Caja TavoStrategy based on "The Box" by Z and Scott
This strategy is based on measuring price volatility one hour before the market opens and half an hour after.
The trade is made in the direction that breaks the upper or lower limits.rior o inferior.
Volatilite
Bar-Close Confirmed SupertrendOverview
This indicator is a Supertrend-style trend follower that confirms direction changes only after a bar closes. Trend flips are determined using the previous bar’s close relative to the bands, which helps avoid intrabar changes during live candles.
How it works
Computes ATR (Average True Range)
Builds upper/lower bands using ATR and a multiplier
Updates trend direction only when a prior candle confirms a break of the band
Confirmation logic (bar-close based)
Trend direction is updated using conditions based on the previous candle, such as:
close > upper → confirm uptrend
close < lower → confirm downtrend
Because signals are confirmed on the prior bar, trend changes and markers are displayed only when confirmation exists.
Signals
Uptrend confirmation: prior candle closes above the upper band → bullish marker
Downtrend confirmation: prior candle closes below the lower band → bearish marker
Inputs
ATR Length (default 10)
ATR Multiplier (default 3.0)
Notes
This script is intended for bar-close workflows. Behavior and responsiveness may differ across markets and timeframes depending on volatility and chosen settings.
yaman short longThis indicator provides clear Long and Short signals to help traders identify potential market direction and trading opportunities with higher confidence.
It is designed to follow price momentum and trend strength, allowing traders to enter trades when the market shows clear directional bias. The indicator focuses on clean signals and avoids unnecessary noise, making it suitable for both beginners and experienced traders.
Key Features:
Clear Long and Short signals displayed on the chart
Helps identify potential trend continuation and reversals
Designed to reduce false signals during choppy market conditions
Suitable for scalping, intraday, and swing trading
Works across multiple markets and timeframes
How to Use:
Long Signal: Indicates potential upward movement when bullish conditions align
Short Signal: Indicates potential downward movement when bearish conditions align
Best used with proper stop-loss and risk management rules
Can be combined with support/resistance or higher timeframe confirmation
Best Markets:
Forex pairs
Gold (XAUUSD)
Cryptocurrencies
Indices
Notes:
Signals are generated after candle close
The indicator does not repaint
This tool is meant to assist decision-making, not guarantee profits
Big Trend Catcher: Dual-Gate EMA & ATR Trailing Swing TraderThe Big Trend Catcher: Long-Only Progressive Swing System
OVERVIEW
The Big Trend Catcher is a high-conviction, long-only swing trading strategy designed to identify and ride sustained market moves. Unlike traditional trend-following systems that often get "chopped out" during sideways consolidation, this strategy utilizes a Dual-Gate Filter to ensure you only enter when short-term momentum and the long-term trend are in total alignment.
It is specifically tuned for high-growth stocks and ETFs where capturing the lion’s share of a multi-week or multi-month move is the primary objective.
CORE LOGIC: THE DUAL-GATE SYSTEM
To maintain a high quality of entries, the strategy requires a "confirmed launch" through two distinct filters:
The Momentum Gate (20 EMA): Identifies immediate price acceleration and volume-backed impulse.
The Long-Term Gate (100 EMA): Acts as the ultimate trend filter. The script utilizes a "Signal Memory" logic—if an impulse happens while price is still below the 100 EMA, the trade is held in a "Pending" state. The entry only triggers once the price closes firmly above the 100 EMA.
Goal: This prevents "bottom fishing" in established downtrends and keeps you in cash during sideways "death loops" when the long-term direction is unclear.
KEY FEATURES
1. Progressive Pyramiding (Scale-In)
The biggest profits in swing trading are often made by adding to winners. This system features two automated scale-in triggers:
Velocity Adds (VOLC): Adds to the position if the stock is up >10% and moving with rising momentum, allowing you to build a larger position as the trend proves its strength.
Pullback Adds: Adds to the position when the price tests the 20 EMA and holds, allowing you to buy the "dip" within a healthy uptrend.
2. The Phoenix Re-Entry
This logic is designed to catch "V-shaped" recoveries. If the strategy exits on a trend break but the price aggressively reclaims the 20 EMA on massive volume shortly after, it re-enters the trade. This ensures you aren't left behind during the second leg of a major run after a temporary shakeout.
3. Iron-Floor ATR Exit
We use a 3.5x ATR Trailing Stop combined with the 100 EMA. This wider-than-average "breathing room" is designed to keep you in for significant gains while ignoring the minor daily volatility that often shakes out traders with tighter stops.
HOW TO USE
Best Timeframes: Daily (D) is recommended for identifying major cycles, but it can be applied to the 4-Hour (4H) for more active swing trading.
Settings:
* 20 EMA: Your short-term momentum guide.
* 100 EMA: Your long-term trend guide.
* ATR Multiplier: Set to 3.5 for maximum "trend hugging."
SUMMARY OF VISUALS
Blue Line (100 EMA): The Long-Term Trend.
Yellow Line (20 EMA): The Short-Term Momentum.
Red Stepped Line: Your ATR Trailing Floor (The "Iron Floor").
Lime Triangle: Initial Trade Entry.
Blue/Orange Shapes: Progressive Scale-in points.
Aggro-15min Pro V4.2 [SMA200 + Vortex] (v6 Ready)🚀 Aggro-15min Pro
Aggro-15min Pro is a professional-grade algorithmic strategy optimized for the 15-minute timeframe. It combines structural trend analysis with aggressive momentum tracking to capture high-probability swings while filtering out market noise.
🛠️ How the Strategy Works
1. Structural Trend (The "Guardrail")
200 SMA: The strategy identifies the primary market direction. It only buys above the 200 SMA and only sells below it, ensuring you stay on the side of institutional flow.
2. Execution Trigger (The "Signal")
EMA Cross (9/50): A crossover of the 9-period Fast EMA and 50-period Slow EMA triggers the entry, identifying a confirmed shift in medium-term momentum.
3. Momentum Engine (The "Vortex")
Vortex Indicator (VI): Validates the "thrust" behind the move.
Dynamic Exit: Includes a "Vortex Reverse" logic that closes trades early if the directional energy fades, preserving capital before a full reversal occurs.
4. Risk & Volatility
ADX Filter: Prevents entries during low-volatility "sideways" periods.
ATR Risk Management: Uses the Average True Range to set dynamic Stop Loss and Take Profit levels that adapt to current market volatility.
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# 📂 STRATEGY PACKAGE: AGGRO-15MIN PRO
**Version:** 4.2 (Pine Script v6 Ready)
**Asset Class:** Crypto, Forex, Indices
**Timeframe:** 15 Minutes
---
## 📘 1. OPERATIONS MANUAL (English)
### 🟢 Strategy Overview
Aggro-15min Pro is a momentum-based trend-following system. It uses a "Triple-Filter" logic to ensure that trades are only taken when long-term trend, medium-term momentum, and short-term volatility are perfectly aligned.
### 🟢 Technical Indicators Setup
* **Structural Filter:** 200-period Simple Moving Average (SMA).
* **Trigger Engine:** 9-period & 50-period Exponential Moving Averages (EMA).
