Multi Indicator Trend Momentum Trading Strategy An Optimized Quantitative Trading System Based on Bollinger Bands Fibonacci and ATR

Pine ScriptMomentum Trend following Machine learning RSI MACD EMA SMA Bollinger Bands ATR

Author: ChaoZhang
Complexity: Starter · 75 lines
Parameters: 0
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

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Overview

This strategy is a multi-dimensional technical analysis trading system that combines momentum indicators (RSI, MACD), trend indicators (EMA), volatility indicators (Bollinger Bands, ATR), and price structure indicators (Fibonacci retracements) to capture market opportunities through multi-dimensional signal coordination. The strategy is optimized for 15-minute timeframes and employs ATR-based dynamic stop-loss and take-profit levels, demonstrating strong risk control capabilities.

Strategy Principles

The core logic includes the following dimensions:

Trend Confirmation: Using 9/21 period EMA crossovers to determine trend direction
Momentum Verification: Combining RSI overbought/oversold (55/45) and MACD histogram for momentum validation
Volatility Reference: Using Bollinger Bands (20 periods, 2 standard deviations) to measure price volatility
Support/Resistance: Fibonacci 0.382/0.618/0.786 levels calculated from 100-period high/low
Risk Management: 1.5x ATR stop-loss and 3x ATR take-profit based on 14-period ATR

Trading occurs only when multiple dimensional signals align, improving trading accuracy.

Strategy Advantages

Multi-dimensional signal cross-validation reduces false signals
Dynamic ATR-based stop-loss and take-profit adapts to different market conditions
Integration of classic technical indicators makes it easy to understand and maintain
Precise entry timing improves win rate
Risk-reward ratio of 1:2 meets professional trading standards
Suitable for highly volatile market environments

Strategy Risks

Parameter optimization may lead to overfitting
Multiple signal conditions might miss some market moves
Fixed multiplier stops may fail in extreme market conditions
High computational resource requirements
Trading costs may impact strategy performance

Strategy Optimization Directions

Introduce volume factors to verify signal strength
Dynamically adjust RSI thresholds for different markets
Add trend strength filters
Optimize stop-loss and take-profit multipliers
Add time filters to avoid ranging markets
Consider implementing machine learning for dynamic parameter optimization

Summary

This strategy builds a robust trading system through the coordination of multi-dimensional technical indicators. Its core advantages lie in signal cross-validation and dynamic risk control, but attention must be paid to parameter optimization and market environment adaptability. Future optimization should focus on dynamic parameter adjustment and signal quality improvement.

Source Pine Script

/*backtest
start: 2024-12-10 00:00:00
end: 2025-01-08 08:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT","balance":49999}]
*/

//@version=5
strategy("Optimized Advanced Strategy", overlay=true)

// Bollinger Bandı
length = input(20, title="Bollinger Band Length")
src = close
mult = input.float(2.0, title="Bollinger Band Multiplier")
basis = ta.sma(src, length)
dev = mult * ta.stdev(src, length)
upper = basis + dev
lower = basis - dev

// RSI
rsi = ta.rsi(close, 14)

// MACD
[macdLine, signalLine, _] = ta.macd(close, 12, 26, 9)

// EMA
emaFast = ta.ema(close, 9)
emaSlow = ta.ema(close, 21)

// ATR
atr = ta.atr(14)

// Fibonacci Seviyeleri
lookback = input(100, title="Fibonacci Lookback Period")
highPrice = ta.highest(high, lookback)
lowPrice = ta.lowest(low, lookback)
fiboLevel618 = lowPrice + (highPrice - lowPrice) * 0.618
fiboLevel382 = lowPrice + (highPrice - lowPrice) * 0.382
fiboLevel786 = lowPrice + (highPrice - lowPrice) * 0.786

// Kullanıcı Ayarlı Stop-Loss ve Take-Profit
stopLossATR = atr * 1.5
takeProfitATR = atr * 3

// İşlem Koşulları
longCondition = (rsi < 55) and (macdLine > signalLine) and (emaFast > emaSlow) and (close >= fiboLevel382 and close <= fiboLevel618)
shortCondition = (rsi > 45) and (macdLine < signalLine) and (emaFast < emaSlow) and (close >= fiboLevel618 and close <= fiboLevel786)

// İşlem Girişleri
if (longCondition)
    strategy.entry("Long", strategy.long, stop=close - stopLossATR, limit=close + takeProfitATR, comment="LONG SIGNAL")

if (shortCondition)
    strategy.entry("Short", strategy.short, stop=close + stopLossATR, limit=close - takeProfitATR, comment="SHORT SIGNAL")

// Bollinger Bandını Çizdir
plot(upper, color=color.red, title="Bollinger Upper Band")
plot(basis, color=color.blue, title="Bollinger Basis")
plot(lower, color=color.green, title="Bollinger Lower Band")

// Fibonacci Seviyelerini Çizdir
// line.new(x1=bar_index[1], y1=fiboLevel382, x2=bar_index, y2=fiboLevel382, color=color.blue, width=1, style=line.style_dotted)
// line.new(x1=bar_index[1], y1=fiboLevel618, x2=bar_index, y2=fiboLevel618, color=color.orange, width=1, style=line.style_dotted)
// line.new(x1=bar_index[1], y1=fiboLevel786, x2=bar_index, y2=fiboLevel786, color=color.purple, width=1, style=line.style_dotted)

// Göstergeleri Görselleştir
plot(macdLine, color=color.blue, title="MACD Line")
plot(signalLine, color=color.orange, title="MACD Signal Line")
plot(emaFast, color=color.green, title="EMA Fast (9)")
plot(emaSlow, color=color.red, title="EMA Slow (21)")

// İşlem İşaretleri
plotshape(series=longCondition, location=location.belowbar, color=color.green, style=shape.labelup, title="Long Entry")
plotshape(series=shortCondition, location=location.abovebar, color=color.red, style=shape.labeldown, title="Short Entry")

Published by ChaoZhang on the FMZ strategy square · last modified 2025-01-10. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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