EMA 12/21 Crossover with ATR-based SL/TP📈 Ultimate Scalper v2
Strategy Type: Trend-Pullback Scalping
Indicators Used: EMA (12/21), MACD Histogram, ADX, ATR
Platform: TradingView (Pine Script v5)
Author:
🎯 Strategy Overview
The Ultimate Scalper v2 is a scalping strategy that catches pullbacks within short-term trends using a dynamic combination of 12/21 EMA bands, MACD Histogram crossovers, and ADX for trend confirmation. It uses ATR-based stop-loss and take-profit levels, making it suitable for volatility-sensitive environments.
🧠 Logic Breakdown
🔍 Trend Detection
Uses the 12 EMA and 21 EMA to identify the short-term trend:
Uptrend: EMA 12 > EMA 21 and ADX > threshold
Downtrend: EMA 12 < EMA 21 and ADX > threshold
The ADX (default: 25) filters out low-momentum environments.
📉 Pullback Identification
Once a trend is detected:
A pullback is flagged when the MACD Histogram moves against the trend (below 0 in uptrend, above 0 in downtrend).
An entry signal is triggered when the histogram crosses back through zero (indicating momentum is resuming in the trend direction).
🟢 Entry Conditions
Long Entry:
EMA 12 > EMA 21
ADX > threshold
MACD Histogram was below 0 and crosses above 0
Short Entry:
EMA 12 < EMA 21
ADX > threshold
MACD Histogram was above 0 and crosses below 0
❌ Exit Logic (ATR-based)
The strategy calculates stop-loss and take-profit levels using ATR at the time of entry:
Stop-Loss: Entry Price −/+ ATR × Multiplier
Take-Profit: Entry Price ± ATR × 2 × Multiplier
Default ATR Multiplier: 1.0
⚙️ Customizable Inputs
ADX Threshold: Minimum trend strength for trades (default: 25)
ATR Multiplier: Controls SL/TP distance (default: 1.0)
📊 Visuals
EMA 12 and EMA 21 band can be added manually for visual reference.
Entry and exit signals are plotted via TradingView’s built-in backtesting engine.
⚠️ Disclaimer
This is a backtesting strategy, not financial advice. Performance varies across markets and timeframes. Always combine with additional confluence or risk management when going live.
震盪指標
System 0530 - Stoch RSI Strategy v13 SL-Priority TP-ReversalStrategy Overview: System 0530 - Stochastic RSI Multi-Timeframe
This TradingView Pine Script outlines a strategy primarily based on the Stochastic RSI (Stoch RSI) indicator, employing a multi-timeframe approach for signal generation and confirmation. It is designed to operate on a 5-minute chart, referencing 15-minute data for higher-level context.
Core Mechanics:
Primary Indicator: Stochastic RSI, used to identify overbought/oversold conditions and potential momentum shifts.
Timeframes:
5-minute chart: For initial signal triggers and primary execution.
15-minute chart: For signal confirmation and certain take-profit conditions.
Entry Logic:
Bullish Market Bias Adjustment: Reflecting an overall bullish market trend, this strategy is intended to be applied with more tolerance or lower requirements for triggering long positions compared to short positions. This can be achieved by adjusting the input parameters accordingly (e.g., setting a higher stoch_5min_k_long_trigger threshold, allowing longs to trigger when less oversold, or a higher stoch_15min_long_entry_level, requiring less deep confirmation for longs).
5-Minute Initial Trigger:
Long: 5-minute Stoch RSI K-line crosses above its D-line, AND the K-value at the time of the cross is below a specified stoch_5min_k_long_trigger level.
Short: 5-minute Stoch RSI K-line crosses below its D-line, AND the K-value at the time of the cross is above a specified stoch_5min_k_short_trigger level.
15-Minute Confirmation:
After a 5-minute trigger, the strategy waits for a configurable number of 5-minute bars (wait_window_5min_bars) for confirmation from the 15-minute timeframe.
Long Confirmation: 15-minute Stoch RSI K-line must be strictly greater than its D-line, AND the 15-minute K-value must be below stoch_15min_long_entry_level.
Short Confirmation: 15-minute Stoch RSI K-line must be strictly less than its D-line, AND the 15-minute K-value must be above stoch_15min_short_entry_level.
Position Lock: No new entry signals are generated if the strategy already holds an open position.
Duplicate Signal Filter: A cooldown period, defined by min_bars_between_signals, must pass before another signal in the same direction can be considered.
Exit Logic:
Stop-Loss (SL):
The SL is set based on the low (for longs) or high (for shorts) of the 5-minute bar on which the trade was entered.
The position is closed if a subsequent 5-minute bar's closing price moves beyond this SL level.
SL checks are prioritized over Take-Profit checks.
Take-Profit (TP) - Two-Stage Mechanism:
TP1 (Closes 50% of the position):
Priority A (Extreme K Levels): If the 5-minute Stoch K OR 15-minute Stoch K value exceeds extreme_long_tp_level (for longs) or drops below extreme_short_tp_level (for shorts).
Priority B (Conditional 5-min Cross + 15-min K-Reversal): If Extreme K conditions are not met, TP1 is triggered if:
A 5-minute Stoch RSI K/D crossover occurs (K crosses below D for longs; K crosses above D for shorts - using strict ta.crossunder/ta.crossover).
AND this 5-minute crossover is confirmed by a 15-minute Stoch K-value "reversal" (current 15m K < previous 15m K for longs; current 15m K > previous 15m K for shorts).
TP2 (Closes remaining 50% of the position):
This stage is active only after TP1 has been taken.
If the 5-minute Stoch K OR 15-minute Stoch K value reaches the same extreme_long_tp_level or extreme_short_tp_level again, a waiting period begins, defined by tp2_extreme_k_wait_bars (number of 5-minute bars).
If the extreme K condition persists after this waiting period, TP2 is executed.
If the extreme K condition disappears during the waiting period, the TP2 attempt for that instance is cancelled.
If tp2_extreme_k_wait_bars is set to 0, TP2 will trigger immediately upon the extreme K condition being met after TP1.
