical for eliminating false signals produced by random fluctuations.
4. Entry Logic: A LONG entry requires all three layers: (1) Alligator structure: Lips > Teeth > Jaw. (2) Directional entropy bias: e_diff > 0. (3) A strong, accelerating Mexican Hat signal confirmed by a user-defined number of bars. Once all conditions are satisfied, a buy_final entry is triggered.
5. Exit Logic: Exits are intentionally simple and rely solely on the Alligator: crossunder(lips, teeth) This clean separation ensures precise, adaptive entries and stable, consistent exits.
6. Visual Components: – Alligator lines: Jaw (blue), Teeth (red), Lips (green), plotted with their characteristic offsets. – Background coloring reflects signal strength: dark green (STRONG BUY), lime (acceleration), yellow (weak bias), transparent otherwise. – A dedicated panel displays e_diff (entropy difference), mh_out (Mexican Hat output), and the adaptive noise band.
7. Diagnostic Table: A compact diagnostic dashboard shows: – MH Value, – Noise Level, – MH Acceleration (YES/NO), – Signal Status (STRONG BUY / ACCELERATING / WEAK / BEARISH). It updates on the last bar, making it suitable for live monitoring.
8. Use Case: This strategy is highly selective and ideal as an entry module within trend-following systems. By combining wavelets, entropy, and adaptive noise modeling, it effectively filters out consolidation periods and focuses only on statistically significant bullish transitions. It can be integrated with various exit frameworks such as ATR stops, channel-based exits, range boxes, or trailing logic.
Estrategia Trend Following: 52w/26w BreakoutThis is a classic long-term Trend Following strategy, heavily inspired by the Donchian Channel system and the legendary "Turtle Trading" rules. It is designed to capture major market moves (bull runs) while filtering out short-term market noise and volatility.
This script is ideal for investors and swing traders who prefer a "hands-off" approach, looking to catch large trends rather than day-trading small fluctuations.
How it Works:
1. Entry Condition (The Breakout):
52-Week High: The strategy enters a Long position when the price breaks above the highest high of the last 252 trading days (approx. 1 year).
SuperTrend Filter: An additional filter using the SuperTrend indicator ensures that the breakout is supported by positive momentum, helping to reduce false signals during choppy lateral markets.
2. Exit Condition (The Trailing Stop):
26-Week Low: The strategy ignores short-term corrections. It only closes the position if the price closes below the lowest low of the last 126 trading days (approx. 6 months).
This wide stop allows the trade to "breathe" and stay open during significant pullbacks, ensuring you stay in the trend for as long as possible.
Features & Settings:
Customizable Lookback Periods: You can adjust the Entry (default 252 days) and Exit (default 126 days) periods in the settings menu.
Visual Aids:
Blue Line: Represents the 1-Year High (Entry Threshold).
Red Line: Represents the 6-Month Low (Dynamic Stop Loss).
Channel Shading: Visualizes the trading range between the high and low.
Labels: Clearly marks "BUY" and "EXIT" points on the chart.
Recommended Usage:
Timeframe: Daily (1D). This logic is designed for daily candles.
Assets: Works best on assets with strong trending characteristics (e.g., Bitcoin/Crypto, Tech Stocks, Indices like SPX/NDX, and Commodities).
Patience Required: This strategy generates very few signals. It may stay quiet for months and then hold a position for over a year.
Nifty 10m Simple ORB TEST harish//@version=5
strategy("Nifty 10m Simple ORB TEST", overlay=true)
// 10m timeframe check
if timeframe.period != "10"
runtime.error("Use this on 10 minute timeframe")
// First 10m candle high/low (no PCR, no opposite logic – just test syntax)
newDay = ta.change(time("D")) != 0
var float dayHigh = na
var float dayLow = na
if newDay
dayHigh := na
dayLow := na
sessStart = 0915
sessEnd = 0925
hhmm = hour * 100 + minute
isFirst = na(dayHigh) and hhmm >= sessStart and hhmm < sessEnd
if isFirst
dayHigh := high
dayLow := low
// Plot first candle range
plot(dayHigh, "First High", color=color.green, style=plot.style_linebr)
plot(dayLow, "First Low", color=color.red, style=plot.style_linebr)
// Simple breakout entries just to test
longCond = not na(dayHigh) and close > dayHigh
shortCond = not na(dayLow) and close < dayLow
if longCond
strategy.entry("LONG", strategy.long)
if shortCond
strategy.entry("SHORT", strategy.short)
MACD + 200 EMA + Chandelier + ML OptimizerNeural MACD Trend Strategy
This script modernizes a classic high-probability trend strategy by integrating Machine Learning and dynamic risk management. It is built on the foundation of the 9, 21, and 200 EMAs with MACD execution, designed to automate the workflow of trend traders.
Key Features:
1. Core Logic: Trades are executed on MACD crosses, but only when aligned with the long-term trend (200 EMA). An optional setting enforces a simultaneous 9/21 EMA cross for high-momentum confirmation.
2. Machine Learning Optimizer: A K-Nearest Neighbors (KNN) algorithm runs in the background, analyzing RSI, CCI, and ROC. It compares the current setup to the last 1,000 bars of history; if the historical probability is negative, the ML blocks the trade to save capital.
3. Range Filter: Uses ADX to detect choppy markets. If the market is ranging (ADX < 20), the background turns gray and trading is paused.
4. Advanced Exits: Automatically calculates Stop Losses based on recent Swing Highs/Lows. Includes a Chandelier Exit (ATR Trailing Stop) to lock in profits dynamically. You can choose between fixed Reward-to-Risk targets (e.g., 1.5x) or disable targets to ride the trend until the trailing stop is hit.
A13: Micro MAP Scalping StrategyA13: Micro MAP Scalping Strategy — Institutional Breakout Scalper (Pine Script v6 – Protected Source)
A completely original, professional scalping strategy developed from scratch over several months of research and live-market testing. The system is built around institutional breakout zones with a unique multi-stage validation process, strict confirmation requirements, and sophisticated risk management — all designed specifically for 1–15 minute timeframes.
Why this implementation is original and the source code is protected
The entire logic — from breakout detection to entry confirmation, multi-filter stop-loss engines, and dynamic position sizing — was built independently without relying on any existing public libraries, built-ins, or open-source code beyond standard Pine functions. The proprietary validation rules, ATR-scaled gap filtering, and layered confirmation system required extensive original development to achieve consistent performance in real-market conditions. Protecting the source code is necessary to preserve the unique edge that distinguishes this system from standard or publicly available implementations.
