Dual Period RSI Trend Momentum Strategy with Pyramiding Position Management System

Pine ScriptMomentum Trend following Breakout RSI ATR ADX / DMI

Author: ChaoZhang
Complexity: Starter · 53 lines
Parameters: 0
Backtest bar: 3h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy is a trend-following trading system based on dual-period RSI (Relative Strength Index) combined with pyramiding position management. The strategy compares RSI indicators of two different periods (14 and 30) to enter trades at trend initiation and adds positions through limit orders during trend continuation, maximizing trend capture. The system includes comprehensive risk control mechanisms, including position management and dynamic exit conditions.

Strategy Principle

The strategy employs dual-period RSI crossover signals as trading triggers combined with pyramiding position management. Specifically:

Entry signals: Uses 14-period RSI breakthrough of oversold (30) and overbought (70) levels as entry signals
Position adding: Implements secondary position adding through limit orders set at 1.5% price deviation after initial entry
Exit signals: Uses 30-period RSI as exit indicator, triggering closure when RSI falls from overbought or rebounds from oversold zones
Position control: System allows maximum of two positions (pyramiding=2) with independently configurable entry quantities

Strategy Advantages

Strong trend capture: Better identifies and tracks medium to long-term trends through dual-period RSI coordination
Optimized risk-reward ratio: Uses pyramiding strategy to amplify returns after trend confirmation
Flexible position management: Adjustable entry and additional position sizes based on market conditions and capital
Dynamic stop-loss design: Uses long-period RSI as exit indicator to avoid premature exits
Strong parameter adaptability: Key parameters can be optimized for different market characteristics

Strategy Risks

Choppy market risk: May incur losses from frequent trading in range-bound markets
Slippage risk: Additional position orders using limit orders may miss optimal entry timing in volatile markets
Capital management risk: Double positions may lead to significant drawdowns
Trend reversal risk: RSI indicator's inherent lag may delay stop-loss execution during trend reversals
Parameter optimization risk: Over-optimization may lead to poor real-trading performance

Strategy Optimization Directions

Introduce trend filters: Add moving averages or ADX indicators to improve entry signal reliability
Optimize position management: Design dynamic position sizing system based on volatility
Enhance stop-loss mechanism: Consider adding trailing stops or ATR-based stop-loss solutions
Add market environment filters: Incorporate volatility indicators to adjust strategy parameters in different market conditions
Improve position adding logic: Dynamically adjust position addition price deviation based on volatility

Summary

The strategy achieves effective trend capture through the combination of dual-period RSI and pyramiding positions. It implements a complete trading system including entry, position adding, stop-loss, and position management elements. Through parameter optimization and risk management improvements, the strategy shows promise for stable performance in actual trading. Traders are advised to thoroughly test and adjust parameters according to specific market characteristics before live implementation.

Source Pine Script

/*backtest
start: 2024-12-17 00:00:00
end: 2025-01-16 00:00:00
period: 3h
basePeriod: 3h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT","balance":49999}]
*/

//@version=5
strategy("RSI Top Strategy", overlay=true, pyramiding=2)

qty1 = input( 1 , "Qty first entry", group="Strategy settings")
qty2 = input( 1 , "Qty second entry", group="Strategy settings")
avg1 = input.float( 1.5 , "% averaging ", group="Strategy settings")

overSold = input( 30 , group="open RSI Settings")
overBought = input( 70 , group="open RSI Settings")
rsi1len = input.int(14, minval=1, title="open RSI Length", group="open RSI Settings")

overSold2 = input( 30 , group="close RSI Settings")
overBought2 = input( 70 , group="close RSI Settings")
rsi2len = input.int(30, minval=1, title="close RSI Length", group="close RSI Settings")

price = close
vrsi = ta.rsi(price, rsi1len)
vrsi2 = ta.rsi(price, rsi2len)

sz=strategy.position_size	

co = ta.crossover(vrsi, overSold)
cu = ta.crossunder(vrsi, overBought)
if (not na(vrsi))
	if (co) and not (sz>0)
		strategy.entry("Long", strategy.long, qty = qty1, comment="Long")
		Avgl=close-close*0.01*avg1
		strategy.entry("AvgL", strategy.long, qty = qty2, limit=Avgl, comment="AvgL")
	if (cu) and not (sz<0)
		strategy.entry("Short", strategy.short, qty = qty1, comment="Short")
		Avgs=close+close*0.01*avg1
		strategy.entry("AvgS", strategy.short, qty = qty2, limit=Avgs, comment="AvgS")
//plot(strategy.equity, title="equity", color=color.red, linewidth=2, style=plot.style_areabr)

if sz[1]<0 and sz<0 and vrsi2<overBought2 and vrsi2[1]>=overBought2
    strategy.close_all("x")
if sz[1]>0 and sz>0 and vrsi2>overSold2  and vrsi2[1]<=overSold2 
    strategy.close_all("x")
    
plot(vrsi,'open rsi',color=color.green)        
plot(vrsi2,'close rsi',color=color.red)    

hline(overBought, "RSI Upper Band", color=#787B86)
hline(overSold, "RSI Upper Band", color=#787B86)

Published by ChaoZhang on the FMZ strategy square · last modified 2025-01-17. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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