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Strategy vault / Trend following

Smoothed Heikin Ashi Trend Following Strategy

This strategy identifies price trends using a custom smoothed oscillator indicator and trades based on trend following principles. It goes long when price breaks above the indicator line and goes short when price…

Author
ChaoZhang
Complexity
Intermediate · 126 lines
Parameters
9
Backtest bar
10m · intraday
Tested on
BTC/USDT · futures

IMG

Overview

This strategy identifies price trends using a custom smoothed oscillator indicator and trades based on trend following principles. It goes long when price breaks above the indicator line and goes short when price breaks below the line.

Strategy Logic

The strategy employs a custom smoothed oscillator that computes the reverse close price required to flip the Heikin Ashi candle color from red to green and vice versa. This reverse close is then smoothed using moving averages to obtain the final oscillator line. Price trading above (below) the line signals an uptrend (downtrend).

The strategy enters trades based on breakouts of the indicator line. Long trades are initiated when price breaks above the line while short trades are initiated on breakdowns below the line. Stop losses are set at a fixed percentage from the entry price to lock in profits and control risk.

Advantages

  1. Custom indicator identifies trends with good backtest results
  2. Trend following approach aligns with quantitative theories
  3. Stop loss implementation promotes risk management

Risks

  1. Potential for repainting leading to poor live performance
  2. Reliance on a single indicator risks bad signals
  3. Stop loss setting requires further optimization

Enhancement Opportunities

  1. Incorporate additional filters like Bollinger Bands, RSI etc.
  2. Test different indicator parameters
  3. Optimize stop loss placement
  4. More testing across instruments and timeframes

Conclusion

The strategy demonstrates a clear trend following approach using a custom oscillator indicator. Backtest results are encouraging, indicating potential for live trading. However sole dependence on one repainting indicator and lack of signal quality verification are concerns. Stop loss mechanics also require additional testing and tuning. Overall the strategy concept looks feasible but more work is needed to make it reliably deployable for live trading.

Parameters

NameDefaultWhat it controls
v_input_1trueUse smoothing Heikin Ashi
v_input_string_10Method: SMA | EMA | HMA | VWMA | RMA
v_input_210Smoothing period
v_input_3trueShow Info Box
v_input_42Prices Decimal Places
v_input_55Info Box Offset
v_input_6falseRepaint - Keep on for live / Off for backtest
v_input_float_1trueLong Stop Loss (%)
v_input_float_2trueShort Stop Loss (%)

Source Pine Script

/*backtest
start: 2023-12-19 00:00:00
end: 2023-12-26 00:00:00
period: 10m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/

// © TraderHalai
// This is a backtest of the Smoothed Heikin Ashi Trend indicator, which computes the reverse candle close price required to flip a heikin ashi trend from red to green and vice versa. Original indicator can be found on the scripts section of my profile.

// Default testing parameters are 10% of equity position size, with a 1% stop loss on short and long strategy.opentrades.commission

// This particular back test uses this indicator as a Trend trading tool with a tight stop loss. The equity curve as tested seems promising but requires further work to refine. Note in an actual trading setup, you may wish to use this with volatilty filters as most of the losses are in sideways, low volatility markets.


//@version=5
strategy("Smoothed Heikin Ashi Trend on Chart - TraderHalai BACKTEST", " SHA Trend - BACKTEST", overlay=true)
//Inputs

i_useSmooth =       input ( true, "Use smoothing Heikin Ashi")
i_smoothingMethod = input.string("SMA", "Method", options=["SMA", "EMA", "HMA", "VWMA", "RMA"])
i_smoothingPeriod = input ( 10, "Smoothing period")

i_infoBox   =       input ( true, "Show Info Box"        )
i_decimalP  =       input ( 2,    "Prices Decimal Places") 
i_boxOffSet =       input ( 5,    "Info Box Offset"      )
i_repaint   =       input (false,  "Repaint -  Keep on for live / Off for backtest")

i_longLossPerc = input.float(title="Long Stop Loss (%)",minval=0.0, step=0.1, defval=1) * 0.01

i_shortLossPerc = input.float(title="Short Stop Loss (%)", minval=0.0, step=0.1, defval=1) * 0.01


