Multi-Timeframe Trend Breakout Strategy with RSI Filter and ATR-Based Risk Management

EMA RSI ATR Trend Filter POSITION SIZING risk management
Created on: 2025-04-24 16:55:42 Modified on: 2025-04-24 16:55:42
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Multi-Timeframe Trend Breakout Strategy with RSI Filter and ATR-Based Risk Management Multi-Timeframe Trend Breakout Strategy with RSI Filter and ATR-Based Risk Management

Overview

This strategy combines trend-following and breakout trading across multiple timeframes, using EMA crossovers as trend filters, RSI for momentum confirmation, and ATR for dynamic risk management. It features a separated alert system for precise entry/exit signal management and employs percentage-based money management to control risk.

Strategy Logic

  1. Trend Identification: Uses the crossover relationship between fast EMA(9) and slow EMA(21) to determine market trend direction.
  2. Momentum Confirmation: RSI indicator (period 14) confirms trend strength, requiring RSI>50 for long trades and RSI<50 for short trades.
  3. Breakout Signals: Generates trading signals when price breaks the previous bar’s high/low points after trend confirmation.
  4. Risk Management: Uses ATR (period 14) to calculate dynamic stop-loss levels with fixed 2% account risk per trade. Take-profit is set at 3 times the stop-loss distance, with trailing stop activated after 50% profit.
  5. Position Sizing: Dynamically calculates position size based on stop-loss distance and risk percentage to ensure consistent risk exposure.

Advantages

  1. Multi-factor Verification: Combines trend, momentum and price action confirmation for higher signal quality.
  2. Dynamic Risk Management: ATR-based stops adapt to market volatility changes, with trailing stops protecting floating profits.
  3. Scientific Money Management: Fixed-percentage risk control prevents overtrading, with precise position sizing.
  4. Clear Visual Signals: plotshape function provides intuitive visual cues for monitoring.
  5. Separated Alert System: Independent entry/exit alerts facilitate automated trading integration.

Risks

  1. Range-bound Market Risk: May generate false breakout signals during trendless conditions. Solution: Add ADX filter.
  2. Parameter Sensitivity: Fixed parameters may fail in different instruments/market regimes. Solution: Parameter optimization or adaptive settings.
  3. Gap Risk: Price gaps may cause slippage. Solution: Reduce position before major news.
  4. Overfitting Risk: Historical optimization may not work forward. Solution: Robust out-of-sample testing.

Optimization Directions

  1. Adaptive Parameters: Replace fixed parameters with volatility-based adaptive settings.
  2. Composite Trend Filter: Add higher timeframe trend confirmation.
  3. Dynamic Take-profit: Replace fixed TP ratio with support/resistance or Fibonacci extensions.
  4. Machine Learning: Use reinforcement learning to dynamically adjust RSI thresholds and TP/SL ratios.
  5. Event Filtering: Integrate economic calendar to adjust risk parameters around major events.

Conclusion

This is a well-structured trend-following strategy that improves signal reliability through multi-indicator confirmation and controls downside risk with scientific money management. It performs best in trending markets with moderate volatility. Further enhancements in parameter adaptation and market regime detection could significantly improve robustness and adaptability.

Strategy source code 
// @version=5
strategy("Trend Breakout Strategy with Separated Alerts", overlay=true, initial_capital=10, default_qty_type=strategy.percent_of_equity, default_qty_value=100)

// --- Parameters ---
var float risk_per_trade = 0.02 // 2% risk per trade
var int ema_fast = 9
var int ema_slow = 21
var int rsi_length = 14
var int atr_length = 14
var float atr_multiplier_sl = 2.0 // ATR multiplier for SL
var float tp_ratio = 3.0 // TP to SL ratio = 3:1
var float trail_trigger_ratio = 0.5 // Trailing stop triggers at 50% of TP

// --- Indicators ---
ema9 = ta.ema(close, ema_fast)
ema21 = ta.ema(close, ema_slow)
rsi = ta.rsi(close, rsi_length)
atr = ta.atr(atr_length)

// --- Trend Filter ---
bull_trend = ta.crossover(ema9, ema21) or (ema9 > ema21)
bear_trend = ta.crossunder(ema9, ema21) or (ema9 < ema21)

// --- Entry Conditions ---
long_entry = bull_trend and rsi > 50 and close > high[1]
short_entry = bear_trend and rsi < 50 and close < low[1]

// --- Position Size Calculation ---
equity = strategy.equity
stop_loss_distance = atr * atr_multiplier_sl
risk_amount = equity * risk_per_trade
position_size = risk_amount / stop_loss_distance

// --- SL and TP Levels ---
long_sl = close - stop_loss_distance
long_tp = close + stop_loss_distance * tp_ratio
short_sl = close + stop_loss_distance
short_tp = close - stop_loss_distance * tp_ratio

// --- Trailing Stop (activated after 50% of TP) ---
trail_points = atr * atr_multiplier_sl * tp_ratio * trail_trigger_ratio
trail_offset = atr * atr_multiplier_sl

// --- Entries ---
if long_entry
    strategy.entry("Long", strategy.long, qty=position_size)
    strategy.exit("Long Exit", "Long", stop=long_sl, limit=long_tp, trail_points=trail_points, trail_offset=trail_offset)

if short_entry
    strategy.entry("Short", strategy.short, qty=position_size)
    strategy.exit("Short Exit", "Short", stop=short_sl, limit=short_tp, trail_points=trail_points, trail_offset=trail_offset)

// --- Alert Conditions ---
var bool long_opened = false
var bool short_opened = false

// Track position opening
long_open_alert = long_entry and not long_opened
short_open_alert = short_entry and not short_opened

// Track position closing
long_close_alert = long_opened and strategy.position_size == 0
short_close_alert = short_opened and strategy.position_size == 0

// Update position states
if long_entry
    long_opened := true
if short_entry
    short_opened := true
if strategy.position_size == 0
    long_opened := false
    short_opened := false

// --- Alerts ---
alertcondition(long_open_alert, title="Open Long", message='{"action":"buy","symbol":"{{ticker}}","price":{{close}}}')
alertcondition(long_close_alert, title="Close Long", message='{"action":"close_long","symbol":"{{ticker}}","price":{{close}}}')
alertcondition(short_open_alert, title="Open Short", message='{"action":"sell","symbol":"{{ticker}}","price":{{close}}}')
alertcondition(short_close_alert, title="Close Short", message='{"action":"close_short","symbol":"{{ticker}}","price":{{close}}}')

// --- Visualization ---
plot(ema9, color=color.blue, title="EMA9")
plot(ema21, color=color.red, title="EMA21")
plotshape(long_open_alert, title="Long Entry", location=location.belowbar, color=color.green, style=shape.triangleup, size=size.small)
plotshape(short_open_alert, title="Short Entry", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small)
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