Note on Fine-Tuning (as per user context):
This strategy has been specifically fine-tuned for SPY. As with any trading system, its performance can vary across different instruments and market conditions. The user notes that to potentially maximize profits, especially in trending scenarios where the current "Extreme K" based TP2 might exit prematurely, it is advisable to explore and integrate other indicators or alternative take-profit methodologies. Dynamic approaches like ATR (Average True Range) trailing stops or trend-following exit signals could be considered for managing the second portion of the position.
Momentum StrategyMomentum Strategy using Volume, RSI and MACD
Optimised using AI to determine:
"Volume MA Lookback" and Volume Spike Threshold"
"RSI Length" vs. "RSI Midline Level"
"MACD Fast Length" , "MACD Slow Length" and"MACD Signal Length"
to generate a "Slow MA Length"
P4H SFP StrategySignals Long or Short Entries based on Previous 4H low/high. Entry criteria are SFP/Rejection of P4h L/H and candle close in opposite direction. RSI must be 65/35 but can customize. Stop/TP 1% from entry. All of this is customizable. Stats are shown and you can change the time range of that as well.
Trend Signals StrategyThis strategy is designed to follow the dominant market trend and only take trades in the direction of that trend. It uses two moving averages for trend detection and candlestick confirmation for entries. The strategy can be used on any timeframe but works best on 15m to 1H for intraday trading.
RSI Trend RiderRSI Trend Rider is a long only, momentum-based trend-following strategy designed for rules based trading. It combines a setup of EMAs (20, 50, 200), RSI(4), ADX filtering, and a daily 120 EMA to capture high-probability long trades in trending markets.
Works best on intraday timeframes (2h, 4h)
Key Features:
Multi-timeframe trend confirmation (EMA alignment + daily EMA)
RSI(4) pullback entries in strong trends
ADX filter to avoid low-momentum conditions
Configurable fixed and EMA-based stop loss/target options
Built-in performance dashboard with key metrics like PnL, drawdown, win rate, and buy & hold comparison (can be turned off on mobile or small screens).
Customizable backtest period and risk settings
Ideal for traders looking for a simple, data-driven system that rides trends and compounds small, consistent wins.
System 0530 - Stoch RSI Strategy with ATR filterStrategy Description: System 0530 - Multi-Timeframe Stochastic RSI with ATR Filter
Overview:
This strategy, "System 0530," is designed to identify trading opportunities by leveraging the Stochastic RSI indicator across two different timeframes: a shorter timeframe for initial signal triggers (assumed to be the chart's current timeframe, e.g., 5-minute) and a longer timeframe (15-minute) for signal confirmation. It incorporates an ATR (Average True Range) filter to help ensure trades are taken during periods of adequate market volatility and includes a cooldown mechanism to prevent rapid, successive signals in the same direction. Trade exits are primarily handled by reversing signals.
How It Works:
1. Signal Initiation (e.g., 5-Minute Timeframe):
Long Signal Wait: A potential long entry is considered when the 5-minute Stochastic RSI %K line crosses above its %D line, AND the %K value at the time of the cross is at or below a user-defined oversold level (default: 30).
Short Signal Wait: A potential short entry is considered when the 5-minute Stochastic RSI %K line crosses below its %D line, AND the %K value at the time of the cross is at or above a user-defined overbought level (default: 70). When these conditions are met, the strategy enters a "waiting state" for confirmation from the 15-minute timeframe.
2. Signal Confirmation (15-Minute Timeframe):
Once in a waiting state, the strategy looks for confirmation on the 15-minute Stochastic RSI within a user-defined number of 5-minute bars (wait_window_5min_bars, default: 5 bars).
Long Confirmation:
The 15-minute Stochastic RSI %K must be greater than or equal to its %D line.
The 15-minute Stochastic RSI %K value must be below a user-defined threshold (stoch_15min_long_entry_level, default: 40).
Short Confirmation:
The 15-minute Stochastic RSI %K must be less than or equal to its %D line.
The 15-minute Stochastic RSI %K value must be above a user-defined threshold (stoch_15min_short_entry_level, default: 60).
3. Filters:
ATR Volatility Filter: If enabled, trades are only confirmed if the current ATR value (converted to ticks) is above a user-defined minimum threshold (min_atr_value_ticks). This helps to avoid taking signals during periods of very low market volatility. If the ATR condition is not met, the strategy continues to wait for the condition to be met within the confirmation window, provided other conditions still hold.
Signal Cooldown Filter: If enabled, after a signal is generated, the strategy will wait for a minimum number of bars (min_bars_between_signals) before allowing another signal in the same direction. This aims to reduce overtrading.
4. Entry and Exit Logic:
Entry: A strategy.entry() order is placed when all trigger, confirmation, and filter conditions are met.
Exit: This strategy primarily uses reversing signals for exits. For example, if a long position is open, a confirmed short signal will close the long position and open a new short position. There are no explicit take profit or stop loss orders programmed into this version of the script.
Key User-Adjustable Parameters:
Stochastic RSI Parameters: RSI Length, Stochastic RSI Length, %K Smoothing, %D Smoothing.
Signal Trigger & Confirmation:
5-minute %K trigger levels for long and short.
15-minute %K confirmation thresholds for long and short.
Wait window (in 5-minute bars) for 15-minute confirmation.
Filters:
Enable/disable and configure the Signal Cooldown filter (minimum bars between signals).
Enable/disable and configure the ATR Volatility filter (ATR period, minimum ATR value in ticks).
Strategy Parameters:
Leverage Multiplier (Note: This primarily affects theoretical position sizing for backtesting calculations in TradingView and does not simulate actual leveraged trading risks).
Recommendations for Users:
Thorough Backtesting: Test this strategy extensively on historical data for the instruments and timeframes you intend to trade.
Parameter Optimization: Experiment with different parameter settings to find what works best for your trading style and chosen markets. The default values are starting points and may not be optimal for all conditions.
Understand the Logic: Ensure you understand how each component (Stochastic RSI on different timeframes, ATR filter, cooldown) interacts to generate signals.
Risk Management: Since this version does not include explicit stop-loss orders, ensure you have a clear risk management plan in place if trading this strategy live. You might consider manually adding stop-loss orders through your broker or using TradingView's separate strategy order settings for stop-loss if applicable.
Disclaimer:
This strategy description is for informational purposes only and does not constitute financial advice. Past performance is not indicative of future results. Trading involves significant risk of loss. Always do your own research and understand the risks before trading.
