Advanced Trend Following Strategy with Adaptive Trailing Stop

Pine ScriptTrend following Mean reversion Volatility ATR Supertrend

Author: ChaoZhang
Complexity: Starter · 87 lines
Parameters: 0
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

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Overview

This is a trend following strategy based on the Supertrend indicator, combined with an adaptive trailing stop loss mechanism. The strategy primarily uses the Supertrend indicator to identify market trend direction and employs dynamically adjusted trailing stops to manage risk and optimize exit timing. It supports multiple stop loss methods, including percentage-based, ATR-based, and fixed-point stops, allowing flexible adjustment according to different market conditions.

Strategy Principles

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

Uses the Supertrend indicator as the primary basis for trend determination, which combines ATR (Average True Range) to measure market volatility
Entry signals are triggered by Supertrend direction changes, supporting long, short, or bilateral trading
Stop loss mechanism employs adaptive trailing stops that automatically adjust based on market volatility
Trade management system includes position sizing (default 15% of account equity) and time filtering mechanisms

Strategy Advantages

Strong trend capture capability: Effectively identifies major trends through the Supertrend indicator, reducing false signals
Comprehensive risk control: Employs diverse stop loss mechanisms suitable for different market environments
High flexibility: Supports configuration of multiple trading directions and stop loss methods
Strong adaptability: Trailing stops automatically adjust according to market volatility, enhancing strategy adaptability
Complete backtesting system: Built-in time filtering functionality for historical performance analysis

Strategy Risks

Trend reversal risk: False signals may occur in highly volatile markets
Slippage risk: Trailing stop execution may be affected by market liquidity
Parameter sensitivity: Supertrend factor and ATR period settings significantly impact strategy performance
Market environment dependency: Frequent trading in ranging markets may increase costs

Strategy Optimization Directions

Signal filtering optimization: Additional technical indicators can be added to filter false signals
Position management optimization: Position size can be dynamically adjusted based on market volatility
Stop loss mechanism enhancement: More complex stop loss logic can be designed incorporating cost average price
Entry timing optimization: Price structure analysis can be added to improve entry accuracy
Backtesting system improvement: More statistical indicators can be added to evaluate strategy performance

Summary

This is a well-designed trend following strategy with controllable risk. By combining the Supertrend indicator with flexible stop loss mechanisms, the strategy can maintain high profitability while effectively controlling risk. The strategy is highly configurable and suitable for use in different market environments, but requires thorough parameter optimization and backtesting verification. Future improvements can be made by adding more technical analysis tools and risk control measures to further enhance strategy stability and profitability.

Source Pine Script

/*backtest
start: 2019-12-23 08:00:00
end: 2024-12-18 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=6
strategy("Supertrend Strategy with Adjustable Trailing Stop [Bips]", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=15)

// Inputs
atrPeriod = input(10, "ATR Länge", "Average True Range „wahre durchschnittliche Schwankungsbreite" und stammt aus der technischen Analyse. Die ATR misst die Volatilität eines Instruments oder eines Marktes. Mit ihr kann die Wahrscheinlichkeit für einen Trendwechsel bestimmt werden.", group="Supertrend Settings")
factor = input.float(3.0, "Faktor", step=0.1, group="Supertrend Settings")
tradeDirection = input.string("Long", "Trade Direction", options=["Both", "Long", "Short"], group="Supertrend Settings")
sl_type    = input.string("%", "SL Type", options=["%", "ATR", "Absolute"])
// Parameter für ST nur für einstieg -> Beim Ausstieg fragen ob der bool WWert true ist -> Für weniger und längere Trädes 

sl_perc    = input.float(4.0, "% SL", group="Stop Loss Einstellung")
atr_length = input.int(10, "ATR Length", group="Stop Loss Einstellung")
atr_mult   = input.float(2.0, "ATR Mult", group="Stop Loss Einstellung")
sl_absol   = input.float(10.0, "Absolute SL", group="Stop Loss Einstellung")

//-------------------------//
// BACKTESTING RANGE
fromDay   = input.int(defval=1, title="From Day", minval=1, maxval=31, group="Backtesting Einstellung")
fromMonth = input.int(defval=1, title="From Month", minval=1, maxval=12, group="Backtesting Einstellung")
fromYear  = input.int(defval=2016, title="From Year", minval=1970, group="Backtesting Einstellung")
toDay     = input.int(defval=1, title="To Day", minval=1, maxval=31, group="Backtesting Einstellung")
toMonth   = input.int(defval=1, title="To Month", minval=1, maxval=12, group="Backtesting Einstellung")
toYear    = input.int(defval=2100, title="To Year", minval=1970, group="Backtesting Einstellung")

startDate  = timestamp(fromYear, fromMonth, fromDay, 00, 00)
finishDate = timestamp(toYear, toMonth, toDay, 00, 00)
time_cond  = time >= startDate and time <= finishDate

//-------------------------//
// Supertrend calculation
[_, direction] = ta.supertrend(factor, atrPeriod)

// SL values
sl_val = sl_type == "ATR"      ? atr_mult * ta.atr(atr_length) : 
         sl_type == "Absolute" ? sl_absol : 
         close * sl_perc / 100
         
// Init Variables
var pos         = 0
var float trailing_sl = 0.0

// Signals
long_signal  = nz(pos[1]) !=  1 and high > nz(trailing_sl[1])
short_signal = nz(pos[1]) != -1 and low  < nz(trailing_sl[1]) 

// Calculate SL
trailing_sl := short_signal     ? high + sl_val : 
               long_signal      ? low  - sl_val : 
               nz(pos[1]) ==  1 ? math.max(low  - sl_val, nz(trailing_sl[1])) :  
               nz(pos[1]) == -1 ? math.min(high + sl_val, nz(trailing_sl[1])) : 
               nz(trailing_sl[1])
               
// Position var               
pos := long_signal  ? 1 : short_signal ? -1 : nz(pos[1]) 

// Entry logic
if ta.change(direction) < 0 and time_cond
    if tradeDirection == "Both" or tradeDirection == "Long"
        strategy.entry("Long", strategy.long, stop=trailing_sl)
    else
        strategy.close_all("Stop Short")

if ta.change(direction) > 0 and time_cond
    if tradeDirection == "Both" or tradeDirection == "Short"
        strategy.entry("Short", strategy.short, stop=trailing_sl)
    else
        strategy.close_all("Stop Long")

// Exit logic: Trailing Stop and Supertrend
//if strategy.position_size > 0 and not na(trailing_sl)
    //strategy.exit("SL-Exit Long", from_entry="Long", stop=trailing_sl)

//if strategy.position_size < 0 and not na(trailing_sl)
    //strategy.exit("SL-Exit Short", from_entry="Short", stop=trailing_sl)

// Trailing Stop visualization
plot(trailing_sl, linewidth = 2, color = pos == 1 ? color.green : color.red)
//plot(not na(trailing_sl) ? trailing_sl : na, color=pos == 1 ? color.green : color.red, linewidth=2, title="Trailing Stop")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-12-20. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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