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Strategy vault / Trend following

Parabolic SAR Trailing Stop Strategy Based on ATR Indicator

This strategy is named "Parabolic SAR Trailing Stop Strategy Based on ATR Indicator". It uses the ATR indicator to adjust the acceleration factor of Parabolic SAR for adapting to changing market volatility. The…

Pine ScriptTrend followingVolatilityATRParabolic SAR
Author
ChaoZhang
Complexity
Starter · 70 lines
Parameters
5
Backtest bar
1h · intraday
Tested on
BTC/USDT · futures
Jump to codeView in vaultOriginal on FMZ

This strategy is named "Parabolic SAR Trailing Stop Strategy Based on ATR Indicator". It uses the ATR indicator to adjust the acceleration factor of Parabolic SAR for adapting to changing market volatility.

The acceleration factor of traditional Parabolic SAR remains fixed and cannot adapt to increased volatility. This strategy makes the SAR curve contract faster as ATR value expands, so the stop can tighten quicker around prices when volatility rises to effectively control risks.

Specifically, after determining price trend, an adaptive acceleration factor is calculated based on ATR value to plot the Parabolic SAR trailing stop curve. When prices breach the stop level, the stop loss is triggered.

The advantage of this strategy is making traditional Parabolic SAR stops dynamic based on market volatility. But ATR parameters need optimization, and the stop line can be prone to premature breach.

In general, adaptive stops are important for protecting profits and limiting risks. Traders should choose suitable stop indicators based on market conditions, and test and optimize parameters, in order to maximize the utility of stop loss strategies.

Parameters

NameDefaultWhat it controls
v_input_114atr_length
v_input_20.02start
v_input_30.02increment
v_input_40.2maximum
v_input_5trueEntry on Nth trend bar

Source Pine Script

/*backtest
start: 2023-08-13 00:00:00
end: 2023-09-12 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy(title="ATR Parabolic SAR Strategy [QuantNomad]", shorttitle="ATR PSAR Strategy [QN]", overlay=true, default_qty_type = strategy.percent_of_equity,  default_qty_value = 100)

atr_length = input(14)
start      = input(0.02)
increment  = input(0.02)
maximum    = input(0.2)
entry_bars = input(1, title = "Entry on Nth trend bar") 

atr = atr(atr_length)

atr := na(atr) ? tr : atr

psar        = 0.0 // PSAR
af          = 0.0 // Acceleration Factor
trend_dir   = 0   // Current direction of PSAR
ep          = 0.0 // Extreme point
trend_bars  = 0

sar_long_to_short = trend_dir[1] == 1  and close <= psar[1] // PSAR switches from long to short
sar_short_to_long = trend_dir[1] == -1 and close >= psar[1] // PSAR switches from short to long

trend_change = barstate.isfirst[1] or sar_long_to_short or sar_short_to_long

// Calculate trend direction
trend_dir    :=  barstate.isfirst[1] and close[1]  > open[1] ?  1 : 
                 barstate.isfirst[1] and close[1] <= open[1] ? -1 : 
                 sar_long_to_short ? -1 : 
                 sar_short_to_long ?  1 : nz(trend_dir[1])

trend_bars := sar_long_to_short ? -1 : 
              sar_short_to_long ?  1 : 
              trend_dir ==  1   ? nz(trend_bars[1]) + 1 : 
              trend_dir == -1   ? nz(trend_bars[1]) - 1 : 
              nz(trend_bars[1])

// Calculate  Acceleration Factor
af := trend_change ? start : 
   (trend_dir == 1 and high > ep[1]) or  
   (trend_dir == -1 and low < ep[1]) ? 
   min(maximum, af[1] + increment) : 
   af[1]

// Calculate extreme point
ep := trend_change and trend_dir == 1 ? high :  
   trend_change and trend_dir == -1 ? low : 
   trend_dir == 1 ? max(ep[1], high) : 
   min(ep[1], low)

// Calculate PSAR
psar :=  barstate.isfirst[1] and close[1]  > open[1] ? low[1]  : 
         barstate.isfirst[1] and close[1] <= open[1] ? high[1] : 
         trend_change ? ep[1] :    
         trend_dir == 1 ? psar[1] + af * atr : 
                          psar[1] - af * atr

plot(psar, style=plot.style_cross, color=trend_dir == 1 ? color.green : color.red,  linewidth = 2)


// Strategy 
strategy.entry("Long",  true,  when = trend_bars ==  entry_bars)
strategy.entry("Short", false, when = trend_bars == -entry_bars)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-13. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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