* **Momentum Engine:** 14-period Vortex Indicator (VI).
* **Strength Filter:** 14-period Average Directional Index (ADX).
* **Volatility/Exits:** 14-period Average True Range (ATR).
### 🟢 Entry Checklist
#### LONG Position:
1. **Trend:** Price is **ABOVE** the 200 SMA.
2. **Trigger:** 9 EMA crosses **ABOVE** the 50 EMA.
3. **Vortex:** VIP (Positive) is **ABOVE** VIM (Negative).
4. **Strength:** ADX is **ABOVE** 20.
#### SHORT Position:
1. **Trend:** Price is **BELOW** the 200 SMA.
2. **Trigger:** 9 EMA crosses **BELOW** the 50 EMA.
3. **Vortex:** VIM (Negative) is **ABOVE** VIP (Positive).
4. **Strength:** ADX is **ABOVE** 20.
### 🟢 Exit Management
* **Take Profit (TP):** $3.0 \times ATR$ (Risk/Reward 1:2).
* **Stop Loss (SL):** $1.5 \times ATR$.
* **Dynamic Exit:** If the Vortex lines cross in the opposite direction (e.g., VIM > VIP during a Long), the strategy closes the position immediately to lock in profits or minimize loss.
---
1H ETH Volume Breakout [ADX Filtered]Title: 1H ETH Volume Breakout w/ ADX Filter
Description:
🚀 Strategy Overview
This strategy is a high-precision Volatility Breakout system designed specifically for Ethereum (ETH) on the 1H timeframe. It focuses on catching explosive moves while aggressively filtering out market noise and "chop" to protect capital.
Unlike standard breakout strategies that get wrecked in sideways markets, this script uses a multi-layer confirmation system (Volume + Trend + Momentum + ADX) to ensure high-probability entries.
🧠 The Logic (How it works)
Keltner Channel Breakout: We use Keltner Channels (Length 22, Multiplier 2.0) instead of Bollinger Bands because they adapt better to ETH's unique volatility, reducing fake-outs.
Volume Confirmation: A trade is only taken if the current volume spikes above the moving average. "No Volume = No Trade."
Trend Filter (220 EMA): We only trade Long when price is above the 220 EMA, and Short when below. We trade with the dominant trend, never against it.
The "Chop Killer" (ADX Filter): An added ADX filter ensures the trend has real strength before entering. If the market is flat (ADX < 20), the strategy sits on the sideline.
🛡️ Risk Management (The "Fee Crusher")
Dynamic Stop Loss: Uses ATR (4.0) to give trades room to breathe without getting wicked out.
Trailing Stop: Activates after a 3% gain to lock in profits during big pumps.
Money Management: Includes a built-in Compounding feature (Optional).
⚙️ Recommended Settings
Coin: ETH/USD or ETH/USDT
Timeframe: 1 Hour (1H)
Leverage: 2x (Recommended)
Exchange Fees: Tuned for 0.1% fees.
⚠️ Disclaimer
Past performance is not indicative of future results. Please backtest with your own exchange settings before using real capital. This is an open-source tool for educational purposes.
Professional Grid & Reversal Bot v10 (Binance Style)Professional Grid & Reversal Bot v10 (Binance Style) – Open Source & Educational
About this Script:
This script is an advanced Grid Trading & Smart Reversal strategy, inspired by professional Binance-style execution. It is designed as an educational, open-source tool for traders who want to understand market dynamics, grid logic, and risk management.
How it Works:
1️⃣ Grid Execution:
• Divides the price range between the high and low into multiple levels (Grids).
• Opens Buy orders in the lower half and Sell orders in the upper half.
• Levels are calculated dynamically based on the highest and lowest prices over a selected lookback period.
2️⃣ Smart Reversal System:
• Detects price touches on the high or low range boundaries to identify potential reversal points.
• Opens Buy orders at the lows and Sell orders at the highs using a configurable confirmation percentage (revPct).
• Helps traders capture short-term price swings effectively.
3️⃣ Risk & Size Management:
• Position sizing based on USD amount and leverage.
• Automatic Take Profit (TP) and Stop Loss (SL) for every trade.
• Controls overtrading via the "pyramiding" parameter (max open trades).
4️⃣ Advanced Visualization:
• Plots the grid range with high/low levels and fills the background for clear context.
• Highlights potential Supply and Demand Zones.
• Displays a dynamic "Binance-style" Order Book table showing Side, Price, Quantity, and PnL.
5️⃣ Key Counters & Indicators:
• levelsArr → Stores all grid levels for execution and plotting.
• touchedHigh / touchedLow → Monitors range touches to trigger reversals.
• strategy.openprofit → Displays live open trade PnL directly on the chart.
Additional Features:
• Supports both English and Arabic languages.
• Dark Theme optimized for readability.
• Dynamic control panel updates on every bar.
• Flexible settings for Auto or Manual grid range updates.
User Guidance:
• This script is for educational purposes only; it does not guarantee profits.
• We recommend adjusting Grid Levels, Reversal Percentage, and Trade Size to experiment with different strategies.
Community Engagement:
• Suggestions and improvements are welcome! 💡
• If you have ideas for new features, let's develop them together to enhance learning.
• Please support the script with a Like & Boost if you find it useful.
• Encourages knowledge sharing to improve collective performance.
License:
Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
Free for educational use only. Please give credit to the author when sharing or modifying the script.
Simple RSI Strategy - Rule Based Higher Timeframe Trading
HOW IT WORKS
With the default settings, the strategy buys when RSI reaches 30 and closes when RSI reaches 40 .
That’s it.
A simple, rule-based mean reversion strategy designed for higher timeframes , where market noise is lower and trading becomes easier to manage.
Core logic:
Long when RSI moves into oversold territory
Exit when RSI mean-reverts upward
Optional short trades from overbought levels
One position at a time (no pyramiding)
No filters.
No discretion.
Just clear, testable rules.
MARKETS & TIMEFRAMES
This strategy is intended for:
Indices (Nasdaq, S&P 500, DAX, etc.)
Liquid futures and CFDs
Higher timeframes: 2H, 4H and Daily
The published example is Nasdaq (NDX) on the 2-hour timeframe .
Higher timeframes are strongly recommended.
HOW TO USE IT
Apply the strategy on a higher timeframe
Adjust RSI levels per market if needed
Use TradingView alerts to avoid constant screen-watching
Focus on execution, risk control, and consistency
This strategy is meant to be a building block , not a complete trading business on its own.
For long-term consistency, it works best when combined with other uncorrelated, rule-based systems.
IMPORTANT
This is not financial advice
All results are historical and not indicative of future performance
Always forward-test and apply proper risk management
For additional notes, setups and related systems, visit my TradingView profile page .
BE-QuantFlow: Adaptive Momentum Trading█ Overview: QuantFlow: Adaptive Momentum Trading
QuantFlow is a sophisticated algorithmic momentum trading method designed specifically for indices and high-beta stocks. However, its logic is universal; with appropriate parameter tuning, it adapts to various asset classes and timeframes.
