Multi Timeframe Stochastic Oscillator Trend Following Trading Strategy

Pine ScriptTrend following Multi-timeframe Mean reversion EMA SMA ATR Stochastic Volume

Author: ChaoZhang
Complexity: Starter · 79 lines
Parameters: 0
Backtest bar: 3h · intraday
Tested on: BTC/USDT · futures

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Overview

This strategy is a trend-following trading system that combines multi-timeframe Stochastic Oscillator with Exponential Moving Average (EMA). It uses higher timeframe Stochastic for overbought/oversold conditions, EMA as a trend filter, and integrates dynamic position sizing and trailing stop functionality, forming a comprehensive trading system.

Strategy Principles

The core logic is based on several key elements:

Uses higher timeframe Stochastic to identify overbought/oversold areas, generating potential signals through crossovers
Employs EMA as a trend filter, only taking long positions above EMA and short positions below
Calculates dynamic stop-loss and take-profit levels based on ATR, with stop-loss at 1.5x ATR and take-profit at 2x stop-loss
Implements risk-based position sizing, ensuring each trade risks a predetermined percentage of account balance
Optional trailing stop feature with a distance of 1.5x ATR

Strategy Advantages

Multiple signal confirmation: Combines higher timeframe Stochastic with EMA trend filter for improved signal reliability
Comprehensive risk management: Uses percentage-based risk management for capital preservation
Flexible stop-loss mechanism: Supports both fixed and trailing stops, adapting to different market conditions
Clear trade visualization: Automatically marks entry points, stop-loss, and target levels for easy execution
Dynamic position sizing: Adjusts trade size based on volatility for optimized capital efficiency

Strategy Risks

Trend reversal risk: May generate false signals in highly volatile markets
Slippage risk: Potential significant slippage during low liquidity periods
Parameter sensitivity: Strategy performance is sensitive to parameter settings, requiring careful optimization
Drawdown risk: May experience significant drawdowns during extreme market volatility
Stop-loss trigger risk: Trailing stops may trigger prematurely during increased volatility

Strategy Optimization Directions

Add market condition filters: Incorporate volatility or trend strength indicators to adjust parameters based on market conditions
Enhance signal confirmation: Consider adding volume confirmation or other technical indicators as supplementary filters
Improve position management: Dynamically adjust risk percentage based on market volatility
Refine stop-loss mechanism: Dynamically adjust trailing stop distance based on market characteristics
Implement time filters: Consider trading restrictions during key time periods to avoid news-related risks

Summary

This strategy builds a comprehensive trading system through multi-timeframe analysis and multiple signal confirmation mechanisms, combined with a robust risk management framework. While certain risks exist, continuous optimization and improvement can help maintain stable performance across different market conditions. It is suitable for experienced traders with higher risk tolerance.

Source Pine Script

/*backtest
start: 2024-02-19 00:00:00
end: 2025-02-17 00:00:00
period: 3h
basePeriod: 3h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Ultimate fairas Oil", overlay=true)

// === Input Parameter ===
k_period = input(14, "K Period")
d_period = input(3, "D Period")
smooth_k = input(3, "Smooth K")
overbought = input(80, "Overbought Level")
oversold = input(20, "Oversold Level")
atrMult = input(1.5, "ATR Multiplier")
use_trailing_stop = input(true, "Enable Trailing Stop")
ema_length = input(50, "EMA Length")
risk_percent = input(2, "Risk per Trade (%)") / 100
account_balance = input(50000, "Account Balance")
mtf_tf = input.timeframe("D", "Higher Timeframe for Stochastic")

// === Multi-Timeframe Stochastic ===
stoch_source = request.security(syminfo.tickerid, mtf_tf, ta.stoch(close, high, low, k_period))
k = ta.sma(stoch_source, smooth_k)

// === Trend Filter (EMA) ===
ema = ta.ema(close, ema_length)
trendUp = close > ema
trendDown = close < ema

// === Entry Conditions ===
longCondition = ta.crossover(k, oversold) and trendUp
shortCondition = ta.crossunder(k, overbought) and trendDown

// === ATR-Based Stop Loss & Take Profit ===
atrValue = ta.atr(14)
stopLoss = atrMult * atrValue
takeProfit = 2 * stopLoss

// === Dynamic Lot Sizing (Risk Management) ===
risk_amount = account_balance * risk_percent
position_size = risk_amount / stopLoss

// === Trailing Stop Calculation ===
trailOffset = atrValue * 1.5
trailStopLong = use_trailing_stop ? close - trailOffset : na
trailStopShort = use_trailing_stop ? close + trailOffset : na

// === Execute Trades ===
if longCondition
    strategy.entry("Long", strategy.long, qty=position_size)
    strategy.exit("Exit Long", from_entry="Long", stop=close - stopLoss, limit=close + takeProfit, trail_points=use_trailing_stop ? trailOffset : na)

    // // Labels & Lines
    // label.new(x=bar_index, y=close, text="BUY", color=color.green, textcolor=color.white, size=size.small, style=label.style_label_down)
    // label.new(x=bar_index, y=close + takeProfit, text="TP ?", color=color.blue, textcolor=color.white, size=size.tiny)
    // label.new(x=bar_index, y=close - stopLoss, text="SL ❌", color=color.red, textcolor=color.white, size=size.tiny)
    // line.new(x1=bar_index, y1=close + takeProfit, x2=bar_index + 5, y2=close + takeProfit, width=2, color=color.blue)
    // line.new(x1=bar_index, y1=close - stopLoss, x2=bar_index + 5, y2=close - stopLoss, width=2, color=color.red)

    // Alert
    alert("BUY Signal! TP: " + str.tostring(close + takeProfit) + ", SL: " + str.tostring(close - stopLoss) + ", Lot Size: " + str.tostring(position_size), alert.freq_once_per_bar_close)

if shortCondition
    strategy.entry("Short", strategy.short, qty=position_size)
    strategy.exit("Exit Short", from_entry="Short", stop=close + stopLoss, limit=close - takeProfit, trail_points=use_trailing_stop ? trailOffset : na)

    // // Labels & Lines
    // label.new(x=bar_index, y=close, text="SELL", color=color.red, textcolor=color.white, size=size.small, style=label.style_label_up)
    // label.new(x=bar_index, y=close - takeProfit, text="TP ?", color=color.blue, textcolor=color.white, size=size.tiny)
    // label.new(x=bar_index, y=close + stopLoss, text="SL ❌", color=color.green, textcolor=color.white, size=size.tiny)
    // line.new(x1=bar_index, y1=close - takeProfit, x2=bar_index + 5, y2=close - takeProfit, width=2, color=color.blue)
    // line.new(x1=bar_index, y1=close + stopLoss, x2=bar_index + 5, y2=close + stopLoss, width=2, color=color.green)

    // Alert
    alert("SELL Signal! TP: " + str.tostring(close - takeProfit) + ", SL: " + str.tostring(close + stopLoss) + ", Lot Size: " + str.tostring(position_size), alert.freq_once_per_bar_close)

Published by ChaoZhang on the FMZ strategy square · last modified 2025-02-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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