Core concepts and methodology (fully transparent — no code revealed)
1. Institutional Breakout Zone Detection
• Real-time identification of high-probability zones using a custom ATR-based minimum gap filter
• Zones are only considered valid when accompanied by clear price displacement and volume confirmation
• No reliance on standard Fair Value Gap or order block libraries — completely custom validation
2. Strict Dual Confirmation Entry Logic
• Entry requires one of two precise conditions:
— Confirmed pullback retest of the validated breakout zone, or
— Clean inside-bar formation fully contained within the zone
• Both conditions must align with the directional bias of the breakout
3. Five Independent Stop-Loss Engines
• ATR-based (default and recommended)
• Swing Low/High levels
• Pivot Point structure
• Trailing Stop with ATR offset
• Fixed percentage
• Every engine includes minimum and maximum stop-loss filters to prevent unrealistic risk during extreme volatility
4. Professional Risk & Position Sizing Engine
• Fixed percentage risk per trade (default 1%)
• Optional compounding mode for growing accounts
• Real-time calculation based on exact stop distance and current equity
• Full integration with leverage settings
5. Multi-Layer Filtering System
• Multi-timeframe EMA filter (default 60-period, fully customizable timeframe)
• Complete trading session control with UTC offset support
• Date range filtering for strategy deployment control
• Consecutive loss protection (optional multi-stop filter)
• Minimum/maximum stop-loss filters to eliminate low-probability setups
6. Real-Time Performance Dashboard
• Live display of win rate, net profit, maximum drawdown, total trades
• Consecutive win/loss streak tracking
• Current position size and average entry price
• All statistics visible directly on chart
Backtesting settings used in the published chart
• Symbol: BTC/USD
• Timeframe: 15-minute
• Initial capital: $10,000
• Risk per trade: 1%
• Commission: 0.04% (realistic for major brokers)
• Slippage: enabled
• Sample size: 200+ trades
These are the exact default Properties settings of the strategy.
The strategy is completely free to add and use on your charts.
#Scalping #Breakout #Intraday #Institutional #RiskManagement #ProfessionalStrategy
Supertrend + MAXTRA inputsThe Supertrend strategy is a trend-following trading method that uses the Supertrend indicator, which is calculated based on the ATR (Average True Range). When the price closes above the Supertrend line, it generates a buy signal, and when the price closes below the Supertrend line, it generates a sell signal. The indicator continuously trails the price, helping traders identify trend direction, ride trends, and manage stop-loss levels.
Long Only EMA Strategy (9/20 with 200 EMA Filter)Details:
This strategy is built around a very simple idea: follow the primary trend and enter only when momentum supports it.
It uses three EMAs on a standard candlestick chart:
1. 9‑period EMA – short‑term momentum
2. 20‑period EMA – medium‑term structure
3. 200‑period EMA – long‑term trend filter
The strategy is ** long‑only ** and is mainly designed for swing trading and positional trading.
It avoids counter‑trend trades by taking entries only when price is trading ** above the 200 EMA **, which is commonly used as a long‑term trend reference.
The rules are deliberately kept simple so that they are easy to understand, modify, and test on different markets and timeframes.
---
Key Features
1. **Trend‑Filtered Entries**
- Fresh long positions are considered only when:
- The 9 EMA crosses above the 20 EMA
- The closing price is **above** the 200 EMA
- This attempts to combine short‑term momentum with a higher‑timeframe trend filter.
2. **Clean Exit Logic**
- The long position is exited when the closing price crosses **below** the 20 EMA.
- This creates an objective, rule‑based way to trail the trade as long as the medium‑term structure remains intact.
3. **Long‑Only, No Short Selling**
- The script intentionally ignores short setups.
- This makes it suitable for markets or accounts where short selling is restricted, or for traders who prefer to participate only on the long side of the market.
4. **Simple Visuals**
- All three EMAs are plotted directly on the chart:
- 9 EMA (fast)
- 20 EMA (medium)
- 200 EMA (trend)
- Trade entries and exits are handled by TradingView’s strategy engine, so users can see results in the Strategy Tester as well as directly on the chart.
5. **Backtest‑Friendly Structure**
- Uses TradingView’s built‑in `strategy()` framework.
- Can be applied to different symbols, timeframes, and markets (equities, indices, crypto, etc.).
- Works on standard candlestick charts, which are supported by TradingView’s backtesting engine.
6. **Configurable in Code**
- The EMA periods are defined in the code and can be easily adjusted.
- Users can tailor the parameters to fit their own style (for example, faster EMAs for intraday trading, slower EMAs for positional trades).
---
How to Use
1. **Add the Strategy to Your Chart**
1. Open any symbol and select a **standard candlestick chart**.
2. Apply the strategy from your “My Scripts” section.
3. Make sure it is enabled so that the trades and results appear.
2. **Select Timeframe**
- The logic can be tested on various timeframes:
- Higher timeframes (1H, 4H, 1D) for swing and positional setups.
- Lower timeframes (5m, 15m) for more active trading, if desired.
- Users should experiment and see where the strategy behaves more consistently for their chosen market.
3. **Read the Signals**
- **Entry:**
- A long trade is opened when the 9 EMA crosses above the 20 EMA while the closing price is above the 200 EMA.
- **Exit:**
- The open long position is closed when the closing price crosses below the 20 EMA.
- All orders are generated automatically once the strategy is attached to the chart.
4. **Use the Strategy Tester**
- Go to the **Strategy Tester** tab in TradingView.
- Check:
- Net profit / drawdown
- Win rate and average trade
- List of trades and the equity curve
- Change the date range and timeframe to see how stable the results are over different periods.
5. **Adjust Parameters if Needed**
- Advanced users can open the code and experiment with:
- EMA lengths (for example 8/21 with 200, or 10/30 with 200)
- Risk sizing and capital settings within the `strategy()` call
- Any changes should be thoroughly re‑tested before considering real‑world application.
---
Practical Applications
1. **Swing Trading on Daily Charts**
- Can be applied to stocks, indices, or ETFs on the daily timeframe.
- The 200 EMA acts as a trend filter to stay aligned with the broad direction, while the 9/20 crossover helps catch medium‑term swings inside that trend.
2. **Positional Trades on Higher Timeframes**
- On 4H or 1D charts, this approach can help in holding trades for several days to weeks.
- The exit rule based on the 20 EMA crossing helps avoid emotional decisions and provides a rules‑based way to trail the trend.
3. **Trend‑Following Filter**
- Even if used purely as a filter, the 200 EMA condition can help traders:
- Avoid taking long trades when the market is in a clear downtrend.
- Focus only on instruments that are trading above their long‑term average.
4. **Educational Use**
- The script is intentionally kept straightforward so that newer users can:
- Learn how a moving average crossover strategy works.
- See how to combine a short‑term signal with a long‑term filter.
- Understand how TradingView’s strategy engine handles entries and exits.
5. **Basis for Further Development**
- This can serve as a starting point for more advanced systems.
- Traders can extend it by adding:
- Additional filters (RSI, volume, volatility filters, time‑of‑day filters, etc.)
- Risk management rules (fixed stop loss, take profit, trailing stops).
- The current version is kept minimal on purpose, so modifications are easy to implement and test.
---
Important Notes & Disclaimer
1. This strategy is provided **for testing, research, and educational purposes only**.
2. It is ** not ** a recommendation to buy or sell any financial instrument.
3. Past performance on historical data does not guarantee similar results in live markets.
4. Markets are risky and trading can lead to financial loss; users should always do their own research, manage risk appropriately, and consult a qualified financial professional if needed.
5. Before using any strategy with real capital, it is strongly advised to:
- Forward test it on a demo / paper trading account.
- Check how it behaves during different market phases (trending, sideways, high‑volatility conditions).
You are free to modify the parameters and logic to better align it with your own trading style and risk tolerance.
Strategy: HMA 50 + Supertrend SniperHMA 50 + Supertrend Confluence Strategy (Trend Following with Noise Filtering)
Description:
Introduction and Concept This strategy is designed to solve a common problem in trend-following trading: Lag vs. False Signals. Standard Moving Averages often lag too much, while price action indicators can generate false signals during choppy markets. This script combines the speed of the Hull Moving Average (HMA) with the volatility-based filtering of the Supertrend indicator to create a robust "Confluence System."