TrendMaster Pro 2.3 with Alerts
Hello friends,
A member of the community approached me and asked me how to write an indicator that would achieve a particular set of goals involving comprehensive trend analysis, risk management, and session-based trading controls. Here is one example method of how to create such a system:
Core Strategy Components
Multi-Moving Average System - Uses configurable MA types (EMA, SMA, SMMA) with short-term (9) and long-term (21) periods for primary signal generation through crossovers
Higher Timeframe Trend Filter - Optional trend confirmation using a separate MA (default 50-period) to ensure trades align with broader market direction
Band Power Indicator - Dynamic high/low bands calculated using different MA types to identify price channels and volatility zones
Advanced Signal Filtering
Bollinger Bands Volatility Filter - Prevents trading during low-volatility ranging markets by requiring sufficient band width
RSI Momentum Filter - Uses customizable thresholds (55 for longs, 45 for shorts) to confirm momentum direction
MACD Trend Confirmation - Ensures MACD line position relative to signal line aligns with trade direction
Stochastic Oscillator - Adds momentum confirmation with overbought/oversold levels
ADX Strength Filter - Only allows trades when trend strength exceeds 25 threshold
Session-Based Trading Management
Four Trading Sessions - Asia (18:00-00:00), London (00:00-08:00), NY AM (08:00-13:00), NY PM (13:00-18:00)
Individual Session Limits - Separate maximum trade counts for each session (default 5 per session)
Automatic Session Closure - All positions close at specified market close time
Risk Management Features
Multiple Stop Loss Options - Percentage-based, MA cross, or band-based SL methods
Risk/Reward Ratio - Configurable TP levels based on SL distance (default 1:2)
Auto-Risk Calculation - Dynamic position sizing based on dollar risk limits ($150-$250 range)
Daily Limits - Stop trading after reaching specified TP or SL counts per day
Support & Resistance System
Multiple Pivot Types - Traditional, Fibonacci, Woodie, Classic, DM, and Camarilla calculations
Flexible Timeframes - Auto-adjusting or manual timeframe selection for S/R levels
Historical Levels - Configurable number of past S/R levels to display
Visual Customization - Individual color and display settings for each S/R level
Additional Features
Alert System - Customizable buy/sell alert messages with once-per-bar frequency
Visual Trade Management - Color-coded entry, SL, and TP levels with fill areas
Session Highlighting - Optional background colors for different trading sessions
Comprehensive Filtering - All signals must pass through multiple confirmation layers before execution
This approach demonstrates how to build a professional-grade trading system that combines multiple technical analysis methods with robust risk management and session-based controls, suitable for algorithmic trading across different market sessions.
Good luck and stay safe!
Strategy Builder With IndicatorsThis strategy script is designed for traders who enjoy building systems using multiple indicators.
Please note: This script does not include any built-in indicators. Instead, it works by referencing the plot outputs of the indicators you’ve already added to your chart.
For example, if you add a MACD and an ATR indicator to your chart, you can assign their plot values as inputs in the settings panel of this strategy.
• MACD as a trigger
• ATR as a filter
How Filters Work
Filters check whether certain conditions are met before a trade can be opened. For instance, if you set a filter like ATR > 30, then no trade will be executed unless that condition is true — even if the trigger fires.
All filters are linked, meaning every active filter must be satisfied for a trade to occur.
How Triggers Work
Triggers are what actually fire a trade signal — such as a moving average crossover or RSI breaking above a specific level. Unlike filters, triggers are independent. Only one active trigger needs to be true for the trade to execute.
Thanks to its modular structure, this strategy can be used with any indicator of your choice.
⸻
Risk Management Features
In the settings, you’ll find flexible options for:
• Stop Loss (SL)
• Trailing Stop Loss (TSL)
• Multi Take-Profit (TP)
These features enhance trade safety and let you tailor your risk management.
SL types available:
• Tick-based SL
• Percent-based SL
• ATR-based SL
Once you select your preferred SL type, you can fine-tune its distance using the offset field.
Trailing SL allows your stop to follow price as it moves in your favor — helping to lock in profits.
Multi-TP lets you take profits at two different levels, helping you secure gains while leaving room for extended moves.
Breakeven option is also available to automatically move your SL to entry after reaching a profit threshold.
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How to Build a Solid Strategy
Let’s break down a good setup into three key components:
1. Trend Filter
Avoid trading against the trend — that’s like swimming against the current.
Use a filter like:
• Supertrend
• Momentum indicators
• Candlestick bias, etc.
Example: In this case, I used Supertrend and filtered for trades only if the price is above the uptrend line.
2. Trigger Condition
Once we confirm the trend is on our side, we need a trigger to execute at the right moment. This can be:
• RSI cross
• Candlestick patterns
• Trendline breaks
• Moving average crossovers, etc.
Example: I used RSI crossing above 50 as the entry trigger.
3. Risk Management
Even in the right trend at the right time — anything can happen. That’s why you should always define Stop Loss and Take Profit levels.
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And there you have it! Your strategy is ready to backtest, refine, and deploy with alerts for live trading.
Questions or suggestions? Feel free to reach out
QQQ Strategy v2 ESL | easy-peasy-x This is a strategy optimized for QQQ (and SPY) for the 1H timeframe. It significantly outperforms passive buy-and-hold approach. With settings adjustments, it can be used on various assets like stocks and cryptos and various timeframes, although the default out of the box settings favor QQQ 1H.
The strategy uses various triggers to take both long and short trades. These can be adjusted in settings. If you try a different asset, see what combination of triggers works best for you.
Some of the triggers employ LuxAlgo's Ultimate RSI - shoutout to him for great script, check it out here .
Other triggers are based on custom signed standard deviation - basically the idea is to trade Bollinger Bands expansions (long to the upside, short to the downside) and fade or stay out of contractions.
There are three key moving averages in the strategy - LONG MA, SHORT MA, BASIC MA. Long and Short MAs are guides to eyes on the chart and also act as possible trend filters (adjustable in settings). Basic MA acts as guide to eye and a possible trade trigger (adjustable in settings).
There are a few trend filters the strategy can use - moving average, signed standard deviation, ultimate RSI or none. The filters act as an additional condition on triggers, making the strategy take trades only if both triggers and trend filter allows. That way one can filter out trades with unfavorable risk/reward (for instance, don't long if price is under the MA200). Different trade filters can be used for long and short trades.