While the standard momentum indicators (like RSI or MACD) simply measure how fast price is moving (Velocity), QuantFlow analyzes the quality and conviction of the trend . Features like Dynamic Volatility Filtering and Trend Shielding, combined with volatility weighting and a "Dual-Line" approach to distinguish between a sustainable institutional trend and a temporary retail spike, make the indicator unique and more powerful.
█ Why QuantFlow ?
Quant (The Engine): This replaces subjective guessing with objective math.
Instead of just seeing that the price is "up," we measure "how it got there". For example, a stock that rises 1 currency value every day for 10 days (smooth trend) gets a much higher score than a stock that jumps 10 currency value in one minute and does nothing else (erratic noise). This mathematical rigor provides the structure.
█ Core Logic & Philosophy
To understand how QuantFlow calculates momentum, imagine a "Tug-of-War" between Buyers (Bulls) and Sellers (Bears). Most indicators (like RSI) use a single line. If RSI is at 50, it means "Neutral." But "Neutral" can mean two very different things:
Peace: Nothing is happening. No one is buying or selling.
War: Buyers are pushing hard, but Sellers are pushing back equally hard. Volatility is massive.
A single line hides this reality. QuantFlow splits the market into two separate scores:
Bull Score (Green Line): How hard are the buyers pushing?
Bear Score (Red Line): How hard are the sellers pushing?
The Layman's Advantage:
If both lines are low = Sleepy Market (Avoid).
If Green is high and Red is low = Clean Uptrend (Buy).
If Red is high and Green is low = Clean Downtrend (Sell).
If both lines are high = Chaos/War Zone (Wait).
█ How it Weight "Sustenance" (The Critical Quality Check)
This is the most unique aspect of QuantFlow: Trend direction alone is not enough; Sustenance is weighed equally . Standard indicators treat every 10 currency value movements the same way with no distinction. However, QuantFlow asks, "Did you hold the ground you gained?"
Scenario A (High Sustenance) : A stock opens at 100, marches to 110, and closes at 110.
Verdict : Buyers pushed up and sustained the price.
QuantFlow Weight : 100%. This is a high-quality move.
Scenario B (Low Sustenance) : A stock opens at 100, spikes to 110, but gets sold off to close at 102.
Verdict : Buyers pushed up (Trend is Up), but failed to sustain it (Long Wick).
QuantFlow Weight : 20%. This is treated as "Noise" or a trap.
By mathematically weighing the Close Location Value (where the candle closes relative to its high/low), QuantFlow filters out "Gap-and-Fade" traps and exhaustion spikes that fool traditional indicators.
Comparisons: QuantFlow vs. The Rest
Calculation Logic : Standard RSI/MACD measures simple price change over time. QuantFlow measures Price Change 'times (x)' Conviction (Sustenance Weighting).
Visual Output : Standard tools show a single line (0-100), often hiding market conflict. QuantFlow displays Dual Lines (Bull vs Bear Intensity) to reveal the true state of the battle.
Trap Handling : Standard indicators are often fooled by sharp spikes. QuantFlow ignores "Gap-and-Fade" moves with poor closing conviction.
Adaptability : Standard tools use static levels (e.g., Overbought > 70). QuantFlow uses Dynamic Bands that adjust automatically to recent volatility.
█ Dynamic Volatility Filtering
Unlike standard indicators that use fixed levels (e.g., "Buy if RSI > 50"), QuantFlow acknowledges that "50" means something different in a quiet market versus a crashing market. This section explains the statistical engine driving the signals.
The Problem with Static Levels : In a low-volatility environment, a momentum score of 55 might indicate a massive breakout. In a high-volatility environment, a score of 55 might just be random noise. A fixed threshold cannot handle both scenarios.
The Solution: Adaptive Statistics : The script maintains a memory of the Momentum Events. It doesn't just look at price; it looks at where the momentum occurred in the past and draws a "Noise Zone" (Grey Band). This logic acts as a "Smart Gatekeeper" for trade entries:
Scenario A: Inside the Noise (The Filter)
If a new momentum signal happens inside the Noise Zone, the script assumes it is likely chop or noise.
Action : It forces a wait period. The signal is delayed until the trend sustains itself for Confirm Bars; else the signal is cancelled. This filters out ~70% of false signals in sideways markets.
Scenario B: Outside the Noise (The Breakout)
If a new momentum signal happens outside the Noise Zone (or the momentum score smashes through the Upper Band), it is statistically significant (an outlier event).
Action: It triggers an Immediate Entry. No waiting is required because the move is powerful enough to escape the historical noise zone.
█ The ⚠️ "Warning" System (Heads-up for Smart Reversals)
While you are directional if there is potential reversal signal, it provides the heads-up warning for a better decision-making
█ Special Utility: Ghost Mode
For intraday traders, the biggest disruption to "Flow" is the mandatory broker square-off at 3:15 PM (considering Indian Market). Often, a trend continues overnight, and the trader misses the gap-up opening the next morning because their algo was flat.
Ghost Mode is a unique feature that runs silently in the background:
At Square-off: The strategy closes your official position to satisfy the broker.
In the Background: It keeps the trade "alive" virtually (Ghost).
Next Morning: If the market opens in the trend's favor, the strategy re-enters the trade automatically. This approach ensures you capture the full swing of the trend, even if you are forced to exit at the previous session.
█ Advice on this indicator:
Parameter Calibration: The default settings are optimized for BankNifty on 5-minute charts. If you trade stocks, crypto, commodities, or any higher timeframes (e.g., 15-min or hourly), you must adjust these.
Low Volatility Assets: Reduce Stop Multiplier to 2.0.
High Volatility Assets: Increase Momentum Lookback to 50 to filter noise.
Confluence (Additional Confirmation): While QuantFlow is a complete system, using it alongside Key Support/Resistance Levels or Volume Profile provides the highest probability setups.
ML-Inspired Adaptive Momentum Strategy (TradingView v6)This strategy demonstrates an adaptive momentum approach using volatility-normalized trend strength. It is designed for educational and analytical purposes and uses deterministic, fully transparent logic compatible with Pine Script v6.
ML-Inspired Concept (Educational Context)
Pine Script cannot train or execute real machine-learning models.
Instead, this strategy demonstrates ML-style thinking by:
Converting price data into features
Normalizing features to account for volatility differences
Producing a bounded confidence score
Applying thresholds for decision making
This is not predictive AI and does not claim forecasting capability.
Strategy Logic
EMA is used to measure directional bias
EMA slope represents momentum change
ATR normalizes the slope (feature scaling)
A clamped score between −1 and +1 is generated
Trades trigger only when the score exceeds defined thresholds
Risk & Execution
Position size capped at 5% equity
Commission and slippage included for realistic testing
Signals are calculated on closed bars only
Purpose
This script is intended to help traders explore adaptive momentum concepts and understand how feature normalization can be applied in systematic trading strategies.
Algomist - Adaptive Velocity Cross🚀 Algomist: The Adaptive Velocity Cross (AVC)
Automate Your Edge
This strategy transcends the limitations of classic Moving Average (MA) crossovers. The Adaptive Velocity Cross (AVC) is a state-of-the-art trend-following system designed for automated execution, filtering out low-probability whipsaws and prioritizing high-momentum breakouts in volatile markets.