The primary goal of this script is not just to overlay two indicators, but to enforce a strict rule where a trade is only taken when Momentum (HMA) and Volatility Direction (Supertrend) are in perfect agreement.
Why this combination? (The Logic Behind the Mashup)
Hull Moving Average (HMA 50): We use the HMA because it significantly reduces lag compared to SMA or EMA by using weighted calculations. It acts as our primary Trend Direction detector. However, HMA can be too sensitive and "whipsaw" during sideways markets.
Supertrend (ATR-based): We use the Supertrend (Factor 3.0, Period 10) as our Volatility Filter. It uses Average True Range (ATR) to determine the significant trend boundary.
How it Works (Methodology) The strategy uses a boolean logic system to filter out low-quality trades:
Bullish Confluence: The HMA must be rising (Slope > 0) AND the Close Price must be above the Supertrend line (Uptrend).
Bearish Confluence: The HMA must be falling (Slope < 0) AND the Close Price must be below the Supertrend line (Downtrend).
The "Choppy Zone" (Noise Filter): This is a unique feature of this script. If the HMA indicates one direction (e.g., Rising) but the Supertrend indicates the opposite (e.g., Downtrend), the market is considered "Choppy" or indecisive. In this state, the script paints the candles or HMA line Gray and exits all positions (optional setting) to preserve capital.
Visual Guide & Signals To make the script easy to interpret for traders who do not read Pine Script, I have implemented specific visual cues:
Green Cross (+): Indicates a LONG entry signal. Both HMA and Supertrend align bullishly.
Red Cross (X): Indicates a SHORT entry signal. Both HMA and Supertrend align bearishly.
Thick Line (HMA): The main line changes color based on the trend.
Green: Bullish Confluence.
Red: Bearish Confluence.
Gray: Divergence/Choppy (No Trade Zone).
Thin Step Line: This is the Supertrend line, serving as your dynamic Trailing Stop Loss.
Strategy Settings
HMA Length: Default is 50 (Mid-term trend).
ATR Factor/Period: Default is 3.0/10 (Standard for trend catching).
Exit on Choppy: A toggle switch allowing users to decide whether to hold through noise or exit immediately when indicators disagree.
Risk Warning This strategy performs best in trending markets (Forex, Crypto, Indices). Like all trend-following systems, it may experience drawdown during prolonged accumulation/distribution phases. Please backtest with your specific asset before using it with real capital.
Trend Flow & Volatility Guard Strategy [ROSTOK V5]Description:
This strategy is a comprehensive trend-following system designed to identify high-probability entries by aligning long-term market direction with short-term momentum, while strictly filtering out low-quality "choppy" market conditions.
How it Works:
The strategy operates on a multi-stage logic system:
Trend Identification: The core direction is determined by a customizable Main Trend Line (selectable between a long-period EMA or Supertrend). Trades are only taken in the direction of the dominant trend.
Signal Generation: Entries are triggered when a fast-moving Signal Line crosses the Main Trend Line, confirmed by specific candlestick price action (Close > Open).
Advanced Filtering (Confluence): To avoid false signals, the strategy employs a robust set of filters. A trade is only valid if:
Momentum: RSI is within safe operating zones (avoiding extreme overbought/oversold unless a strong trend override is active).
Cycle: CCI and MACD histograms align with the trade direction.
Volatility: The ADX is analyzed to ensure sufficient trend strength, while a Choppiness Index filter blocks trades during sideways/ranging markets.
Risk Management & Recovery: The strategy features built-in money management tools, including:
ADR (Average Daily Range) Filter: Prevents entering trades when the asset has already moved its expected daily distance.
Daily Limits: Hard stops for Max Daily Loss and Target Daily Profit to preserve capital.
Recovery Logic: An optional mechanism to manage drawdowns on difficult days using calculated recovery targets.
Settings & Customization: Users can toggle individual filters (Volume, Choppiness, ADX) and adjust the sensitivity of the trend lines to fit different assets and timeframes (e.g., EURAUD 15m).
Disclaimer: Past performance is not indicative of future results. This script is for educational purposes and backtesting analysis.
AB=CD Fibonacci Strategy (One Trade at a Time)
AB=CD Fibonacci Strategy - Harmonic Pattern Trading Bot
Description
An automated trading strategy that identifies and trades the classic AB=CD harmonic pattern, one of the most reliable geometric price formations in technical analysis. This strategy detects perfectly proportioned Fibonacci retracement setups and executes trades with precise risk-reward management.
How It Works
The indicator scans for the AB=CD pattern structure:
Leg AB: Initial swing from pivot point A to pivot point B
Leg BC: Retracement to point C (customizable Fibonacci levels)
Leg CD: Mirror projection equal to the AB leg length
When price touches point D, the strategy automatically enters a position with predefined take-profit and stop-loss levels based on your risk-reward ratio.
Key Features
One Trade at a Time: Ensures disciplined position management by allowing only one active trade per pattern
Customizable Fibonacci Retracement: Set your preferred retracement range for point C (default 50% - 78.6%)
Risk-Reward Control: Adjust stop-loss and take-profit multiples to match your trading plan
Visual Pattern Display: Clear labeling of A, B, C, D points with pattern lines for easy identification
Both Directions: Identifies bullish and bearish AB=CD patterns automatically
Ideal For
Swing traders on higher timeframes (4H, Daily, Weekly)
Harmonic pattern traders seeking automation
Traders wanting precise entry and exit rules based on Fibonacci geometry
Those looking to reduce emotional trading and increase consistency
Default Settings Optimized For
NASDAQ futures and currency pairs
Medium timeframe analysis
Conservative risk management (10% position size per trade)
Trendshift [CHE] StrategyTrendshift Strategy — First-Shift Structural Regime Trading
Profitfactor 2,603
Summary
Trendshift Strategy implements a structural regime-shift trading model built around the earliest confirmed change in directional structure. It identifies major swing highs and lows, validates breakouts through optional ATR-based conviction, and reacts only to the first confirmed shift in each direction. After a regime reversal, the strategy constructs a premium and discount band between the breakout candle and the previous opposite swing. This band is used as contextual bias and may optionally inform stop placement and position sizing.
The strategy focuses on clear, interpretable structural events rather than continuous signal generation. By limiting entries to the first valid shift, it reduces false recycles and allows the structural state to stabilize before a new trade occurs. All signals operate on closed-bar logic, and the strategy avoids higher-timeframe calls to stabilize execution behavior.
Motivation: Why this design?
Many structure-based systems repeatedly trigger as price fluctuates around prior highs and lows. This often leads to multiple flips during volatile or choppy conditions. Trendshift Strategy addresses this problem by restricting execution to the first confirmed structural event in each direction. ATR-based filters help differentiate genuine structural breaks from noise, while the contextual band ensures that the breakout is meaningful in relation to recent volatility.
The design aims to represent a minimalistic structural trading framework focused on regime turns rather than continuous trend signaling. This reduces chart noise and clarifies where the market transitions from one regime to another.
What’s different vs. standard approaches?
Baseline reference
Typical swing-based structure indicators report every break above or below recent swing points.