The strategy employs various stop loss types, the default of which is a trailing %-based stop loss type. ATR-based stop loss is also available. The default 1.5% trailing stop loss is suitable for leveraged trading.
Lastly, the strategy can trigger take profit orders if certain conditions are met, adjustable in settings. Also, it can hold onto winning trades and exit only after stop out (in which case, consecutive triggers to take other positions will be ignored until stop out).
Let me know if you like it and if you use it, what kind of tweaks would you like to see.
With kind regards,
easy-peasy-x
MACD + RSI + EMA + BB + ATR Day Trading StrategyEntry Conditions and Signals
The strategy implements a multi-layered filtering approach to entry conditions, requiring alignment across technical indicators, timeframes, and market conditions .
Long Entry Requirements
Trend Filter: Fast EMA (9) must be above Slow EMA (21), price must be above Fast EMA, and higher timeframe must confirm uptrend
MACD Signal: MACD line crosses above signal line, indicating increasing bullish momentum
RSI Condition: RSI below 70 (not overbought) but above 40 (showing momentum)
Volume & Volatility: Current volume exceeds 1.2x 20-period average and ATR shows sufficient market movement
Time Filter: Trading occurs during optimal hours (9:30-11:30 AM ET) when market volatility is typically highest
Exit Strategies
The strategy employs multiple exit mechanisms to adapt to changing market conditions and protect profits :
Stop Loss Management
Initial Stop: Placed at 2.0x ATR from entry price, adapting to current market volatility
Trailing Stop: 1.5x ATR trailing stop that moves up (for longs) or down (for shorts) as price moves favorably
Time-Based Exits: All positions closed by end of trading day (4:00 PM ET) to avoid overnight risk
Best Practices for Implementation
Settings
Chart Setup: 5-minute timeframe for execution with 15-minute chart for trend confirmation
Session Times: Focus on 9:30-11:30 AM ET trading for highest volatility and opportunity
RSI SwingRadar🧠 Strategy Overview
This long-only strategy combines RSI/MA crossovers with ATR-based risk management, designed for cleaner entries during potential bounce phases — especially tuned for assets like XMR/USDT.
🔍 Core Logic:
- RSI Crossover: Entry occurs when the 14-period RSI crosses above its 14-period SMA, signaling a potential shift in momentum.
- Oversold Filter: The RSI must have been below a user-defined oversold threshold (default: 35) on the previous candle, filtering for bounce setups after a pullback.
- ATR-Based Stop/Target: Stop-loss is placed below the low by a user-adjustable ATR multiplier (default: 0.5×). Take-profit is calculated with a Risk:Reward multiplier (default: 4×).
These elements work in tandem — RSI crossovers give momentum confirmation, oversold filtering adds context, and ATR-based exits adapt to volatility, creating a compact yet responsive strategy.
📉 Visuals:
- Dynamic Bands: The chart displays the active stop-loss, entry price, and take-profit as colored bands for easy visual tracking.
- Clean Overlay: Designed with simplicity — only confirmed setups are shown, keeping noise low.
✅ Suggested Use:
- Works best on XMR/USDT or similarly trending assets.
- Best suited for pullback entries during broader uptrends.
- Adjustable for different volatility conditions and asset behaviors.
⚠️ Disclaimer
- This strategy is for educational and research purposes only.
- It does not guarantee profitability in any market.
- Always backtest, forward-test, and understand your own risk tolerance before using any
strategy in a live environment.
- Past performance is not indicative of future results.
- This script is not financial advice.
Futures Trading Hours RSI StrategyFutures Trading Hours RSI Strategy
A lightweight, session-filtered RSI strategy designed for equity-index futures (e.g. NQ, ES, YM) on a 30-minute chart. It dynamically enters long when RSI crosses above your oversold threshold and short when RSI crosses below your overbought threshold—but only during regular U.S. trading hours (08:30–15:00 CT, Monday–Friday). All positions are set to close at 15:00 CT to avoid overnight risk, and optional background shading highlights your open longs (green) and shorts (red).
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Key Features
• RSI-based entries: configurable length, oversold, and overbought levels
• Session filter: trades only between 08:30–15:00 CT, Monday through Friday
• Automatic exit: closes all positions at or after 15:00 CT each day
• Visual cues: optional background shading for open long/short positions
• Easy customization: adjust length, overSold, overBought, and time offsets
Backtest Performance (NQ Jun 2025, 30 min)
• Total P&L: +$10,230 (+1.02%)
• Profit Factor: 4.61
• Win Rate: 57.1% (4 wins / 7 trades)
• Max Drawdown: $2,215 (0.22%)
(Results shown are for illustrative purposes only; past performance does not guarantee future returns.)
How to Use
1. Add this script to your 30-minute futures chart.
2. Tweak the RSI parameters and time-zone offset to suit your instrument.
3. Enable “background shading” if you’d like a visual reminder of open positions.
4. Run in paper-trade mode to validate performance before going live.
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⚠️ Disclaimer: Trading carries risk. Always backtest and paper-trade before using real capital. Adjust position sizing and risk controls to your own tolerance.
Chaikin Momentum Scalper🎯 Overview
The Chaikin Momentum Scalper is a powerful trading strategy designed to identify momentum shifts in the market and ride the trend for maximum profits. This strategy is ideal for trading the USD/JPY currency pair on a 15-minute chart, making it perfect for high-frequency trading (HFT). Whether you’re starting with a small account of $1,000 or managing a larger portfolio, this strategy can scale to suit your needs.
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🔑 How the Strategy Works
Here’s how the Chaikin Momentum Scalper identifies trade opportunities:
1️⃣ Momentum Detection
The core of this strategy is the Chaikin Oscillator, a tool that measures the flow of money into or out of a market. It helps us understand whether buyers (bulls) or sellers (bears) are in control.
• When the indicator crosses above zero, it signals that buying momentum is picking up – a buying opportunity.
• When the indicator crosses below zero, it signals that selling momentum is increasing – a selling opportunity.
2️⃣ Trend Confirmation
We don’t just jump into trades based on momentum alone. We also use a 200-period simple moving average (SMA) to confirm the overall trend.
• If the price is above the SMA, it confirms an uptrend, so we look for buy trades.
