Multi Technical Indicator Based Mean Reversion and Trend Following Strategy

Pine ScriptMean reversion Trend following Breakout RSI EMA SMA Bollinger Bands

Author: ChaoZhang
Complexity: Starter · 73 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 hybrid system combining mean reversion and trend following approaches, utilizing RSI, Bollinger Bands, and multiple EMA indicators to capture market overbought and oversold opportunities. The strategy enhances traditional technical analysis by incorporating trend confirmation and range-bound market identification, significantly improving accuracy.

Strategy Principles

The strategy employs a triple verification mechanism for trade signals. Initially, it identifies overbought/oversold conditions using RSI (below 30 or above 70). Secondly, it confirms signals using Bollinger Bands breakouts. Finally, it validates market trends using 100/50-day EMA relative positions and volatility. Trades are only executed when all three conditions align. The strategy also incorporates EMA volatility assessment for range-bound market identification.

Strategy Advantages

Multiple indicator cross-validation reduces false signals
Combines oversold/overbought and trend following for enhanced adaptability
Incorporates EMA volatility for effective range-bound market identification
Clear visualization for strategy monitoring and optimization
Highly adjustable parameters for different market conditions

Strategy Risks

Multiple indicators may lead to delayed signals
Potential missed opportunities in highly volatile markets
Risk of overfitting through parameter optimization
EMA trend identification may generate confusing signals in sideways markets Recommend backtesting across different timeframes and implementing appropriate stop-loss mechanisms.

Optimization Directions

Incorporate volume indicators for signal confirmation
Implement adaptive parameter adjustment mechanisms
Add profit/loss management module
Develop trend strength scoring system
Optimize EMA volatility calculation method
Add market volatility filters

Summary

The strategy achieves a balance between robustness and flexibility through the synergy of multiple technical indicators. With clear logic and concise implementation, it demonstrates practical value. Through proper parameter optimization and risk management, the strategy shows potential for consistent performance across various market conditions.

Source Pine Script

/*backtest
start: 2024-01-01 00:00:00
end: 2024-11-11 00:00:00
period: 3h
basePeriod: 3h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("BTC Dominance Analysis Strategy (Improved)", overlay=true)

// Input Parameters
rsi_period = input(14, title="RSI Period")
bb_period = input(20, title="Bollinger Band Period")
bb_std_dev = input(2.0, title="Bollinger Std Dev")
ema_period = input(100, title="100 EMA Period")
ema_30_period = input(30, title="30 EMA Period")
ema_50_period = input(50, title="50 EMA Period")

// RSI Calculation
rsi_value = ta.rsi(close, rsi_period)

// Bollinger Bands Calculation
basis = ta.sma(close, bb_period)
dev = bb_std_dev * ta.stdev(close, bb_period)
upper_bb = basis + dev
lower_bb = basis - dev

// EMA Calculation
ema_100 = ta.ema(close, ema_period)
ema_30 = ta.ema(close, ema_30_period)
ema_50 = ta.ema(close, ema_50_period)

// Determine EMA trends
range_bound_ema = math.abs(ema_100 - ta.sma(ema_100, 10)) < ta.stdev(ema_100, 10)
uptrend_ema = ema_100 > ema_50
downtrend_ema = ema_100 < ema_50

// Long Condition: All 3 conditions must be met
// 1. RSI < 30
// 2. BTC Dominance < lower Bollinger Band
// 3. 100 EMA must be range-bound or in an uptrend (but NOT in a downtrend)
long_condition = (rsi_value < 30) and (close < lower_bb) and (range_bound_ema or uptrend_ema)

// Short Condition: All 3 conditions must be met
// 1. RSI > 70
// 2. BTC Dominance > upper Bollinger Band
// 3. 100 EMA must be range-bound or in a downtrend (but NOT in an uptrend)
short_condition = (rsi_value > 70) and (close > upper_bb) and (range_bound_ema or downtrend_ema)

// Plot Buy and Sell Signals for Debugging
plotshape(long_condition, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")
plotshape(short_condition, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")

// Execute Buy Trade
if (long_condition)
    strategy.entry("Buy", strategy.long)

// Execute Sell Trade
if (short_condition)
    strategy.entry("Sell", strategy.short)

// Plot Bollinger Bands and EMA
plot(upper_bb, color=color.red, title="Upper Bollinger Band")
plot(lower_bb, color=color.green, title="Lower Bollinger Band")
plot(ema_100, color=color.blue, title="100 EMA")
plot(ema_50, color=color.orange, title="50 EMA")
// plot(rsi_value, "RSI", color=color.purple)

// Display background color for Buy and Sell signals
bgcolor(long_condition ? color.new(color.green, 90) : na, title="Buy Background")
bgcolor(short_condition ? color.new(color.red, 90) : na, title="Sell Background")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-11-12. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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