Architecture differences
First-shift-only regime logic that blocks repeated signals until direction reverses
ATR-filtered validation to avoid weak or momentum-less breaks
Premium and discount bands derived from breakout structure
Optional band-driven stop placement
Optional band-dependent position-sizing factor
Regime timeout system to neutralize structure after extended inactivity
Persistent-state architecture to prevent re-triggering
Practical effect
Only the earliest actionable structure change is traded
Fewer but higher-quality signals
Premium/discount tint assists contextual evaluation
Stops and sizing can be aligned with structural context rather than arbitrary volatility measures
Improved chart interpretability due to reduced marker frequency
How it works (technical)
The algorithm evaluates symmetric swing points using a fixed bar window. When a swing forms, its value and bar index are stored as persistent state. A structural shift occurs when price closes beyond the most recent major swing on the opposite side. If ATR filtering is enabled, the breakout must exceed a volatility-scaled distance to prevent micro-breaks from firing.
Once a valid shift is confirmed, the regime is updated to bullish or bearish. The script records the breakout level, the opposite swing, and derives a band between them. This band is checked for minimum size relative to ATR to avoid unrealistic contexts.
The first shift in a new direction generates both the strategy entry and a visual marker. Additional shifts in the same direction are suppressed until a reversal occurs. If a timeout is enabled, the regime resets after a specified number of bars without structural change, optionally clearing the band.
Stop placement, if enabled, uses either the opposite or same band edge depending on configuration. Position size is computed from account percentage and may optionally scale with the price-span-to-ATR relationship.
Parameter Guide
Market Structure
Swing length (default 5): Controls swing sensitivity. Lower values increase responsiveness.
Use ATR filter (default true): Requires breakouts to show momentum relative to ATR. Reduces false shifts.
ATR length (default 14): Volatility estimation for breakout and band validation.
Break ATR multiplier (default 1.0): Required breakout strength relative to ATR.
Premium/Discount Framework
Enable framework (default true): Activates premium/discount evaluation.
Persist band on timeout (default true): Keeps structural band after timeout.
Min band ATR mult (default 0.5): Rejects narrow bands.
Regime timeout bars (default 500): Neutralizes regime after inactivity.
Invert colors (default false): Color scheme toggle.
Visuals
Show zone tint (default true): Background shade in premium or discount region.
Show shift markers (default true): Display first-shift markers.
Execution and Risk
Risk per trade percent (default 1.0): Determines position size as account percentage.
Use band for size (default false): Scales size relative to band width behavior.
Flat on opposite shift (default true): Forces reversal behavior.
Use stop at band (default false): Stop anchored to band edges.
Stop band side: Chooses which band edge is used for stop generation.
Reading & Interpretation
A green background indicates discount conditions within the structural band; red indicates premium conditions. A green triangle below price marks the first bullish structural shift after a bearish regime. A red triangle above price marks the first bearish structural shift after a bullish regime.
When stops are active, the opposite band edge typically defines the protective level. Band width relative to ATR indicates how significant a structural change is: wider bands imply stronger volatility structure, while narrow bands may be suppressed by the minimum-size filter.
Practical Workflows & Combinations
Trend following: Use first-shift entries as initial regime confirmation. Add higher-timeframe trend filters for additional context.
Swing trading: Combine with simple liquidity or fair-value-gap concepts to refine entries.
Bias mapping: Use higher timeframes for structural regime and lower timeframes for execution within the premium/discount context.
Exit management: When using stops, consider ATR-scaling or multi-stage profit targets. When not using stops, reversals become the primary exit.
Behavior, Constraints & Performance
The strategy uses only confirmed swings and closed-bar logic, avoiding intrabar repaint. Pivot-based swings inherently appear after the pivot window completes, which is standard behavior. No higher-timeframe calls are used, preventing HTF-related repaint issues.
Persistent variables track regime and structural levels, minimizing recomputation. The maximum bars back setting is five-thousand. The design avoids loops and arrays, keeping performance stable.
Known limitations include limited signal density during consolidations, delayed swing confirmation, and sensitivity to extreme gaps that stretch band logic. ATR filtering mitigates some of these effects but does not eliminate them entirely.
Sensible Defaults & Quick Tuning
Fewer but stronger entries: Increase swing length or ATR breakout multiplier.
More responsive entries: Reduce swing length to capture earlier shifts.
More active band behavior: Lower the minimum band ATR threshold.
Stricter stop logic: Use the opposite band edge for stop placement.
Volatile markets: Increase ATR length slightly to stabilize behavior.
What this indicator is—and isn’t
Trendshift Strategy is a structural-regime trading engine that evaluates major directional shifts. It is not a complete trading system and does not include take-profit logic or prediction features. It does not attempt to forecast future price movement and should be used alongside broader market structure, volatility context, and disciplined risk management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
DTR V 1.0DTR V 1.0 is a momentum-based reversal strategy that combines the Stochastic Oscillator and the Relative Strength Index (RSI) to identify potential turning points in the market. It uses dual confirmation to filter out weak signals and focus on moments when price is genuinely stretched.
The strategy calculates Stochastic and RSI using user-defined lengths (default 14). A long entry occurs when both indicators show oversold conditions: Stochastic falls below the Oversold Level (default 20) and RSI drops below the RSI Oversold Level (default 30). This suggests weakening downward momentum and a possible reversal.
A long position is closed when both indicators reach overbought conditions: Stochastic rises above the Overbought Level (default 80) and RSI moves above the RSI Overbought Level (default 70). This helps capture the rebound move without staying in during momentum exhaustion.
DTR V 1.0 works best in range-bound markets, where oscillators frequently move between extremes, and it can also be effective for catching pullbacks within uptrends. It is generally suited for intraday to swing-trading timeframes. Like most oscillator-based systems, it may struggle during strong trending or high-volatility conditions where overbought or oversold readings can persist.
All thresholds and indicator lengths are adjustable, allowing traders to tune the strategy to different assets and market environments.
Best Entry Swing MASTER v3 PUBLIC (S.S)Strategy Description (English)
Best Entry Swing MASTER v3 – Quality Mode
The Best Entry Swing MASTER v3 is a structured swing trading and trend-following strategy designed to identify high-probability long and short entries during directional markets.
It combines three core setup types commonly used by momentum and breakout traders:
Breakout (BO)
Pullback Reversal (PB)
Volatility Contraction Pattern (VCP)
The strategy applies multiple layers of confirmation, including multi-EMA trend structure, volatility contraction, volume filters, and an optional market regime filter.
It is suitable for swing trading on higher timeframes (4H, Daily), as well as medium-term trend continuation setups.
Core Concepts
1. Trend Structure
A trend is considered valid when:
Uptrend: Price > EMA20 > EMA50 > EMA100
Downtrend: Price < EMA20 < EMA50 < EMA100
In addition, a simple but effective trend-strength metric is calculated using the percentage spread between EMA20 and EMA100.
This helps avoid signals during sideways or low-volatility environments.
2. Market Regime Filter
The market environment is determined using a higher timeframe benchmark (default: SPY on Daily).
Only long trades are allowed in bullish market conditions
Only short trades in bearish conditions
This significantly reduces false signals in counter-trend conditions.
Entry Logic
Breakout (BO)
A long breakout triggers when:
Price closes above the highest high of the lookback period
Volume exceeds its 20-period average
Trend and market regime confirm
(Optional A+ mode): true volatility contraction is required
Similar logic applies for short breakdowns.
Pullback (PB)
A pullback entry triggers after:
At least two corrective candles
A strong reversal candle (close above previous high for long)
Volume confirmation
Price interacts with EMA20
This structure models classical trend-reentry conditions.
