Multi Indicator Fusion Mean Reversion Trend Following Strategy

Pine ScriptMean reversion Trend following Volatility MACD EMA SMA ATR

Author: ChaoZhang
Complexity: Starter · 62 lines
Parameters: 0
Backtest bar: 3h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy combines mean reversion and trend following approaches, utilizing MA, MACD, and ATR technical indicators for generating trading signals and risk control. The core concept is to capture market reversals when price deviates from moving averages, confirmed by MACD crossover signals, while implementing ATR-based dynamic stop-loss for risk management.

Strategy Principles

The strategy employs a triple verification mechanism:

Using Moving Average (MA) to assess price deviation, with options for SMA or EMA
Utilizing MACD crossovers to identify trend reversal timing
Implementing ATR indicator for dynamic stop-loss placement Specifically, long positions are initiated when price is below MA with MACD golden cross, while short positions are triggered when price is above MA with MACD death cross. Stop-loss levels are automatically set based on ATR volatility.

Strategy Advantages

High signal reliability: Multiple indicator verification reduces false signals
Comprehensive risk control: ATR dynamic stop-loss prevents significant drawdowns
Flexible parameters: Adjustable based on different market characteristics
Clear strategy logic: Explicit entry and exit conditions
Strong adaptability: Applicable to various timeframes and market conditions

Strategy Risks

Frequent trading in choppy markets may increase costs
Possible lag in trend reversal detection
Parameter optimization risks overfitting
Potential slippage during high volatility periods
Multiple indicators may reduce strategy efficiency

Optimization Directions

Incorporate volume indicators for enhanced signal reliability
Add trend strength filters to avoid weak market conditions
Optimize stop-loss mechanism, consider trailing stops
Include volatility filters to adjust positions during high volatility periods
Develop adaptive parameter mechanisms for improved stability

Summary

This strategy achieves a relatively robust trading system by combining mean reversion and trend following approaches. The multiple indicator verification mechanism enhances trading signal reliability, while ATR dynamic stop-loss effectively controls risk. Despite some room for optimization, it represents a logically sound and practical strategy framework.

Source Pine Script

/*backtest
start: 2024-10-01 00:00:00
end: 2024-10-31 23:59:59
period: 3h
basePeriod: 3h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Mean Reversion Strategy with ATR, MACD and MA", overlay=true)

// === Настройки для индикаторов ===
// Параметры скользящей средней (MA)
maLength = input.int(30, title="Период скользящей средней (MA)")
maType = input.string("EMA", title="Тип скользящей средней", options=["SMA", "EMA"])

// Параметры ATR
atrLength = input.int(10, title="Период ATR")
atrMultiplier = input.float(10, title="ATR множитель для стоп-лосса")

// Параметры MACD
macdFastLength = input.int(8, title="Период быстрой EMA для MACD")
macdSlowLength = input.int(26, title="Период медленной EMA для MACD")
macdSignalLength = input.int(5, title="Период сигнальной линии MACD")

// === Рассчёт индикаторов ===
// Скользящая средняя
ma = if maType == "SMA"
    ta.sma(close, maLength)
else
    ta.ema(close, maLength)

// ATR (Средний истинный диапазон)
atr = ta.atr(atrLength)

// MACD
[macdLine, signalLine, _] = ta.macd(close, macdFastLength, macdSlowLength, macdSignalLength)

// Условия для входа на покупку и продажу
longCondition = ta.crossover(macdLine, signalLine) and close < ma
shortCondition = ta.crossunder(macdLine, signalLine) and close > ma

// === Управление позициями ===
if (longCondition)
    strategy.entry("Buy", strategy.long)
    // Стоп-лосс на основе ATR
    stopLossLevel = close - atr * atrMultiplier
    strategy.exit("Take Profit/Stop Loss", "Buy", stop=stopLossLevel)

if (shortCondition)
    strategy.entry("Sell", strategy.short)
    // Стоп-лосс на основе ATR
    stopLossLevel = close + atr * atrMultiplier
    strategy.exit("Take Profit/Stop Loss", "Sell", stop=stopLossLevel)

// Визуализация
plot(ma, title="MA", color=color.blue, linewidth=2)
plot(macdLine, title="MACD Line", color=color.green)
plot(signalLine, title="Signal Line", color=color.red)
hline(0, "Zero Line", color=color.gray)

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.

Build this with AgenKit

A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.

in Claude Code, Cursor, Codex & 4 more

/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/Multi-Indicator-Fusion-Mean-Reversion-Trend-Following-Strategy.md

npx agenkit install engineering-kit in your project
Paste the command into your agent and approve each phase
Get tests, backtest, risk controls and a paper-trading switch

Get AgenKit How /agenkit works

Understand it first

Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.