It's not just a signal generator; it's a fully automated, risk-managed trading plan that delivers structured trade signals directly to your Algomist account.
🔥 Key Features & Technology
Adaptive Hull Moving Averages (HMA): Utilizes the Hull MA to significantly reduce lag compared to standard EMAs and SMAs. The faster and slower HMAs provide a highly responsive gauge of short-term and medium-term trend direction.
Multi-Layer Volatility Filtering: Trades are strictly prohibited during flat, low-volatility market conditions.
Current Timeframe Filter (ATRMinFilter): Ensures trades only fire when current market momentum is strong enough to carry the trend.
Higher Timeframe Filter: Checks the ATR on a higher timeframe (e.g., 1H) to confirm the structural trend strength, preventing entries during tight squeezes.
Visual Trend Velocity: The space between the Fast (Blue) and Slow (Pink) HMAs is colored and filled, providing an immediate visual cue for trend direction and strength (width of the band).
Asymmetric Risk Management: Uses the dynamic Average True Range (ATR) to calculate Stop Loss and Take Profit levels, ensuring risk and reward are proportional to current market volatility.
⚙️ How It Works (The Logic)
The AVC only executes a trade when all three high-conviction criteria are met:
Trend Signal: The Fast $\text{HMA}$ crosses the Slow $\text{HMA}$ (Crossover).
Volatile Market Confirmation: The market must be sufficiently volatile on both the current timeframe and the higher structural timeframe ($\text{ATR}$ filters passed).
Risk Management: A defined $\text{SL}$ (Stop Loss) and $\text{TP}$ (Take Profit) are calculated based on the current market $\text{ATR}$ to manage the position before entry.
🤖 Automation Ready
The strategy is built with automation as the priority. Upon a confirmed entry, the script sends a cleanly formatted JSON string via a TradingView Webhook alert to Algomist. Create your account and get your own web hook @ www.algomist.app
Example Alert Output:
{
"symbol": "ETHUSDC",
"side": "LONG",
"entry_price": 67500.0,
"stop_loss": 66000.0,
"take_profit": 70000.0,
"timestamp": 1766715660462
}
This signal is ready for immediate consumption by your Algomist execution engine, ensuring lightning-fast and error-free order placement.
📊 Recommended Use
Asset Class: Highly effective on high-liquidity, high-volatility assets (e.g., Crypto Majors, Forex Pairs, Indices).
Timeframes: Works best on 1m to 15 min charts.
Risk Profile: Medium-to-High frequency trend-following system.
Disclaimer: The strategy code provided is for informational and educational purposes. Past performance is not indicative of future results. Always backtest and forward-test any automated strategy extensively before using real capital.
ilker %90This strategy is a short-term momentum approach based on moving averages and volume. Studies show it performs more effectively on the 1-hour and 4-hour timeframes. Take-profit and stop-loss distances are kept short, resulting in a high win rate, while the profit factor ranges between 1.4 and 2.
Golden Vector Trend Orchestrator (GVTO)Golden Vector Trend Orchestrator (GVTO) is a composite trend-following strategy specifically engineered for XAUUSD (Gold) and volatile assets on H4 (4-Hour) and Daily timeframes.
This script aims to solve a common problem in trend trading: "Whipsaws in Sideways Markets." Instead of relying on a single indicator, GVTO employs a Multi-Factor Confluence System that filters out low-probability trades by requiring alignment across Trend Structure, Momentum, and Volatility.
🛠 Methodology & Logic
The strategy executes trades only when four distinct technical conditions overlap (Confluence). If any single condition is not met, the trade is filtered out to preserve capital.
1. Market Structure Filter (200 EMA)
Indicator: Exponential Moving Average (Length 200).
Logic: The 200 EMA acts as the baseline for the long-term trend regime.
Bullish Regime: Price must close above the 200 EMA.
Bearish Regime: Price must close below the 200 EMA.
Purpose: Prevents counter-trend trading against the macro direction.
2. Signal Trigger & Trailing Stop (Supertrend)
Indicator: Supertrend (ATR Length 14, Factor 3.5).
Logic: Uses Average True Range (ATR) to detect trend reversals while accounting for volatility.
Purpose: Provides the specific entry signal and acts as a dynamic trailing stop-loss to let profits run while cutting losses when the trend invalidates.
3. Volatility Gatekeeper (ADX Filter)
Indicator: Average Directional Index (Length 14).
Threshold: > 25.
Logic: A high ADX value indicates a strong trend presence, regardless of direction.
Purpose: This is the most critical filter. It prevents the strategy from entering trades during "choppy" or ranging markets (consolidation zones) where trend-following systems typically fail.
4. Momentum Confirmation (DMI)
Indicator: Directional Movement Index (DI+ and DI-).
Logic: Checks if the buying pressure (DI+) is physically stronger than selling pressure (DI-), or vice versa.
Purpose: Ensures that the price movement is backed by genuine momentum, not just a momentary price spike.
📋 How to Use This Strategy
🟢 LONG (BUY) Setup
A Buy signal is generated only when ALL of the following occur simultaneously:
Price Action: Price closes ABOVE the 200 EMA (Orange Line).
Trigger: Supertrend flips to GREEN (Bullish).
Strength: ADX is greater than 25 (Strong Trend).
Momentum: DI+ (Plus Directional Indicator) is greater than DI- (Minus).
🔴 SHORT (SELL) Setup
A Sell signal is generated only when ALL of the following occur simultaneously:
Price Action: Price closes BELOW the 200 EMA (Orange Line).
Trigger: Supertrend flips to RED (Bearish).
Strength: ADX is greater than 25 (Strong Trend).
Momentum: DI- (Minus Directional Indicator) is greater than DI+ (Plus).
🛡 Exit Strategy
Stop Loss / Take Profit: The strategy utilizes the Supertrend Line as a dynamic Trailing Stop.
Exit Long: When Supertrend turns Red.
Exit Short: When Supertrend turns Green.
Note: Traders can also use the real-time P/L Dashboard included in the script to manually secure profits based on their personal Risk:Reward ratio.
📊 Included Features
Real-Time P/L Dashboard: A table in the top-right corner displays the current trend status, ADX strength, and the Unrealized Profit/Loss % of the current active position.
Smart Labeling: Buy/Sell labels are coded to appear only on the initial entry trigger. They do not repaint and do not spam the chart if the trend continues (no pyramiding visualization).
Visual Aids: Background color changes (Green/Red) to visually represent the active trend based on the Supertrend status.
⚠️ Risk Warning & Best Practices
Asset Class: Optimized for XAUUSD (Gold) due to its high volatility nature. It also works well on Crypto (BTC, ETH) and Major Forex Pairs.
Timeframe: Highly recommended for H4 (4 Hours) or D1 (Daily). Using this on lower timeframes (M5, M15) may result in false signals due to market noise.
News Events: Automated strategies cannot predict economic news (CPI, NFP). Exercise caution or pause trading during high-impact economic releases.