Volatility Contraction Pattern (VCP)
A VCP entry triggers when:
True range contracts over multiple bars
Price holds near the breakout zone
Volume contracts
Trend and market regime are aligned
This setup aims to capture explosive continuation moves.
Quality Modes
The strategy offers two modes:
Balanced Mode
Moderate signal frequency
Broader trend-strength allowance
Suitable for more active traders
A+ Only Mode
Strict confirmation requirements
Only high-quality setups with multiple confluences
Designed to avoid low-probability trades entirely
Risk Management
Risk is managed using an ATR-based stop and target:
Long SL = Close − ATR × 1.5
Long TP = Close + ATR × 3
(Equivalent logic for short positions)
This provides a balanced reward-to-risk profile and avoids overly tight stops.
Early Entry Signals (Optional)
The script offers optional “Early Entry” markers that highlight when a setup is forming but not yet confirmed.
These are not entry signals and are disabled by default for public use.
Intended Use
This strategy is designed for:
Swing trading
Momentum continuation
Trend-following
Multi-day to multi-week trades
It performs best on:
4H
Daily
High-liquidity equities, indices, and futures
Disclaimer
This script is intended for educational and research purposes.
Past performance does not guarantee future results.
Always backtest thoroughly and use appropriate risk management.
Yellow Candle X:@BADPERSON129**Yellow Candle Strategy - Performance Overview**
The Yellow Candle signal demonstrates moderate effectiveness with a success rate ranging from 30% to 60%. This strategy yields profit margins between 3% and 10%, depending on your portfolio management approach and market conditions.
**Key Parameters:**
- **Success Rate:** 30%-60%
- **Profit Target:** 3%-10%
- **Stop Loss:** 3%-8%
**Risk Management Notes:**
- Adjust position sizing according to your risk tolerance
- Stop loss placement is crucial for capital preservation
- The wide success rate range reflects varying market volatility
- Portfolio diversification recommended when implementing this signal
*Note: Performance may vary based on market conditions, timeframe selection, and proper risk management execution. Always backtest and forward test strategies before live implementation.*
G-BOT ENGULFING CANDLE - FIXED SL & TP // Description:
This Pine Script strategy identifies bullish and bearish engulfing candle patterns over a defined lookback period and places trades based
on recent market highs and lows. It calculates stop loss and take profit levels using the Average True Range (ATR) multiplied by a user-defined factor, with the ability to adjust the risk-to-reward ratio for each trade.
Full Regime Engine – Trend / Mean Revert / No-Trade🚀 Full Regime Engine Strategy: Trend / Mean Revert / No-Trade
This comprehensive strategy, named the Full Regime Engine, is designed to adapt its trading logic based on prevailing market conditions, classifying the market into three distinct regimes: Trend, Mean Reversion (MR), and No-Trade. It uses a combination of Average True Range (ATR) volatility ratio and the Average Directional Index (ADX) to determine the current regime, ensuring the appropriate entry and exit logic is applied.
⚙️ How the Regime Engine Works
The strategy uses two core indicators to define the market regime:
Volatility Ratio (ATR / SMA of ATR):
High Volatility Ratio (above highVolThr) suggests an active, potentially trending market.
Low Volatility Ratio (below lowVolThr) suggests a calmer, mean-reverting environment.
Average Directional Index (ADX):
High ADX (above adxTrendMin) confirms the strength of a potential trend.
Low ADX (below adxChopMax) confirms a weak, non-directional, or choppy market suitable for mean reversion.
The regimes are defined as follows:
🟢 Trend Regime: High Volatility Ratio AND High ADX.
🔵 Mean Reversion (MR) Regime: Low Volatility Ratio AND Low ADX.
⚫ No-Trade Regime: Any other condition, including outside of the defined session/time filters.
🎯 Entry and Exit Logic by Regime
The strategy employs a different entry and exit approach for each active regime:
1. Trend Regime (Pullback Entries)
Definition: The trend is established using a cross of Fast and Slow EMAs (emaFastLen and emaSlowLen).
Entry Signal: A pullback entry, where the price momentarily touches the Fast EMA and then closes back in the direction of the trend.
Long: low <= Fast EMA and close > Fast EMA (during a bullish trend).
Short: high >= Fast EMA and close < Fast EMA (during a bearish trend).
Risk Management: Uses a wider Stop Loss (slTrend) and Take Profit (tpTrend) based on ATR multiples, reflecting the expectation of larger moves in a trending market.
2. Mean Reversion Regime (VWAP Deviation Fades)
Definition: Trades the fade of extreme price movements back towards the Volume-Weighted Average Price (VWAP).
Entry Signal: Price is significantly deviated from VWAP (measured in ATR multiples mrDevATR) and shows a reversal candle.
Long (Fade Short): Price is far below VWAP (devZ < -mrDevATR) and the current candle is bullish (close > open).
Short (Fade Long): Price is far above VWAP (devZ > mrDevATR) and the current candle is bearish (close < open).
Risk Management: Uses a tighter Stop Loss (slMR) and Take Profit (tpMR) based on ATR multiples, suitable for capturing smaller moves near the mean.
⏱️ Time-Based Filters
The strategy includes robust time filters to only trade during periods with higher liquidity and predictable activity:
RTH Session Filter: Trades only within the defined "Regular Trading Hours" session (sessionStr).
Midday Filter: Optionally avoids the typically slow and choppy midday trading hours (11:00–13:00).
📊 Visuals & Customization
Background Colors: The chart background automatically colors to display the current regime: Green for Trend, Blue for Mean Revert, and Gray for No-Trade.
Plot Shapes: Distinct shapes and labels mark the raw entry signals for both Trend (Triangles) and Mean Reversion (Circles).
ATR Exits: Plots the dynamically calculated Stop Loss (Red) and Take Profit (Green) lines based on the trade's entry mode (Trend or MR).
💡 Note: This is a comprehensive engine that requires careful optimization of the input parameters for your specific instrument and timeframe. Start with the default settings and adjust the regime thresholds (ATR Ratio and ADX) and the risk/reward multiples (SL/TP) to suit your trading style.
Dual MTF Confirmed Trend Strategy (5m Entry / 15m MACD & RSI) v1That is a detailed Dual Multi-Timeframe (MTF) Confirmed Trend Strategy written in Pine Script for TradingView. The core idea of this strategy is to only take entry signals on a faster timeframe (5-minute) when the trend is strongly confirmed on a slower, higher timeframe (15-minute). This aims to reduce false signals and trade in the direction of the dominant trend. Here is an explanation of how the strategy works, broken down by section:
1. 5-Minute Entry Filters 🚀This section calculates several indicators on the current 5-minute chart to identify potential trade setups. A position is only considered if all 5-minute conditions align.
Supertrend: A trend-following indicator based on Average True Range (ATR).
Long Condition: The closing price must be above the Supertrend line.
Short Condition: The closing price must be below the Supertrend line.
Gann Hi-Lo (GHL): A trend indicator using Simple Moving Averages (SMA) of the high and low prices. GHL Line: Switches between the SMA of the Highs and the SMA of the Lows based on price action.
Long Condition: The closing price must be above the GHL line.
Short Condition: The closing price must be below the GHL line.
Exponential Moving Averages (EMAs): It uses a 50-period EMA and a 100-period EMA to confirm the short-term trend direction.
Long Condition: The closing price must be above both the 50 EMA and the 100 EMA.
Short Condition: The closing price must be below both the 50 EMA and the 100 EMA.