• If the price is below the SMA, it confirms a downtrend, so we look for sell trades.
This way, we align our trades with the broader market direction for higher success rates.
3️⃣ Volatility & Risk Management
We use a tool called the Average True Range (ATR) to measure market volatility. This helps us:
• Set a stop-loss (where we’ll exit the trade if the market moves against us) at a safe distance from our entry point.
• Set a take-profit (where we’ll lock in profits) at a target that’s larger than the stop-loss, ensuring a good reward-to-risk ratio.
This approach adapts to the market’s behavior, tightening stops in calmer conditions and widening them when volatility increases.
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📈 Why This Strategy Works
✅ It combines momentum and trend-following principles, increasing the chances of trading in the right direction.
✅ It dynamically adjusts risk levels based on market volatility, keeping losses small and profits big.
✅ It’s scalable – perfect for both small accounts (like $1,000) and larger, corporate-sized portfolios.
✅ It has been deep-backtested on USD/JPY 15-minute charts, proving its consistency across different market conditions.
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📝 Important Notes
📌 This strategy is best used for USD/JPY on a 15-minute chart, making it great for high-frequency trading while you continue to build and refine your trading system.
📌 It’s designed to work on both small ($1,000+) and large accounts, so it can grow with you as your capital increases.
📌 While it has passed deep backtesting on this pair and timeframe, remember that no strategy is perfect. It’s crucial to test it yourself, start with a demo account, and apply proper risk management before trading real money.
🌟 Final Thoughts
The Chaikin Momentum Scalper is a solid, adaptable trading approach combining momentum, trend direction, and volatility awareness. If you’re looking for a strategy to kick-start your trading journey—or to add to your existing system—it offers a strong foundation.
Momentum Long + Short Strategy (BTC 3H)Momentum Long + Short Strategy (BTC 3H)
🔍 How It Works, Step by Step
Detect the Trend (📈/📉)
Calculate two moving averages (100-period and 500-period), either EMA or SMA.
For longs, we require MA100 > MA500 (uptrend).
For shorts, we block entries if MA100 exceeds MA500 by more than a set percentage (to avoid fading a powerful uptrend).
Apply Momentum Filters (⚡️)
RSI Filter: Measures recent strength—only allow longs when RSI crosses above its smoothed average, and shorts when RSI dips below the oversold threshold.
ADX Filter: Gauges trend strength—ensures we only enter when a meaningful trend exists (optional).
ATR Filter: Confirms volatility—avoids choppy, low-volatility conditions by requiring ATR to exceed its smoothed value (optional).
Confirm Entry Conditions (✅)
Long Entry:
Price is above both MAs
Trend alignment & optional filters pass ✅
Short Entry:
Price is below both MAs and below the lower Bollinger Band
RSI is sufficiently oversold
Trend-blocker & ATR filter pass ✅
Position Sizing & Risk (💰)
Each trade uses 100 % of account equity by default.
One pyramid addition allowed, so you can scale in if the move continues.
Commission and slippage assumptions built in for realistic backtests.
Stops & Exits (🛑)
Long Stop-Loss: e.g. 3 % below entry.
Long Auto-Exit: If price falls back under the 500-period MA.
Short Stop-Loss: e.g. 3 % above entry.
Short Take-Profit: e.g. 4 % below entry.
🎨 Why It’s Powerful & Customizable
Modular Filters: Turn on/off RSI, ADX, ATR filters to suit different market regimes.
Adjustable Thresholds: Fine-tune stop-loss %, take-profit %, RSI lengths, MA gaps and more.
Multi-Timeframe Potential: Although coded for 3 h BTC, you can adapt it to stocks, forex or other cryptos—just recalibrate!
Backtest Fine-Tuned: Default settings were optimized via backtesting on historical BTC data—but they’re not guarantees of future performance.
⚠️ Warning & Disclaimer
This strategy is for educational purposes only and designed for a toy fund. Crypto markets are highly volatile—you can lose 100 % of your capital. It is not a predictive “holy grail” but a rules-based framework using past data. The parameters have been fine-tuned on historical data and are not valid for future trades without fresh calibration. Always practice with paper-trading first, use proper risk management, and do your own research before risking real money. 🚨🔒
Good luck exploring and experimenting! 🚀📊
Big Mover Catcher BTC 4h🧠 Big Mover Catcher (BTC 4H Strategy) — Educational Tool
⚠️ Disclaimer: I am not a financial advisor. This script is for educational and testing purposes only. Cryptocurrency trading is highly volatile and involves significant risk. You can lose all of your invested capital.
📌 Overview
The Big Mover Catcher strategy is a work-in-progress trading system designed for Bitcoin (BTC) on the 4-hour chart. It aims to identify strong breakout moves by combining multiple technical indicators and conditions, allowing for high customization and filter-based confirmations.
This script is part of a personal project to learn Pine Script and backtesting on TradingView. It is currently in the testing and research phase.
🎯 Strategy Objective
Catch large, high-momentum breakout moves in the BTC market using:
Bollinger Band breakouts for entry signals
Momentum, volatility, and trend filters for trade confirmation
🧰 Features & Filters
The script provides a flexible set of filters that can be turned ON/OFF and adjusted directly from the settings panel:
✅ Entry Conditions
Price must break above or below Bollinger Bands
All selected filters must align before entry
🧪 Available Filters:
Relative Strength Index (RSI) with EMA/SMA smoothing
Average Directional Index (ADX) with EMA/SMA smoothing
Average True Range (ATR) with EMA/SMA smoothing
MACD Signal above or below zero
EMA 350 trend filter
ATR / ADX / RSI Threshold toggles for added control
🔥 Additional Feature:
Force Take Profit: Optionally closes the trade immediately if a candle closes with more than a defined % movement (default: 5%). This can help lock in quick profits during high volatility moves.
⚙️ Customizable Inputs
You can configure:
Stop loss percentage
All indicator lengths
Smoothing types (EMA/SMA)
Threshold activation toggles
Individual filter ON/OFF switches
This makes the strategy highly adaptable for educational exploration and optimization.
📊 Best Used For
Learning Pine Script and strategy structure
Testing filter combinations for BTC on the 4H timeframe
Understanding how different indicators interact in live markets
⚠️ Note: ❌ Short trades are currently disabled by default, as short-side logic is still under development.