Algomist.app v1.0🚀 WMA Crossover Momentum Scalper: Algomist.app AUTO-EXECUTION
This strategy is a momentum-based trend-following system optimized for fully automated, high-frequency trade execution via algomist.app webhooks. It systematically enters trades based on a powerful moving average crossover, confirmed by both volume and volatility filters.
⚙️ Core Strategy Logic
This script is designed to capture short- to medium-term moves in trending markets by combining three key indicators:
Trend Confirmation (WMA Crossover): The primary signal is generated when a Fast WMA (50-period) crosses the Slow WMA (100-period). This crossover confirms the shift in the prevailing trend direction.
Volume Filter (VWAP): The trade is only taken if the price is trading above the VWAP for Long entries, or below the VWAP for Short entries. This ensures the trade is aligned with the asset's average price relative to trading volume.
Volatility Filter (ATR): A minimum Average True Range (ATR) filter is applied. This is critical for avoiding entries during periods of extreme low volatility ("chop"), ensuring the market has enough movement to justify the trade.
🔗 Algomist.app Automation Ready
This is the most important feature. The script contains custom-coded alert() functions that output a perfect JSON payload, making it 100% compatible with the algomist.app webhook infrastructure.
Seamless Execution: The strategy instantly transmits all required parameters—symbol, side, entry_price, dynamic stop_loss, and dynamic take_profit—directly to your MT5 terminal through the algomist.app connector.
Simple Setup: To enable live automation, you only need to configure a TradingView alert using the provided webhook URL and the {{strategy.order.alert_message}} placeholder on the bar's close.
Default Asset: The webhook is pre-configured to trade the ETHUSDC symbol. This can be easily adapted to other crypto or Forex pairs within the algomist.app settings.
🛡️ Dynamic Risk Management (ATR-Based)
Risk management is dynamic, ensuring the Stop Loss and Take Profit levels automatically adapt to current market volatility:
Stop Loss (SL): Placed at a customizable (x) * ATR distance from the entry price. The default setting is 3.0x ATR.
Take Profit (TP): Placed at a customizable (x) * ATR distance from the entry price. The default setting is 9.0x ATR, offering a fixed Reward-to-Risk ratio of 3:1 (9.0 / 3.0).
Position Sizing: The script uses strategy.percent_of_equity = 10% for backtesting, but the algomist.app execution is based on an internal calculation using a small percentage (e.g., 5%) of a leveraged notional value for illustrative purposes. Users must set their risk size within the algomist.app platform.
Disclaimer: This script is provided as an example for Algomist.app users and is NOT financial advice. Backtest thoroughly across various assets and timeframes. Past performance is not indicative of future results. The user assumes all responsibility for live trading risk.
Ichimoku Cloud Strategy - 1H HyperliquidStategy for Hyperliquid 1hr time frame using Ichimoku's Cloud.
Tailwind.(BTC)Imagine the price of Bitcoin is like a person climbing a staircase.
The Steps (Grid): Instead of watching every single price movement, the strategy divides the market into fixed steps. In your configuration, each step measures **3,000 points**. (Examples: 60,000, 63,000, 66,000...).
The Signal: We buy only when the price climbs a full step decisively.
The "Expensive Price" Filter: If the price jumps the step but lands too far away (the candle closes too high), we do not buy. It is like trying to board a train that has already started moving too fast; the risk is too high.
Rigid Exits: The Take Profit (TP) and Stop Loss (SL) are calculated from the edge of the step, not from the specific price where you managed to buy. This preserves the geometric structure of the market.
The Code Logic (Step-by-Step)
A. The Math of the Grid (`math.floor`)
pinescript
level_base = math.floor(close / step_size) * step_size
This is the most important line.
What does it do? It rounds the price down to the nearest multiple of 3,000.
Example: If BTC is at 64,500 and the step size is 3,000:
1. Divide: $64,500 / 3,000 = 21.5$
2. `math.floor` (Floor): Removes the decimals $\rightarrow$ remains $21$.
3. Multiply: $21 * 3,000 = 63,000$.
Result: The code knows that the current "floor" is **63,000**, regardless of whether the price is at 63,001 or 65,999.
B. The Strict Breakout (`strict_cross`)
pinescript
strict_cross = (open < level_base) and (close > level_base)
Most strategies only check if `close > level`. We do things slightly differently:
`open < level_base`: Requires the candle to have "born" *below* the line (e.g., opened at 62,900).
`close > level_base`: Requires the candle to have *finished* above the line (e.g., closed at 63,200).
Why? This avoids entering on gaps (price jumps where the market opens already very high) and confirms that there was real buying power crossing the line.
C. The "Expensive Price" Filter (`max_dist_pct`)
pinescript
limit_price_entry = level_base + (step_size * (max_dist_pct / 100.0))
price_is_valid = close <= limit_price_entry
Here you apply the percentage rule:
-If the level is 63,000 and the next is 66,000 (a difference of 3,000).
-If `max_dist_pct` is **60%**, the limit is $63,000 + (60\% \text{ of } 3,000) = 64,800$.
-If the breakout candle closes at **65,000**, the variable `price_is_valid` will be **false** and it will not enter the trade. This avoids buying at the ceiling.
D. TP and SL Calculation (Anchored to the Level)
pinescript
take_profit = level_base + (step_size * tp_mult)
stop_loss = level_base - (step_size * sl_mult)
Note that we use `level_base` and not `close`.
-If you entered because the price broke 63,000, your SL is calculated starting from 63,000.
-If your SL is 1.0x, your stop will be exactly at 60,000.
This is crucial: If you bought "expensive" (e.g., at 63,500), your real stop is wider (3,500 points) than if you bought cheap (63,100). Because you filter out expensive entries, you protect your Risk/Reward ratio.
E. Visual Management (`var line`)
The code uses `var` variables to remember the TP and SL lines and the `line.set_x2` function to stretch them to the right while the operation remains open, providing that visual reference on the chart until the trade ends.
Workflow Summary
Strategy Parameters:
Total Capital: $20,000
We will use 10% of total capital per trade.
Commissions: 0.1% per trade.
TP: 1.4
SL: 1
Step Size (Grid): 3,000
We use the 200 EMA as a trend filter.
Feel free to experiment with the parameters to your liking. Cheers.
PMax - Asymmetric MultipliersDescription: This script is an enhanced version of the popular PMax (Profit Maximizer) indicator, originally developed by KivancOzbilgic. It has been converted into a full strategy with advanced customization options for backtesting and trend following.
Key Features & Modifications:
Asymmetric ATR Multipliers: Unlike the standard version, this script allows you to set different ATR multipliers for Upper (Short/Resistance) and Lower (Long/Support) bands.
Default Upper: 1.5 (Tighter trailing for Short positions)
Default Lower: 3.0 (Wider trailing for Long positions to avoid whipsaws)
Expanded MA Types: Added HULL (HMA) and VAR (Variable Index Dynamic Average) options.
VAR is highly recommended for filtering out noise in ranging markets.
HULL is ideal for scalping and faster reactions.
Built-in Risk Management: A fixed 5% Stop Loss mechanism is integrated into the strategy. It protects your capital by closing positions if the price moves 5% against you, even if the trend hasn't reversed yet.