2. 15-Minute MTF Confirmation Filters ⏳This is the crucial step where the strategy verifies the trend on the slower, 15-minute timeframe using the request security function. This step acts as a gatekeeper to ensure the 5-minute trade aligns with the larger trend.
MACD Histogram (12, 26, 9): The difference between the MACD Line and the Signal Line.
Long Confirmation: The 15m MACD Histogram must be greater than 0 (MACD line is above the Signal line, indicating bullish momentum).
Short Confirmation: The 15m MACD Histogram must be less than 0 (MACD line is below the Signal line, indicating bearish momentum).
RSI (Relative Strength Index) (14): A momentum oscillator. The 50 level is often used to determine the general market trend.
Long Confirmation: The 15m RSI must be greater than 50 (indicating stronger bullish momentum).
Short Confirmation: The 15m RSI must be less than 50 (indicating stronger bearish momentum).
The Total 15m Confirmation is only true if both the MACD and the RSI confirmation signals align.
3. Trade Orders (Entry Logic) ⚖️
The strategy only executes a trade when the 5-minute entry conditions are met AND the 15-minute confirmation conditions are met.
Final Long Condition:
5m Conditions (Supertrend, GHL, EMA alignment) AND
15m Confirmation (MACD Hist > 0 AND RSI > 50)
Final Short Condition:
5m Conditions (Supertrend, GHL, EMA alignment) AND
15m Confirmation (MACD Hist < 0 AND RSI < 50)
When a trade signal is generated, the strategy:
Closes any opposite position (e.g., closes a "Short" trade if a "Long" signal appears).
Enters the new position (e.g., enters a "Long" trade).
This is designed as a reversal strategy where a new entry automatically closes the previous opposing trade.
In Summary
The strategy operates on a principle of Trend Alignment:
5-Minute Chart: Is used for Signal Timing (when exactly to enter the market).
15-Minute Chart: Is used for Trend Validation (is the overall market momentum supporting the signal?).
It's an attempt to capture short-term moves (5m signals) that are backed by strong medium-term momentum (15m confirmation), thereby aiming for higher probability trades.
This is not investment advice; it is recommended to perform optimization and backtesting for the assets intended for implementation.
EMA 12-26-100 Momentum Strategy# Triple EMA Multi-Signal Momentum Strategy
## 📊 Overview
**Triple EMA Multi-Signal** is a comprehensive trend-following momentum strategy designed specifically for cryptocurrency markets. It combines multiple technical indicators and signal types to identify high-probability trading opportunities while maintaining strict risk management protocols.
The strategy excels in trending markets and uses adaptive position sizing with trailing stops to maximize profits during strong trends while protecting capital during choppy conditions.
## 🎯 Core Algorithm
### Triple EMA System
The strategy employs a three-layer EMA system to identify trend direction and strength:
- **Fast EMA (12)**: Quick response to price changes
- **Slow EMA (26)**: Confirmation of trend direction
- **Trend EMA (100)**: Overall market bias filter
Trades are only taken when all three EMAs align in the same direction, ensuring we trade with the dominant trend.
### Multi-Signal Confirmation (8 Signal Types)
The strategy requires at least 1-2 confirmed signals from multiple independent sources before entering a position:
1. **EMA Crossover** - Fast EMA crossing Slow EMA (primary signal)
2. **MACD Cross** - MACD line crossing signal line (momentum confirmation)
3. **RSI Reversal** - RSI bouncing from oversold/overbought zones
4. **Price Action** - Strong bullish/bearish candles (>60% of range)
5. **Volume Spike** - Above-average volume confirmation
6. **Breakout** - Price breaking 20-period high/low with volume
7. **Pullback to EMA** - Trend continuation after healthy retracement
8. **Bollinger Bounce** - Price bouncing from BB bands
This multi-signal approach significantly reduces false signals and improves win rate.
## 💰 Risk Management
### Position Sizing
- Default: 20-25% of equity per trade
- Adjustable based on risk tolerance
- Smaller positions recommended for leveraged trading
### Stop Loss & Take Profit
- **Stop Loss**: 2.0% (tight control of risk)
- **Take Profit**: 5.5% (2.75:1 reward-to-risk ratio)
- Both levels are fixed at entry to avoid emotional decisions
### Trailing Stop System
- Activates after 1.8% profit
- Trails at 1.3% below current price
- Locks in profits during extended trends
- Automatically adjusts as price moves in your favor
### Maximum Hold Time
- 36-48 hours maximum (configurable)
- Designed to minimize funding rate costs on futures
- Forces position closure to avoid excessive exposure
- Helps maintain capital velocity
## 📈 Key Features
### Trend Filters
- **ADX Filter**: Ensures sufficient trend strength (threshold: 20)
- **EMA Alignment**: All three EMAs must confirm trend direction
- **RSI Boundaries**: Avoids extreme overbought/oversold entries
### Volume Analysis
- Volume must exceed 20-period moving average
- Configurable multiplier (default: 1.0x)
- Helps identify institutional participation
### Automatic Exit Conditions
1. Take Profit target reached
2. Stop Loss triggered
3. Trailing stop activated
4. Trend reversal (EMA cross in opposite direction)
5. Maximum hold time exceeded
## 🎮 Recommended Settings
### For Spot Trading (Conservative)
```
Position Size: 15-20%
Stop Loss: 2.5%
Take Profit: 6.0%
Max Hold: 72 hours
Leverage: 1x
```
### For Futures 3-5x Leverage (Balanced)
```
Position Size: 12-15%
Stop Loss: 2.0%
Take Profit: 5.5%
Max Hold: 36 hours
Trailing: Active
```
### For Aggressive Trading 5-10x (High Risk)
```
Position Size: 8-12%
Stop Loss: 1.5%
Take Profit: 4.5%
Max Hold: 24 hours
ADX Filter: Disabled
```
## 📊 Performance Metrics
### Backtested Results (BTC/USDT 1H, 2 years)
- **Total Return**: ~19% (spot) / ~75% (5x leverage)*
- **Total Trades**: 240-300
- **Win Rate**: 49-52%
- **Profit Factor**: 1.25-1.50
- **Max Drawdown**: ~18-22%
- **Average Trade**: 0.5-3 days
*Leverage results exclude funding rates and real-world slippage
### Optimal Timeframes
- **1 Hour**: Best for active trading (recommended)
- **4 Hour**: More stable, fewer signals
- **15 Min**: High frequency (requires monitoring)
### Best Performing Assets
- BTC/USDT (most tested)
- ETH/USDT
- Major altcoins with good liquidity
- Not recommended for low-cap or illiquid pairs
## ⚙️ How to Use
1. **Add to Chart**: Apply strategy to 1H BTC/USDT chart
2. **Adjust Settings**: Configure risk parameters based on your preference
3. **Review Signals**: Green = Long, Red = Short, labels show signal count
4. **Monitor Performance**: Check strategy tester for detailed statistics
5. **Optimize**: Use strategy optimization to find best parameters for your market
## 🎨 Visual Indicators
The strategy provides clear visual feedback:
- **EMA Lines**: Blue (Fast), Red (Slow), Orange (Trend)
- **BUY/SELL Labels**: Show entry points with signal count
- **Stop/Target Lines**: Red (SL), Green (TP) displayed during active trades
- **Background Color**: Light green (long), light red (short) when in position
- **Info Panel**: Shows current trend, RSI, ADX, and volume status
## ⚠️ Important Notes
### Risk Disclaimer
- This strategy is for educational purposes only
- Past performance does not guarantee future results
- Cryptocurrency trading involves substantial risk
- Only trade with capital you can afford to lose
- Always use proper position sizing and risk management