❗ Final Reminder
This script is not financial advice. It is an educational tool. Use it to learn and explore trading logic. Trading cryptocurrencies carries high risk — only invest what you can afford to lose.
Ichimoku Cloud Breakout Only LongThis is a very simple trading strategy based exclusively on the Ichimoku Cloud. There are no additional indicators or complex rules involved. The key condition is that we only open long positions when the price is clearly above the cloud — indicating a bullish trend.
For optimal results, the recommended timeframes are 1D (daily) or 1W (weekly) charts. These higher timeframes help filter out market noise and provide more reliable trend signals.
We do not short the market under any circumstances. The focus is purely on riding upward momentum when the price breaks out or stays above the cloud.
This strategy works best when applied to growth stocks with strong upward trends and good fundamentals — such as Google (GOOGL), Tesla (TSLA), Apple (AAPL), or NVIDIA (NVDA).
Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power
Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time.
What Makes This Unique
GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto.
True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation.
Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals.
Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity.
Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading.
No hidden DCA or pyramiding—what you see is what you trade.
Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable.
📊 Inputs and What They Mean (Read Carefully)
Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this.
RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals.
⚡ Regime & Momentum Gates
Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop.
🕒 Volatility & Session
ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time.
Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills.
📊 Sizing & Risk
Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk. ATR will effect losses in high volatility times.
🔄 Exits & Scaling
Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode.
Visuals That Actually Matter
Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”).
Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge.
*No cosmetics, no hidden code distractions.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Why It Wins
While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive:
- Context-aware signals, not just patterns
- Tight, transparent risk
- Inputs that adapt, not confuse
- Visuals that clarify, not distract
- Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box)
Disclaimer (for TradingView compliance):
Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades.
This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private.
Use with discipline, use with clarity, and always trade smarter.
— Dskyz , powered by DAFE Trading Systems.
RCI Strategy [PineIndicators]RCI Strategy
This strategy leverages the Rank Correlation Index (RCI) — a statistical oscillator that measures the relationship between time and price rank — combined with a configurable moving average filter. It offers clean, rule-based entries and exits, and visually enhanced trade tracking via labeled markers and boxes on the chart.
The RCI Strategy is well-suited for momentum traders looking to capture directional shifts with confirmation through RCI smoothing.
Core Logic
1. Rank Correlation Index (RCI)
Measures how closely price changes correlate with time rankings.
Values range between -100 and +100.
Thresholds at ±80 help identify potential reversals or extremes.
2. RCI Smoothing via Moving Average
A moving average (MA) is applied to the RCI to smooth out fluctuations.
Supported MA types:
SMA
EMA
SMMA (RMA)
WMA
VWMA
Users can disable the smoothing by selecting "None".
Trade Entry Logic
Long Entry: RCI crosses above the selected moving average.
Short Entry: RCI crosses below the moving average.
Entries are restricted by trade direction settings:
Long Only
Short Only
Long & Short
Visual Features
RCI Panel Display
Plots RCI line and its moving average in a separate pane.
Horizontal guide lines at 0, +80, and -80 help visualize signal zones.
Trade Labels on Chart
Buy Label: Plotted when a long entry is executed.
Close Label: Plotted when any position is closed.
Triangle markers for visual emphasis on direction change.
Trade Visualization Boxes
A colored box is drawn between entry and exit prices.
Green = profitable trade; Red = losing trade.
Two horizontal lines connect entry and exit prices for reference.
Customization Parameters
RCI Source: Select input price for the RCI (default: close).
RCI Length: Set sensitivity of the oscillator.
MA Type and Length: Choose and configure the smoothing filter.
Trade Direction Mode: Define whether to allow Long, Short, or both.
Use Cases
Swing traders who want to trade directional reversals with statistical backing.
Traders seeking a clean and visual strategy based on rank momentum.
Environments where both trend and range dynamics occur.
Conclusion
The RCI Strategy is a non-repainting, rule-based trading model that combines rank correlation momentum with smoothed trend logic. Its clean visual markers, labeled trades, and flexible MA filters make it a valuable tool for discretionary and systematic traders alike.
Parabolic RSI Strategy [ChartPrime × PineIndicators]This strategy combines the strengths of the Relative Strength Index (RSI) with a Parabolic SAR logic applied directly to RSI values.
Full credit to ChartPrime for the original concept and indicator, licensed under the MPL 2.0.
It provides clear momentum-based trade signals using an innovative method that tracks RSI trend reversals via a customized Parabolic SAR, enhancing traditional oscillator strategies with dynamic trend confirmation.
How It Works
The system overlays a Parabolic SAR on the RSI, detecting trend shifts in RSI itself rather than on price, offering early reversal insight with visual and algorithmic clarity.
Core Components
1. RSI-Based Trend Detection
Calculates RSI using a customizable length (default: 14).
Uses upper and lower thresholds (default: 70/30) for overbought/oversold zones.
2. Parabolic SAR Applied to RSI
A custom Parabolic SAR function tracks momentum within the RSI, not price.
This allows the system to capture RSI trend reversals more responsively.
Configurable SAR parameters: Start, Increment, and Maximum acceleration.
3. Signal Generation
Long Entry: Triggered when the SAR flips below the RSI line.
Short Entry: Triggered when the SAR flips above the RSI line.
Optional RSI filter ensures that:
Long entries only occur above a minimum RSI (e.g. 50).
Short entries only occur below a maximum RSI.
Built-in logic prevents new positions from being opened against trend without prior exit.
Trade Modes & Controls
Choose from:
Long Only
Short Only
Long & Short
Optional setting to reverse positions on opposite signal (instead of waiting for a flat close).
Visual Features
1. RSI Plotting with Thresholds
RSI is displayed in a dedicated pane with overbought/oversold fill zones.
Custom horizontal lines mark threshold boundaries.
2. Parabolic SAR Overlay on RSI
SAR dots color-coded for trend direction.
Visible only when enabled by user input.
3. Entry & Exit Markers
Diamonds: Mark entry points (above for shorts, below for longs).
Crosses: Mark exit points.
Strategy Strengths
Provides early momentum reversal entries without relying on price candles.
Combines oscillator and trend logic without repainting.
Works well in both trending and mean-reverting markets.
Easy to configure with fine-tuned filter options.