Visibility Fix: Solved the issue where the PMax line would disappear or start at zero in the initial bars.
How to Use:
Use the VAR MA type for trend following in volatile markets.
Adjust the "Stop Loss Percent" input to fit your risk appetite.
The strategy employs an "Always In" logic (Long/Short) but respects the hard Stop Loss.
Credits: Original PMax logic by KivancOzbilgic.
Volatility Trend FollowerThe script combines several classic technical analysis techniques:
SuperTrend / Adaptive Band - The main idea comes from the SuperTrend indicator, which uses ATR (Average True Range) to create a trailing band that adapts to volatility
ATR (Average True Range) - A volatility measure developed by J. Welles Wilder Jr.
EMA (Exponential Moving Average) - Used as a global trend filter
Heikin Ashi - An option to smooth prices and reduce noise
Trend Following $BTC - Multi-Timeframe Structure + ReversTREND FOLLOWING STRATEGY - MULTI-TIMEFRAME STRUCTURE BREAKOUT SYSTEM
Strategy Overview
This is an enhanced Turtle Trading system designed for cryptocurrency spot trading. It combines Donchian Channel breakouts with multi-timeframe structure filtering and ATR-based dynamic risk management. The strategy trades both long and short positions using reverse signal exits to maximize trend capture.
Core Features
Multi-Timeframe Structure Filtering
The strategy uses Swing High/Low analysis to identify market structure trends. You can customize the structure timeframe (default: 3 minutes) to match your trading style. Only enters trades aligned with the identified trend direction, avoiding counter-trend positions that often lead to losses.
Reverse Signal Exit System
Instead of using fixed stop-losses or time-based exits, this strategy exits positions only when a reverse entry signal triggers. This approach maximizes trend profits and reduces premature exits during normal market retracements.
ATR Dynamic Pyramiding
Automatically adds positions when price moves 0.5 ATR in your favor. Supports up to 2 units maximum (adjustable). This pyramid scaling enhances profitability during strong trends while maintaining disciplined risk management.
Complete Risk Management
Fixed position sizing at 5000 USD per unit. Includes realistic commission fees of 0.06% (Binance spot rate). Initial capital set at 10,000 USD. All backtest parameters reflect real-world trading conditions.
Trading Logic
Entry Conditions
Long Entry: Close price breaks above the 20-period high AND structure trend is bullish (price breaks above Swing High)
Short Entry: Close price breaks below the 20-period low AND structure trend is bearish (price breaks below Swing Low)
Position Scaling
Long positions: Add when price rises 0.5 ATR or more
Short positions: Add when price falls 0.5 ATR or more
Maximum 2 units including initial entry
Exit Conditions
Long Exit: Triggers when short entry signal appears (price breaks 20-period low + structure turns bearish)
Short Exit: Triggers when long entry signal appears (price breaks 20-period high + structure turns bullish)
Default Parameters
Channel Settings
Entry Channel Period: 20 (Donchian Channel breakout period)
Exit Channel Period: 10 (reserved parameter)
ATR Settings
ATR Period: 20
Stop Loss ATR Multiplier: 2.0
Add Position ATR Multiplier: 0.5
Structure Filter
Swing Length: 300 (Swing High/Low calculation period)
Structure Timeframe: 3 minutes
Adjust these based on your trading timeframe and asset volatility
Position Management
Maximum Units: 2 (including initial entry)
Capital Per Unit: 5000 USD
Visualization Features
Background Colors
Light Green: Bullish market structure
Light Red: Bearish market structure
Dark Green: Long position entry
Dark Red: Short position entry
Optional Display Elements (Default: OFF)
Entry and exit channel lines
Structure high/low reference lines
ATR stop-loss indicator
Next position add level
Entry/exit labels
Alert Message Format
The strategy sends notifications with the following format:
Entry: "5m Long EP:90450.50"
Add Position: "15m Add Long 2/2 EP:91000.25"
Exit: "5m Close Long Reverse Signal"
Where the first part shows your current chart timeframe and EP indicates Entry Price
Backtest Settings
Capital Allocation
Initial Capital: 10,000 USD
Per Entry: 5,000 USD (split into 2 potential entries)
Leverage: 0x (spot trading only)
Trading Costs
Commission: 0.06% (Binance spot VIP0 rate)
Slippage: 0 (adjust based on your experience)
Best Use Cases
Ideal Scenarios
Trending markets with clear directional movement
Moderate to high volatility assets
Timeframes from 1-minute to 4-hour charts
Best suited for major cryptocurrencies with good liquidity
Not Recommended For
Highly volatile choppy/ranging markets
Low liquidity small-cap coins
Extreme market conditions or black swan events
Usage Recommendations
Timeframe Guidelines
1-5 minute charts: Use for scalping, consider Swing Length 100-160
15-30 minute charts: Good for short-term trading, Swing Length 50-100
1-4 hour charts: Suitable for swing trading, Swing Length 20-50
Optimization Tips
Always backtest on historical data before live trading
Adjust swing length based on asset volatility and your timeframe
Different cryptocurrencies may require different parameter settings
Enable visualization options initially to understand entry/exit points
Monitor win rate and drawdown during backtesting
Technical Details
Built on Pine Script v6
No repainting - uses proper bar referencing with offset
Prevents lookahead bias with lookahead=off parameter
Strategy mode with accurate commission and slippage modeling
Multi-timeframe security function for structure analysis
Proper position state tracking to avoid duplicate signals
Risk Disclaimer
This strategy is provided for educational and research purposes only. Past performance does not guarantee future results. Backtesting results may differ from live trading due to slippage, execution delays, and changing market conditions. The strategy performs best in trending markets and may experience drawdowns during ranging conditions. Always practice proper risk management and never risk more than you can afford to lose. It is recommended to paper trade first and start with small position sizes when going live.
How to Use
Add the strategy to your TradingView chart
Select your desired timeframe (1m to 4h recommended)
Adjust parameters based on your risk tolerance and trading style
Review backtest results in the Strategy Tester tab
Set up alerts for automated notifications
Consider paper trading before risking real capital
Tags
Trend Following, Turtle Trading, Donchian Channel, Structure Breakout, ATR, Cryptocurrency, Spot Trading, Risk Management, Pyramiding, Multi-Timeframe Analysis
---
Strategy Name: Trend Following BTC
Version: v1.0
Pine Script Version: v6
Last Updated: December 2025
Trend Following $ZEC - Multi-Timeframe Structure Filter + Revers# Trend Following CRYPTOCAP:ZEC - Strategy Guide
## 📊 Strategy Overview
Trend Following CRYPTOCAP:ZEC is an enhanced Turtle Trading system designed for cryptocurrency spot trading, combining Donchian Channel breakouts, multi-timeframe structure filtering, and ATR-based dynamic risk management for both long and short positions.