### Limitations
- Performs poorly in sideways/choppy markets
- Requires sufficient liquidity for best execution
- Backtests do not include:
- Real-world slippage (especially during volatility)
- Funding rates (for perpetual futures)
- Exchange downtime or connection issues
- Emotional trading decisions
### For Futures Trading
If using this strategy on futures with leverage:
- Reduce position size proportionally to leverage
- Account for funding rates (~0.01% per 8h)
- Set max hold time to minimize funding costs
- Use lower leverage (3-5x max recommended)
- Monitor liquidation price carefully
## 🔧 Customization
All parameters are fully customizable:
- EMA periods (fast/slow/trend)
- MACD settings (12/26/9)
- RSI levels (30/70)
- Stop Loss / Take Profit percentages
- Trailing stop activation and offset
- Volume multiplier
- ADX threshold
- Maximum hold time
## 📚 Strategy Logic
The strategy follows this decision tree:
```
1. Check Trend Direction (EMA alignment)
↓
2. Scan for Entry Signals (8 types)
↓
3. Confirm with Filters (ADX, Volume, RSI)
↓
4. Enter Position with Fixed SL/TP
↓
5. Monitor for Exit Conditions:
- TP Hit → Close with profit
- SL Hit → Close with loss
- Trailing Active → Follow price
- Trend Reversal → Close position
- Max Time → Force close
```
## 🎓 Best Practices
1. **Start Conservative**: Use smaller position sizes initially
2. **Track Performance**: Monitor actual vs backtested results
3. **Optimize Regularly**: Market conditions change, adapt parameters
4. **Combine with Analysis**: Don't rely solely on automated signals
5. **Manage Emotions**: Stick to the system, avoid manual overrides
6. **Paper Trade First**: Test on demo before risking real capital
## 📞 Support & Updates
This strategy is actively maintained and updated based on:
- Market condition changes
- User feedback and suggestions
- Performance optimization
- Bug fixes and improvements
## 🏆 Conclusion
Triple EMA Multi-Signal Strategy offers a robust, systematic approach to cryptocurrency trading by combining trend following, momentum indicators, and strict risk management. Its multi-signal confirmation system helps filter false signals while the trailing stop mechanism captures extended trends.
The strategy is suitable for both manual traders looking for high-probability setups and algorithmic traders seeking a proven systematic approach.
**Remember**: No strategy wins 100% of the time. Success comes from consistent application, proper risk management, and continuous adaptation to changing market conditions.
---
*Version: 1.0*
*Last Updated: November 2025*
*Tested on: BTC/USDT, ETH/USDT (1H, 4H timeframes)*
*Recommended Capital: $5,000+ for optimal position sizing*
Liquidity Sweep & FVG StrategyThis strategy combines higher-timeframe liquidity levels, stop-hunt (sweep) logic, Fair Value Gaps (FVGs) and structure-based take-profits into a single execution engine.
It is not a simple mash-up of indicators: every module (HTF levels, sweeps, FVGs, ZigZag, sessions) feeds the same entry/exit logic.
1. Core Idea
The script looks for situations where price:
Sweeps a higher-timeframe high/low (takes liquidity around obvious levels),
Then forms a displacement candle with a gap (FVG) in the opposite direction,
Then uses the edge of that FVG as a limit entry,
And manages exits using unswept structural levels (ZigZag swings or HTF levels) as targets.
The intent is to systematically trade failed breakouts / stop hunts with a defined structure and risk model.
It is a backtesting / study tool, not a signal service.
2. How the Logic Works (Conceptual)
a) Higher-Timeframe Liquidity Engine
Daily, Weekly and Monthly highs/lows are pulled via request.security() and stored as HTF liquidity levels.
Each level is drawn as a line with optional label (1D/1W/1M High/Low).
A level is marked as “swept” once price trades through it; swept levels may be removed or shortened depending on settings.
b) Sweep & Manipulation Filter
A low sweep occurs when the current low trades through a stored HTF low.
A high sweep occurs when the current high trades through a stored HTF high.
If both a high and a low are swept in the same bar, the script flags this as “manipulation” and blocks new entries around that noise.
The script also tracks the sweep wick, bar index and HTF timeframe for later use in SL placement and labels.
c) FVG Detection & Management
FVGs are defined using a 3-candle displacement model:
Bullish FVG: high < low
Bearish FVG: low > high
Only gaps larger than a minimum size (ATR-based if no manual value is set) are kept.
FVGs are stored in arrays as boxes with: top, bottom, mid (CE), direction, and state (filled / reclaimed).
Boxes are auto-extended and visually faded when price is far away, or deleted when filled.
d) Entry Conditions (Sweep + FVG)
For each recent sweep window:
After a low sweep, the script searches for the nearest bullish FVG below price and uses its top edge as a long limit entry.
After a high sweep, it searches for the nearest bearish FVG above price and uses its bottom edge as a short limit entry.
A “knife protection” check blocks trades where price is already trading through the proposed stop.
Only one entry per sweep is allowed; entries are only placed inside the configured NY trading sessions and only if no manipulation flag is active and EOD protection allows it.
e) Stop-Loss Placement (“Tick-Free” SL)
The stop is not placed directly on the HTF level; instead, the script scans a window around the sweep bar to find a local extreme:
Longs: lowest low in a configurable bar window around the sweep.
Shorts: highest high in that window.
This produces a structure-based SL that is generally outside the main sweep wick.
f) Take-Profit Logic (ZigZag + HTF Levels)
A lightweight ZigZag engine tracks swing highs/lows and removes levels that have already been broken.
For intraday timeframes (< 1h), TP candidates come from unswept ZigZag swings above/below the entry.
For higher timeframes (≥ 1h), TP candidates fall back to unswept HTF liquidity levels.
The script picks up to two targets:
TP1: nearest valid target in the trade direction (or a 2R fallback if none exists),
TP2: second target (or a 4R fallback if none exists).
A multi-TP model is used: typically 50% at TP1, remainder managed towards TP2 with breakeven plus offset once TP1 is hit.
g) Session & End-of-Day Filters
Three predefined NY sessions (Early, Open, Afternoon) are available; entries are only allowed inside active sessions.
An End-of-Day filter checks a user-defined NY close time and:
Blocks new entries close to the end of the day,
Optionally forces flat before the close.
3. Inputs Overview (Conceptual)
Liquidity settings: which HTF levels to track (1D/1W/1M), how many to show, and sweep priority (highest TF vs nearest vs any).
FVG settings: visibility radius, search window after a sweep, minimum FVG size.
ZigZag settings: swing length used for TP discovery.
Execution & protection: limit order timeout, breakeven offset, EOD protection.
Visuals: labels, sweep markers, manipulation warning, session highlighting, TP lines, etc.
For exact meaning of each input, please refer to the inline comments in the open-source code.
4. Strategy Properties & Backtesting Notes
Default strategy properties in this script:
Initial capital: 100,000
Order size: 10% of equity (strategy.percent_of_equity)
Commission: 0.01% per trade (adjust as needed for your broker/asset)
Slippage: must be set manually in the Strategy Tester (recommended: at least a few ticks on fast markets).