Recommended Use Cases
Intraday or swing traders who want to catch RSI-based reversals early.
Traders seeking smoother signals than price-based Parabolic SAR entries.
Users of RSI looking to reduce false positives via trend tracking.
Customization Options
RSI Length and Thresholds.
SAR Start, Increment, and Maximum values.
Trade Direction Mode (Long, Short, Both).
Optional RSI filter and reverse-on-signal settings.
SAR dot color customization.
Conclusion
The Parabolic RSI Strategy is an innovative, non-repainting momentum strategy that enhances RSI-based systems with trend-confirming logic using Parabolic SAR. By applying SAR logic to RSI values, this strategy offers early, visualized, and filtered entries and exits that adapt to market dynamics.
Credit to ChartPrime for the original methodology, published under MPL-2.0.
Multi-Indicator Swing [TIAMATCRYPTO]v6# Strategy Description:
## Multi-Indicator Swing
This strategy is designed for swing trading across various markets by combining multiple technical indicators to identify high-probability trading opportunities. The system focuses on trend strength confirmation and volume analysis to generate precise entry and exit signals.
### Core Components:
- **Supertrend Indicator**: Acts as the primary trend direction filter with optimized settings (Factor: 3.0, ATR Period: 10) to balance responsiveness and reliability.
- **ADX (Average Directional Index)**: Confirms the strength of the prevailing trend, filtering out sideways or choppy market conditions where the strategy avoids taking positions.
- **Liquidity Delta**: A volume-based indicator that analyzes buying and selling pressure imbalances to validate trend direction and potential reversals.
- **PSAR (Optional)**: Can be enabled to add additional confirmation for trend changes, turned off by default to reduce signal filtering.
### Key Features:
- **Flexible Direction Trading**: Choose between long-only, short-only, or bidirectional trading to adapt to market conditions or account restrictions.
- **Conservative Risk Management**: Implements fixed percentage-based stop losses (default 2%) and take profits (default 4%) for a positive risk-reward ratio.
- **Realistic Backtesting Parameters**: Includes commission (0.1%) and slippage (2 points) to reflect real-world trading conditions.
- **Visual Signals**: Clear buy/sell arrows with customizable sizes for easy identification on the chart.
- **Information Panel**: Dynamic display showing active indicators and current risk settings.
### Best Used On:
Daily timeframes for cryptocurrencies, forex, or stock indices. The strategy performs optimally on assets with clear trending behavior and sufficient volatility.
### Default Settings:
Optimized for conservative position sizing (5% of equity per trade) with an initial capital of $10,000. The backtesting period (2021-2023) provides a statistically significant sample of varied market conditions.
EXODUS EXODUS by (DAFE) Trading Systems
EXODUS is a sophisticated trading algorithm built by Dskyz (DAFE) Trading Systems for competitive and competition purposes, designed to identify high-probability trades with robust risk management. this strategy leverages a multi-signal voting system, combining three core components—SPR, VWMO, and VEI—alongside ADX, choppiness filters, and ATR-based volatility gates to ensure trades are taken only in favorable market conditions. the algo uses a take-profit to stop-loss ratio, dynamic position sizing, and a strict voting mechanism requiring all signals to align before entering a trade.
EXODUS was not overfitted for any specific symbol. instead, it uses a generic tuned setting, making it versatile across various markets. while it can trade futures, it’s not currently set up for it but has the potential to do more with further development. visuals are intentionally minimal due to its competition focus, prioritizing performance over aesthetics. a more visually stunning version may be released in the future with enhanced graphics.
The Unique Core Components Developed for EXODUS
SPR (Session Price Recalibration)
SPR measures momentum during regular trading hours (RTH, 0930-1600, America/New_York) to catch session-specific trends.
spr_lookback = input.int(15, "SPR Lookback") this sets how many bars back SPR looks to calculate momentum (default 15 bars). it compares the current session’s price-volume score to the score 15 bars ago to gauge momentum strength.
how it works: a longer lookback smooths out the signal, focusing on bigger trends. a shorter one makes SPR more sensitive to recent moves.
how to adjust: on a 1-hour chart, 15 bars is 15 hours (about 2 trading days). if you’re on a shorter timeframe like 5 minutes, 15 bars is just 75 minutes, so you might want to increase it to 50 or 100 to capture more meaningful trends. if you’re trading a choppy stock, a shorter lookback (like 5) can help catch quick moves, but it might give more false signals.
spr_threshold = input.float (0.7, "SPR Threshold")
this is the cutoff for SPR to vote for a trade (default 0.7). if SPR’s normalized value is above 0.7, it votes for a long; below -0.7, it votes for a short.
how it works: SPR normalizes its momentum score by ATR, so this threshold ensures only strong moves count. a higher threshold means fewer trades but higher conviction.
how to adjust: if you’re getting too few trades, lower it to 0.5 to let more signals through. if you’re seeing too many false entries, raise it to 1.0 for stricter filtering. test on your chart to find a balance.
spr_atr_length = input.int(21, "SPR ATR Length") this sets the ATR period (default 21 bars) used to normalize SPR’s momentum score. ATR measures volatility, so this makes SPR’s signal relative to market conditions.
how it works: a longer ATR period (like 21) smooths out volatility, making SPR less jumpy. a shorter one makes it more reactive.
how to adjust: if you’re trading a volatile stock like TSLA, a longer period (30 or 50) can help avoid noise. for a calmer stock, try 10 to make SPR more responsive. match this to your timeframe—shorter timeframes might need a shorter ATR.
rth_session = input.session("0930-1600","SPR: RTH Sess.") rth_timezone = "America/New_York" this defines the session SPR uses (0930-1600, New York time). SPR only calculates momentum during these hours to focus on RTH activity.
how it works: it ignores pre-market or after-hours noise, ensuring SPR captures the main market action.
how to adjust: if you trade a different session (like London hours, 0300-1200 EST), change the session to match. you can also adjust the timezone if you’re in a different region, like "Europe/London". just make sure your chart’s timezone aligns with this setting.