---
## 🎯 Core Features
1. Multi-Timeframe Structure Filtering
- Uses Swing High/Low to identify market structure
- Customizable structure timeframe (default: 1 minute)
- Only enters trades in the direction of the trend, avoiding counter-trend positions
2. Reverse Signal Exit
- No fixed stop-loss or fixed-period exits
- Exits only when a reverse entry signal triggers
- Maximizes trend profits, reduces premature exits
3. ATR Dynamic Pyramiding
- Adds positions when price moves 0.5 ATR in favorable direction
- Supports up to 2 units maximum (adjustable)
- Pyramid scaling to enhance profitability
4. Complete Risk Management
- Fixed position size (5000 USD per unit)
- Commission fee 0.06% (Binance spot rate)
- Initial capital 10,000 USD
---
## 📈 Trading Logic
Entry Conditions
✅ Long Entry:
- Close price breaks above 20-period high
- Structure trend is bullish (price breaks above Swing High)
✅ Short Entry:
- Close price breaks below 20-period low
- Structure trend is bearish (price breaks below Swing Low)
Add Position Conditions
- Long: Price rises ≥ 0.5 ATR
- Short: Price falls ≥ 0.5 ATR
- Maximum 2 units including initial entry
Exit Conditions
- Long Exit: When short entry signal triggers (price breaks 20-period low + structure turns bearish)
- Short Exit: When long entry signal triggers (price breaks 20-period high + structure turns bullish)
---
## ⚙️ Parameter Settings
Channel Settings
- Entry Channel Period: 20 (Donchian Channel breakout period)
- Exit Channel Period: 10 (reserved parameter, actually uses reverse signal exit)
ATR Settings
- ATR Period: 20
- Stop Loss ATR Multiplier: 2.0 (reserved parameter)
- Add Position ATR Multiplier: 0.5
Structure Filter
- Swing Length: 160 (Swing High/Low calculation period)
- Structure Timeframe: 1 minute (can change to 5/15/60, etc.)
Position Management
- Maximum Units: 2 (including initial entry)
- Capital Per Unit: 5000 USD
---
## 🎨 Visualization Features
Background Colors
- Light Green: Bullish structure
- Light Red: Bearish structure
- Dark Green: Long entry
- Dark Red: Short entry
Optional Display (Default: OFF)
- Entry/exit channel lines
- Structure high/low lines
- ATR stop-loss line
- Next add position indicator
- Entry/exit labels
---
## 📱 Alert Message Format
Strategy sends notifications on entry/exit with the following format:
- Entry: `1m Long EP:428.26`
- Add Position: `15m Add Long 2/2 EP:429.50`
- Exit: `1m Close Long Reverse Signal`
Where:
- `1m`/`15m` = Current chart timeframe
- `EP` = Entry Price
---
## 💰 Backtest Settings
Capital Allocation
- Initial Capital: 10,000 USD
- Per Entry: 5,000 USD (split into 2 entries)
- Leverage: 0x (spot trading)
Trading Costs
- Commission: 0.06% (Binance spot VIP0)
- Slippage: 0
---
## 🎯 Use Cases
✅ Best Scenarios
- Trending markets
- Moderate volatility assets
- 1-minute to 4-hour timeframes
⚠️ Not Suitable For
- Highly volatile choppy markets
- Low liquidity small-cap coins
- Extreme market conditions (black swan events)
---
## 📊 Usage Recommendations
Timeframe Suggestions
| Timeframe | Trading Style | Suggested Parameter Adjustment |
|-----------|--------------|-------------------------------|
| 1-5 min | Scalping | Swing Length 100-160 |
| 15-30 min | Short-term | Swing Length 50-100 |
| 1-4 hour | Swing Trading | Swing Length 20-50 |
Optimization Tips
1. Adjust swing length based on backtest results
2. Different coins may require different parameters
3. Recommend backtesting on 1-minute chart first before live trading
4. Enable labels to observe entry/exit points
---
## ⚠️ Risk Disclaimer
1. Past Performance Does Not Guarantee Future Results
- Backtest data is for reference only
- Live trading may be affected by slippage, delays, etc.
2. Market Condition Changes
- Strategy performs better in trending markets
- May experience frequent stops in ranging markets
3. Capital Management
- Do not invest more than you can afford to lose
- Recommend setting total capital stop-loss threshold
4. Commission Impact
- Frequent trading accumulates commission fees
- Recommend using exchange discounts (BNB fee reduction, etc.)
---
## 🔧 Troubleshooting
Q: No entry signals?
A: Check if structure filter is too strict, adjust swing length or timeframe
Q: Too many labels displayed?
A: Turn off "Show Labels" option in settings
Q: Poor backtest performance?
A:
1. Check if the coin is suitable for trend-following strategies
2. Adjust parameters (swing length, channel period)
3. Try different timeframes
Q: How to set alerts?
A:
1. Click "Alert" in top-right corner of chart
2. Condition: Select "Strategy - Trend Following CRYPTOCAP:ZEC "
3. Choose "Order filled"
4. Set notification method (Webhook/Email/App)
---
## 📞 Contact Information
Strategy Name: Trend Following CRYPTOCAP:ZEC
Version: v1.0
Pine Script Version: v6
Last Updated: December 2025
---
## 📄 Copyright Notice
This strategy is for educational and research purposes only.
All risks of using this strategy for live trading are borne by the user.
Commercial use without authorization is prohibited.
---
## 🎓 Learning Resources
To understand the strategy principles in depth, recommended reading:
- "The Complete TurtleTrader" - Curtis Faith
- "Trend Following" - Michael Covel
- TradingView Pine Script Official Documentation
---
Happy Trading! Remember to manage your risk 📈
Elliott Wave Full Fractal System v2.0Elliott Wave Full Fractal System v2.0 – Q.C. FINAL (Guaranteed R/R)
Elliott Wave Full Fractal System is a multi-timeframe wave engine that automatically labels Elliott impulses and ABC corrections, then builds a rule-based, ATR-driven risk/reward framework around the “W3–W4–W5” leg.
“Guaranteed R/R” here means every order is placed with a predefined stop-loss and take-profit that respect a minimum Reward:Risk ratio – it does not mean guaranteed profits.
Core Idea
This strategy turns a full fractal Elliott Wave labelling engine into a systematic trading model.
It scans fractal pivots on three wave degrees (Primary, Intermediate, Minor) to detect 5-wave impulses and ABC corrections.
A separate “Trading Degree” pivot stream, filtered by a 200-EMA trend filter and ATR-based dynamic pivots, is then used to find W4 pullback entries with a minimum, user-defined Reward:Risk ratio.
Default Properties & Risk Assumptions
The backtest uses realistic but conservative defaults:
// Default properties used for backtesting
strategy(
"Elliott Wave Full Fractal System - Q.C. FINAL (Guaranteed R/R)",
overlay = true,
initial_capital = 10000, // realistic account size
default_qty_type = strategy.percent_of_equity,
default_qty_value = 1, // 1% risk per trade
commission_type = strategy.commission.cash_per_contract,
commission_value = 0.005, // example stock commission
slippage = 0 // see notes below
)
Account size: 10,000 (can be changed to match your own account).
Position sizing: 1% of equity per trade to keep risk per idea sustainable and aligned with TradingView’s recommendations.
Commission: 0.005 cash per contract/share as a realistic example for stock trading.
Slippage: set to 0 in code for clarity of “pure logic” backtesting. Real-life trading will experience slippage, so users should adjust this according to their market and broker.
