Momentum Reversal Quantitative Trading Strategy Combining Bollinger Bands and RSI

Pine ScriptMean reversion Momentum Trend following RSI SMA Bollinger Bands Volume

Author: ianzeng123
Complexity: Starter · 52 lines
Parameters: 0
Backtest bar: 1h · intraday
Tested on: BNB/USDT · spot

Jump to code View in vault Original on FMZ

Overview

This strategy is a technical analysis trading system that combines Bollinger Bands and Relative Strength Index (RSI). It seeks trading opportunities in overbought and oversold areas by utilizing price volatility and market momentum characteristics. The strategy generates buy signals when RSI indicates oversold conditions (below 30) and price breaks above the lower Bollinger Band; sell signals are generated when RSI indicates overbought conditions (above 70) and price breaks below the upper Bollinger Band. The middle Bollinger Band is used as a stop-loss position.

Strategy Principles

The core logic of the strategy is based on the following key elements:

Bollinger Bands parameters use 20-period moving average as the middle band, with a standard deviation multiplier of 2.0
RSI uses the traditional 14-period setting
Entry conditions:
- Buy: price breaks above lower Bollinger Band and RSI<30
- Sell: price breaks below upper Bollinger Band and RSI>70
Exit conditions: positions are closed when price crosses the middle Bollinger Band (20-period moving average) This combination considers both price statistics and momentum indicators, effectively improving trading accuracy.

Strategy Advantages

Multiple confirmation mechanism: combines price and momentum indicators to reduce false signals
Reasonable risk control: uses middle Bollinger Band as stop-loss point for both profit protection and risk control
Strong adaptability: Bollinger Bands automatically adjust bandwidth based on market volatility
Classic parameter settings: uses widely validated parameter combinations for strategy stability
Clear logic: trading rules are explicit, facilitating backtesting and live trading

Strategy Risks

Choppy market risk: may generate frequent trading signals in sideways markets
Trend market risk: might miss part of strong trends
Parameter sensitivity: strategy performance is significantly affected by Bollinger Bands period and RSI settings
Slippage impact: may face significant slippage during rapid price movements Recommended risk management measures:

Set appropriate position sizing
Add trend filters
Optimize parameter adaptation mechanism
Consider trading costs in backtesting

Strategy Optimization Directions

Dynamic parameter optimization:
- Dynamically adjust Bollinger Bands parameters based on market volatility
- Adjust RSI thresholds based on market conditions
Add auxiliary indicators:
- Include volume confirmation
- Consider trend indicators as filters
Improve stop-loss mechanism:
- Implement trailing stops
- Set maximum loss limits
Optimize trade execution:
- Implement partial position trading
- Add entry price optimization logic

Conclusion

This strategy constructs a relatively complete trading system by combining Bollinger Bands and RSI indicators. The strategy logic is clear, risk control is reasonable, and it has practical value. Through the suggested optimization directions, there is room for further improvement. In practical application, investors are advised to make appropriate adjustments based on their risk tolerance and market conditions.

Source Pine Script

/*backtest
start: 2024-07-15 00:00:00
end: 2025-02-18 08:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Binance","currency":"BNB_USDT"}]
*/

//@version=5
strategy("Bollinger Bands + RSI Strategy", overlay=true)

// Bollinger Bands parameters
length = input.int(20, title="Bollinger Bands Length")
src = input(close, title="Source")
mult = input.float(2.0, title="Bollinger Bands Multiplier")

basis = ta.sma(src, length)
dev = mult * ta.stdev(src, length)
upper_band = basis + dev
lower_band = basis - dev

// RSI parameters
rsi_length = input.int(14, title="RSI Length")
rsi = ta.rsi(src, rsi_length)

// Plot Bollinger Bands
plot(upper_band, color=color.red, linewidth=2, title="Upper Bollinger Band")
plot(lower_band, color=color.green, linewidth=2, title="Lower Bollinger Band")
plot(basis, color=color.blue, linewidth=1, title="Middle Band")

// Buy Condition
buy_condition = ta.crossover(close, lower_band) and rsi < 30
if buy_condition
    strategy.entry("Buy", strategy.long)

// Sell Condition
sell_condition = ta.crossunder(close, upper_band) and rsi > 70
if sell_condition
    strategy.entry("Sell", strategy.short)

// Exit Conditions (optional: use the middle Bollinger Band for exits)
exit_condition = ta.cross(close, basis)
if exit_condition
    strategy.close("Buy")
    strategy.close("Sell")

// Optional: Plot RSI for additional insight
hline(70, "Overbought", color=color.red)
hline(30, "Oversold", color=color.green)
plot(rsi, color=color.purple, title="RSI", linewidth=1, offset=-5)

Published by ianzeng123 on the FMZ strategy square · last modified 2025-02-20. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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