Even though the order size is 10% of equity, actual risk per trade depends on the SL distance and is typically much lower than 10% of the account. You should still adjust these values to keep risk within what you personally consider sustainable (e.g. somewhere in the 1–2% range per trade).
For more meaningful results:
Test on liquid instruments (e.g. major indices, FX, or liquid futures).
Use enough history to reach 100+ closed trades on your market/timeframe.
Always include realistic commission and slippage.
Do not assume that past performance will continue.
5. How to Use
Apply the strategy to your preferred symbol and timeframe.
Set broker-like commission and slippage in the Strategy Tester.
Adjust:
HTF levels (1D/1W/1M),
Sessions (NY windows),
FVG search window and minimum size,
ZigZag length and EOD filter.
Observe how entries only appear:
After a HTF sweep,
In the configured session,
At a FVG edge,
With TP lines anchored at unswept structure / liquidity.
Use this primarily as a research and backtesting tool to study how your own ICT / SMC ideas behave over a large sample of trades.
6. Disclaimer
This script is for educational and research purposes only.
It does not constitute financial advice, and it does not guarantee profitability. Always validate results with realistic assumptions and use your own judgment before trading live.
AUDNZD Mean Reversion (5 minutes)Here are the results
drive.google.com
🔒 The Mechanism for Exploiting Asymmetry in the AUD/NZD Pair
This strategy is not about directional trading; it is about Relational Trading, leveraging the structural fact that the Australian Dollar (AUD) and New Zealand Dollar (NZD) are highly synchronized due to their similar fundamental drivers (commodity exports, sensitivity to China, risk sentiment). This coupling creates a strong Structural Elasticity where the price is inherently inclined to revert to a long-term equilibrium.
1. Defining the Equilibrium State (The Center Point)
The core of the strategy lies in accurately defining the pair's True Statistical Mean (μ), which acts as the pair's long-term gravitational center.
Principle: Identify the μ value—the statistical equilibrium—that the pair has historically maintained (often observed near the 1.0800 - 1.1000 range).
Significance: This μ represents the Gravitational Pull; any movement beyond this point is considered temporary short-term noise or a deviation from the structural norm.
2. Measuring the Tension (The Deviation Gauge)
A statistical tool is necessary to measure precisely how far the price has been stretched away from its mean relative to its historical volatility.
The Instrument: This is achieved by calculating the Z-Score or using volatility-based Envelopes calibrated against the historical standard deviation of the price movement relative to μ.
The Analysis: When the AUD/NZD price deviates beyond a statistical significance level (e.g., exceeding ±2 Sigma), it indicates that the Tension in the relationship has peaked, and the corrective force towards the mean is maximized.
3. The Execution Protocol (Actionable Triggers)
Trading occurs only when tension is at an extreme, effectively fading the current momentum to capitalize on the structural force of mean reversion.
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🔒 กลไกการฉวยโอกาสจากความไม่สมมาตรในคู่ AUD/NZD
กลยุทธ์นี้ไม่ได้เป็นการเทรดทิศทาง (Directional) แต่เป็นการเทรด ความสัมพันธ์ (Relational) โดยอาศัยข้อเท็จจริงที่ว่า AUD และ NZD เป็นสกุลเงินที่ได้รับอิทธิพลจากปัจจัยพื้นฐานที่ใกล้เคียงกันมาก (สินค้าโภคภัณฑ์และความเสี่ยง) จึงทำให้ราคามี "ความยืดหยุ่นเชิงโครงสร้าง" ที่จะกลับมาสู่จุดสมดุลเสมอ
1. การกำหนดจุดศูนย์กลาง (The Equilibrium State)
หัวใจของกลยุทธ์คือการนิยาม "ค่าเฉลี่ยจริง" ของความสัมพันธ์นี้ (ไม่ใช่แค่ค่าเฉลี่ยเคลื่อนที่ของราคา)
หลักการ: ต้องหาค่า μ (Mu) ซึ่งเป็นจุด สมดุลทางสถิติ ในระยะยาวของคู่เงินนี้ ซึ่งมักอยู่ใกล้เคียงค่า 1.0800 - 1.1000
ความสำคัญ: ค่า μ นี้คือ เส้นแรงดึงดูด (Gravitational Pull) ที่ราคามีแนวโน้มจะวิ่งกลับเข้าหาในท้ายที่สุด การเคลื่อนไหวที่เกินจากจุดนี้ถือเป็นเพียง "สัญญาณรบกวนระยะสั้น"
2. การวัดความตึงเครียด (The Tension Gauge)
เราจำเป็นต้องมีเครื่องมือวัดว่าแรงดึงดูดถูก "ยืดออก" ไปจากค่าสมดุลมากน้อยเพียงใด ซึ่งทำได้โดยการวัด "ความเบี่ยงเบนมาตรฐาน (Standard Deviation)" ของราคาเทียบกับจุดศูนย์กลาง
เครื่องมือที่ใช้: การประยุกต์ใช้ค่า Z-Score หรือ Envelope ที่ตั้งค่าตามความผันผวนทางสถิติในอดีต
การวิเคราะห์: เมื่อราคา AUD/NZD เบี่ยงเบนเกินระดับนัยสำคัญ (เช่น เกิน ±2 Sigma) นั่นหมายความว่า ความตึงเครียด ระหว่างสองสกุลเงินอยู่ในระดับสูงสุด และแรงผลักให้กลับสู่ค่าเฉลี่ยกำลังสะสม
3. โปรโตคอลการเข้าปฏิบัติการ (The Execution Protocol)
การเข้าเทรดจะต้องเกิดขึ้นเมื่อความตึงเครียดถึงขีดสุด โดยเป็นการ "สวนทางกับแรงเหวี่ยงปัจจุบัน" เพื่อจับจังหวะที่แรงดึงดูดกลับเข้าทำงาน
1M XAU Cumulative Delta Volume with OB Breakouts
### Overview
This is a **session-based CVD strategy** built around the **00:00–07:00 CEST range**. It finds the high/low of that session, turns them into **adaptive ATR-based support (yellow)** and **resistance (purple)** zones, and trades only **CVD-confirmed reversals** off those levels.
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### How it Works
* For each day, the script:
* Builds a 00:00–07:00 CEST **profile high/low**.
* Creates a **support zone** around the session low and a **resistance zone** around the session high.
* Using lower timeframe data, it reconstructs **Cumulative Volume Delta (CVD)** and a **recent delta** filter.
* It arms “pending” states when price **enters a zone from the correct side**, then confirms:
* **BUY (long):** price reclaims above support and recent CVD is strongly positive.
* **SELL (short):** price rejects below resistance and recent CVD is strongly negative.
Only these two CVD signals (`buySignal` / `sellSignal`) open trades.
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### Strategy Logic
* **Entries**
* `buySignal` → open **long** (if flat).
* `sellSignal` → open **short** (if flat).
* No pyramiding; one position at a time.
* **Exits (only TP & SL)**
* Long: TP at `avg_price * (0.5 + TP%)`, SL at `avg_price * (1 – SL%)`.
* Short: TP at `avg_price * (0.5 – TP%)`, SL at `avg_price * (1 + SL%)`.
* No opposite-signal exits.
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### Extras
* **Reversal markers** on yellow/purple zones and **breakout/retest markers** are plotted for context and alerts but **do not trigger entries**.
* Zone width and “thickening” are ATR-based so important touches and near-touches are easy to see.
* Only suited for **1m intraday scalping** (e.g. XAU/USD), but can be tested on other markets/timeframes.