Always re-run the backtest after changing any of these values, and avoid using high risk fractions (5–10%+) as that is rarely sustainable.
1. Full Fractal Wave Engine
The script builds and maintains four pivot streams using ATR-adaptive fractals:
Primary Degree (Macro Trend):
Captures the large swings that define the major trend. Labels ①–⑤ and ⒶⒷⒸ using blue “Circle” labels and thicker lines.
Intermediate Degree (Trading Degree):
Captures the medium swings (swing-trading horizon). Uses teal labels ( (1)…(5), (A)(B)(C) ).
Minor Degree (Micro Structure):
Tracks short-term swings inside the larger waves. Uses red roman numerals (i…v, a b c).
ABC Corrections (Optional):
When enabled, the engine tries to detect standard A–B–C corrective structures that follow a completed 5-wave impulse and plots them with dashed lines.
Each degree uses a dynamic pivot lookback that expands when ATR is above its EMA, so the system naturally requires “stronger” pivots in volatile environments and reacts faster in quiet conditions.
2. Theory Rules & Strict Mode
Normal Mode: More permissive detection. Designed to show more wave structures for educational / exploratory use.
Strict Mode: Enforces key Elliott constraints:
Wave 3 not shorter than waves 1 and 5.
No invalid W4 overlap with W1 (for standard impulses).
ABC Logic: After a confirmed bullish impulse, the script expects a down-up-down corrective pattern (A,B,C). After a bearish impulse, it looks for up-down-up.
3. Trend Filter & Pivots
EMA Trend Filter: A configurable EMA (default 200) is used as a non-wave trend filter.
Price above EMA → Only long setups are considered.
Price below EMA → Only short setups are considered.
ATR-Adaptive Pivots: The pivot engine scales its left/right bars based on current ATR vs ATR EMA, making waves and trading pivots more robust in volatile regimes.
4. Dynamic Risk Management (Guaranteed R/R Engine)
The trading engine is designed around risk, not just pattern recognition:
ATR-Based Stop:
Stop-loss is placed at:
Entry ± ATR × Multiplier (user-configurable, default 2.0).
This anchors risk to current volatility.
Minimum Reward:Risk Ratio:
For each setup, the script:
Computes the distance from entry to stop (risk).
Projects a take-profit target at risk × min_rr_ratio away from entry.
Only accepts the setup if risk is positive and the required R:R ratio is achievable.
Result: Every order is created with both TP and SL at a predefined distance, so each trade starts with a known, minimum Reward:Risk profile by design.
“Guaranteed R/R” refers exclusively to this order placement logic (TP/SL geometry), not to win-rate or profitability.
5. Trading Logic – W3–W4–W5 Pattern
The Trading pivot stream (separate from visual wave degrees) looks for a simple but powerful pattern:
Bullish structure:
Sequence of pivots forms a higher-high / higher-low pattern.
Price is above the EMA trend filter.
A strong “W3” leg is confirmed with structure rules (optionally stricter in Strict mode).
Entry (Long – W4 Pullback):
The “height” of W3 is measured.
Entry is placed at a configurable Fibonacci pullback (default 50%) inside that leg.
ATR-based stop is placed below entry.
Take-profit is projected to satisfy min Reward:Risk.
Bearish structure:
Mirrored logic (lower highs/lows, price below EMA, W3 down, W4 retrace up, W5 continuation down).
Once a valid setup is found, the script draws a colored box around the entry zone and a label describing the type of signal (“LONG SETUP” or “SHORT SETUP”) with the suggested limit price.
6. Orders & Execution
Entry Orders: The strategy uses limit orders at the computed W4 level (“Sniper Long” or “Sniper Short”).
Exits: A single strategy.exit() is attached to each entry with:
Take-profit at the projected minimum R:R target.
Stop-loss at ATR-based level.
One Trade at a Time: New setups are only used when there is no open position (strategy.opentrades == 0) to keep the logic clear and risk contained.
7. Visual Guide on the Chart
Wave Labels:
Primary: ①,②,③,④,⑤, ⒶⒷⒸ
Intermediate: (1)…(5), (A)(B)(C)
Minor: i…v, a b c
Trend EMA: Single blue EMA showing the dominant trend.
Setup Boxes:
Green transparent box → long entry zone.
Red transparent box → short entry zone.
Labels: “LONG SETUP / SHORT SETUP” labels mark the proposed limit entry with price.
8. How to Use This Strategy
Attach the strategy to your chart
Choose your market (stocks, indices, FX, crypto, futures, etc.) and timeframe (for example 1h, 4h, or Daily). Then add the strategy to the chart from your Scripts list.
Start with the default settings
Leave all inputs on their defaults first. This lets you see the “intended” behaviour and the exact properties used for the published backtest (account size, 1% risk, commission, etc.).
Study the wave map
Zoom in and out and look at the three wave degrees:
Blue circles → Primary degree (big picture trend).
Teal (1)…(5) → Intermediate degree (swing structure).
Red i…v → Minor degree (micro waves).
Use this to understand how the engine is interpreting the Elliott structure on your symbol.
Watch for valid setups
Look for the coloured boxes and labels:
Green box + “LONG SETUP” label → potential W4 pullback long in an uptrend.
Red box + “SHORT SETUP” label → potential W4 pullback short in a downtrend.
Only trades in the direction of the EMA trend filter are allowed by the strategy.
Check the Reward:Risk of each idea
For each setup, inspect:
Limit entry price.
ATR-based stop level.
Projected take-profit level.
Make sure the minimum Reward:Risk ratio matches your own rules before you consider trading it.
Backtest and evaluate
Open the Strategy Tester:
Verify you have a decent sample size (ideally 100+ trades).
Check drawdowns, average trade, win-rate and R:R distribution.
Change markets and timeframes to see where the logic behaves best.
Adapt to your own risk profile
If you plan to use it live:
Set Initial Capital to your real account size.
Adjust default_qty_value to a risk level you are comfortable with (often 0.5–2% per trade).
Set commission and slippage to realistic broker values.
Re-run the backtest after every major change.
Use as a framework, not a signal machine
Treat this as a structured Elliott/R:R framework:
Filter signals by higher-timeframe trend, major S/R, volume, or fundamentals.
Optionally hide some wave degrees or ABC labels if you want a cleaner chart.
Combine the system’s structure with your own trade management and discretion.
Best Practices & Limitations
This is an approximate Elliott Wave engine based on fractal pivots. It does not replace a full discretionary Elliott analysis.
All wave counts are algorithmic and can differ from a manual analyst’s interpretation.
Like any backtest, results depend heavily on:
Symbol and timeframe.
Sample size (more trades are better).
Realistic commission/slippage settings.
The 0-slippage default is chosen only to show the “raw logic”. In real markets, slippage can significantly impact performance.
No strategy wins all the time. Losing streaks and drawdowns will still occur even with a strict R:R framework.
Disclaimer
This script is for educational and research purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Past performance, whether real or simulated, is not indicative of future results. Always test on multiple symbols/timeframes, use conservative risk, and consult your financial advisor before trading live capital.
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.






