VWMO (Volume-Weighted Momentum Oscillator)
VWMO measures momentum weighted by volume to spot sustained, high-conviction moves.
vwmo_momlen = input.int(21, "VWMO Momentum Length") this sets how many bars back VWMO looks to calculate price momentum (default 21 bars). it takes the price change (close minus close 21 bars ago).
how it works: a longer period captures bigger trends, while a shorter one reacts to recent swings.
how to adjust: on a daily chart, 21 bars is about a month—good for trend trading. on a 5-minute chart, it’s just 105 minutes, so you might bump it to 50 or 100 for more meaningful moves. if you want faster signals, drop it to 10, but expect more noise.
vwmo_volback = input.int(30, "VWMO Volume Lookback") this sets the period for calculating average volume (default 30 bars). VWMO weights momentum by volume divided by this average.
how it works: it compares current volume to the average to see if a move has strong participation. a longer lookback smooths the average, while a shorter one makes it more sensitive.
how to adjust: for stocks with spiky volume (like NVDA on earnings), a longer lookback (50 or 100) avoids overreacting to one-off spikes. for steady volume stocks, try 20. match this to your timeframe—shorter timeframes might need a shorter lookback.
vwmo_smooth = input.int(9, "VWMO Smoothing")
this sets the SMA period to smooth VWMO’s raw momentum (default 9 bars).
how it works: smoothing reduces noise in the signal, making VWMO more reliable for voting. a longer smoothing period cuts more noise but adds lag.
how to adjust: if VWMO is too jumpy (lots of false votes), increase to 15. if it’s too slow and missing trades, drop to 5. test on your chart to see what keeps the signal clean but responsive.
vwmo_threshold = input.float(10, "VWMO Threshold") this is the cutoff for VWMO to vote for a trade (default 10). above 10, it votes for a long; below -10, a short.
how it works: it ensures only strong momentum signals count. a higher threshold means fewer but stronger trades.
how to adjust: if you want more trades, lower it to 5. if you’re getting too many weak signals, raise it to 15. this depends on your market—volatile stocks might need a higher threshold to filter noise.
VEI (Velocity Efficiency Index)
VEI measures market efficiency and velocity to filter out choppy moves and focus on strong trends.
vei_eflen = input.int(14, "VEI Efficiency Smoothing") this sets the EMA period for smoothing VEI’s efficiency calc (bar range / volume, default 14 bars).
how it works: efficiency is how much price moves per unit of volume. smoothing it with an EMA reduces noise, focusing on consistent efficiency. a longer period smooths more but adds lag.
how to adjust: for choppy markets, increase to 20 to filter out noise. for faster markets, drop to 10 for quicker signals. this should match your timeframe—shorter timeframes might need a shorter period.
vei_momlen = input.int(8, "VEI Momentum Length") this sets how many bars back VEI looks to calculate momentum in efficiency (default 8 bars).
how it works: it measures the change in smoothed efficiency over 8 bars, then adjusts for inertia (volume-to-range). a longer period captures bigger shifts, while a shorter one reacts faster.
how to adjust: if VEI is missing quick reversals, drop to 5. if it’s too noisy, raise to 12. test on your chart to see what catches the right moves without too many false signals.
vei_threshold = input.float(4.5, "VEI Threshold") this is the cutoff for VEI to vote for a trade (default 4.5). above 4.5, it votes for a long; below -4.5, a short.
how it works: it ensures only strong, efficient moves count. a higher threshold means fewer trades but higher quality.
how to adjust: if you’re not getting enough trades, lower to 3. if you’re seeing too many false entries, raise to 6. this depends on your market—fast stocks like NQ1 might need a lower threshold.
Features
Multi-Signal Voting: requires all three signals (SPR, VWMO, VEI) to align for a trade, ensuring high-probability setups.
Risk Management: uses ATR-based stops (2.1x) and take-profits (4.1x), with dynamic position sizing based on a risk percentage (default 0.4%).
Market Filters: ADX (default 27) ensures trending conditions, choppiness index (default 54.5) avoids sideways markets, and ATR expansion (default 1.12) confirms volatility.
Dashboard: provides real-time stats like SPR, VWMO, VEI values, net P/L, win rate, and streak, with a clean, functional design.
Visuals
EXODUS prioritizes performance over visuals, as it was built for competitive and competition purposes. entry/exit signals are marked with simple labels and shapes, and a basic heatmap highlights market regimes. a more visually stunning update may be released later, with enhanced graphics and overlays.
Usage
EXODUS is designed for stocks and ETFs but can be adapted for futures with adjustments. it performs best in trending markets with sufficient volatility, as confirmed by its generic tuning across symbols like TSLA, AMD, NVDA, and NQ1. adjust inputs like SPR threshold, VWMO smoothing, or VEI momentum length to suit specific assets or timeframes.
Setting I used: (Again, these are a generic setting, each security needs to be fine tuned)
SPR LB = 19 SPR TH = 0.5 SPR ATR L= 21 SPR RTH Sess: 9:30 – 16:00
VWMO L = 21 VWMO LB = 18 VWMO S = 6 VWMO T = 8
VEI ES = 14 VEI ML = 21 VEI T = 4
R % = 0.4
ATR L = 21 ATR M (S) =1.1 TP Multi = 2.1 ATR min mult = 0.8 ATR Expansion = 1.02
ADX L = 21 Min ADX = 25
Choppiness Index = 14 Chop. Max T = 55.5
Backtesting: TSLA
Frame: Jan 02, 2018, 08:00 — May 01, 2025, 09:00
Slippage: 3
Commission .01
Disclaimer
this strategy is for educational purposes. past performance is not indicative of future results. trading involves significant risk, and you should only trade with capital you can afford to lose. always backtest and validate any strategy before using it in live markets.
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
About the Author
Dskyz (DAFE) Trading Systems is dedicated to building high-performance trading algorithms. EXODUS is a product of rigorous research and development, aimed at delivering consistent, and data-driven trading solutions.
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
2025 Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
RTB - Momentum Breakout Strategy V3
📈 RTB - Momentum Breakout Strategy V3 is a directional breakout strategy based on momentum. It combines exponential moving averages (EMAs), RSI, and recent support/resistance levels to detect breakout entries with trend confirmation. The system includes dynamic risk management using ATR-based stop-loss and trailing stop levels. Webhook alerts are supported for external automated trading integrations.
🔎 The strategy was backtested using default parameters on BTCUSDT Futures (Bybit) with 4-hour timeframe and a 0.05% commission per trade.
⚠️ This script is for educational purposes only and does not constitute financial advice. Always do your own research before trading.