timeperiod = timeframe.period

//Security functions to avoid repaint, as per PineCoders
f_secureSecurity(_symbol, _res, _src) => request.security(_symbol, _res, _src[1], lookahead = barmerge.lookahead_on)
f_security(_symbol, _res, _src, _repaint) => request.security(_symbol, _res, _src[_repaint ? 0 : barstate.isrealtime ? 1 : 0])[_repaint ? 0 : barstate.isrealtime ? 0 : 1]
f_secSecurity2(_symbol, _res, _src) => request.security(_symbol, _res, _src[1])


candleClose = f_security(syminfo.tickerid, timeperiod, close, i_repaint)
candleOpen = f_security(syminfo.tickerid, timeperiod, open, i_repaint)
candleLow = f_security(syminfo.tickerid, timeperiod, low, i_repaint)
candleHigh = f_security(syminfo.tickerid, timeperiod, high, i_repaint)

haTicker = ticker.heikinashi(syminfo.tickerid)
haClose = f_security(haTicker, timeperiod, close, i_repaint)
haOpen = f_security(haTicker, timeperiod, open, i_repaint)
haLow = f_security(haTicker, timeperiod, low, i_repaint)
haHigh= f_security(haTicker, timeperiod, high, i_repaint)


reverseClose = (2 * (haOpen[1] + haClose[1])) - candleHigh - candleLow - candleOpen

if(reverseClose < candleLow)
    reverseClose := (candleLow + reverseClose) / 2

if(reverseClose > candleHigh)
    reverseClose := (candleHigh + reverseClose) / 2
    
//Smoothing
    
smaSmoothed = ta.sma(reverseClose, i_smoothingPeriod)
emaSmoothed = ta.ema(reverseClose, i_smoothingPeriod)
hmaSmoothed = ta.hma(reverseClose, i_smoothingPeriod)
vwmaSmoothed = ta.vwma(reverseClose, i_smoothingPeriod)
rmaSmoothed = ta.rma(reverseClose, i_smoothingPeriod)

shouldApplySmoothing = i_useSmooth and i_smoothingPeriod > 1 

smoothedReverseClose = reverseClose

if(shouldApplySmoothing)
    if(i_smoothingMethod == "SMA")
        smoothedReverseClose := smaSmoothed
    else if(i_smoothingMethod == "EMA")
        smoothedReverseClose := emaSmoothed
    else if(i_smoothingMethod == "HMA")
        smoothedReverseClose := hmaSmoothed
    else if(i_smoothingMethod == "VWMA")
        smoothedReverseClose := vwmaSmoothed
    else if(i_smoothingMethod == "RMA")
        smoothedReverseClose := rmaSmoothed
    else 
        smoothedReverseClose := reverseClose // Default to non-smoothed for invalid smoothing type
    
haBull = candleClose >= smoothedReverseClose
haCol = haBull ? color.green : color.red


//Overall trading strategy
if(ta.crossover(candleClose, smoothedReverseClose))
    strategy.entry("LONG", strategy.long, stop=smoothedReverseClose)
else
    strategy.cancel("LONG")

if(ta.crossunder(candleClose, smoothedReverseClose))
    strategy.entry("SHORT", strategy.short, stop=smoothedReverseClose)
else
    strategy.cancel("SHORT")
    

longStopPrice  = strategy.position_avg_price * (1 - i_longLossPerc)
shortStopPrice = strategy.position_avg_price * (1 + i_shortLossPerc)



plot(series=(strategy.position_size > 0) ? longStopPrice : na,
     color=color.red, style=plot.style_cross,
     linewidth=2, title="Long Stop Loss")
plot(series=(strategy.position_size < 0) ? shortStopPrice : na,
     color=color.red, style=plot.style_cross,
     linewidth=2, title="Short Stop Loss")
     
plot(smoothedReverseClose, color=haCol)

if (strategy.position_size > 0)
    strategy.exit(id="XL STP", stop=longStopPrice)

if (strategy.position_size < 0)
    strategy.exit(id="XS STP", stop=shortStopPrice)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-27. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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