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Strategy vault / Trend following

Super Trend Daily 20 BF

This is my Super Trend Daily strategy but with one important difference. You can now adjust settings for long or short signals individually and separately. For example, the condition for a long signal may require a…

Author
ChaoZhang
Complexity
Intermediate · 172 lines
Parameters
32
Backtest bar
10m · intraday
Tested on
BTC/USDT · futures

This is my Super Trend Daily strategy but with one important difference. You can now adjust settings for long or short signals individually and separately. For example, the condition for a long signal may require a different parameter setting than the condition for a short signal. Each parameter in the signal generation can be tuned. You can also decide what kind of stop loss you want for each side - you could have a fixed stop loss for longs and an ATR derived stop loss for shorts, or whatever.

We also have the option to choose if we want longs, shorts or both.

INISTRUCTIONS Look at the background colors: Green line = long signal Red line = short signal Aqua = No long trades White = No short trades Yellow dotted line = stop loss for long Orange dotted line = stop loss for short

The aqua and white backgrounds mean the conditions are choppy/sideways according to our settings we applied to the rate of change function for a long/short signal respectively. It is possible to get a long signal in a white background, but not a short signal. Similarly, it is possible to get a short signal in an aqua background, but not a long signal.

This is a work in progress so any suggestions for improvements are welcome.

backtest

IMG

Parameters

NameDefaultWhat it controls
v_input_1false════════ Test Period ═══════
v_input_22017Backtest Start Year
v_input_3trueBacktest Start Month
v_input_4trueBacktest Start Day
v_input_52019Backtest Stop Year
v_input_612Backtest Stop Month
v_input_731Backtest Stop Day
v_input_8false═════ Super Trend L ═════
v_input_92ATR Period
v_input_101.5ATR Multiplier
v_input_11false═════ Super Trend S ═════
v_input_123ATR Period
v_input_131.3ATR Multiplier
v_input_14false═════ Rate of Change L ═════
v_input_1530ROC Length
v_input_166ROC % Change
v_input_17false═════ Rate of Change S ═════
v_input_1876ROC Length
v_input_196ROC % Change
v_input_20false═══════ Stop Loss L ══════
v_input_210Stop Loss Type: Fixed | ATR Derived
v_input_225Fixed Stop Loss %
v_input_2320ATR Stop Period
v_input_241.5ATR Stop Multiplier
v_input_25false═══════ Stop Loss S ══════
v_input_260Stop Loss Type: Fixed | ATR Derived
v_input_276Fixed Stop Loss %
v_input_2820ATR Stop Period
v_input_291.5ATR Stop Multiplier
v_input_30false══════ Longs or Shorts ═════
v_input_31trueUse Longs
v_input_32trueUse Shorts

Source Pine Script

/*backtest
start: 2022-04-25 00:00:00
end: 2022-05-24 23:59:00
period: 10m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("Super Trend Daily 2.0 BF ", overlay=true, precision=2, initial_capital=10000, default_qty_type=strategy.percent_of_equity, default_qty_value=100, commission_type=strategy.commission.percent, commission_value=0.075)

/////////////// Time Frame ///////////////
_0 = input(false,  "════════ Test Period ═══════")
testStartYear = input(2017, "Backtest Start Year") 
testStartMonth = input(1, "Backtest Start Month")
testStartDay = input(1, "Backtest Start Day")
testPeriodStart = timestamp(testStartYear,testStartMonth,testStartDay, 0, 0)

testStopYear = input(2019, "Backtest Stop Year")
testStopMonth = input(12, "Backtest Stop Month")
testStopDay = input(31, "Backtest Stop Day")
testPeriodStop = timestamp(testStopYear,testStopMonth,testStopDay, 0, 0)

testPeriod() => true

///////////// Super Trend Long /////////////
_1 = input(false,  "═════ Super Trend L ═════")
lengthl = input(title="ATR Period", type=input.integer, defval=2)
multl = input(title="ATR Multiplier", type=input.float, step=0.1, defval=1.5)

atrl = multl * atr(lengthl)

longStopl = hl2 - atrl
longStopPrevl = nz(longStopl[1], longStopl)
longStopl :=  close[1] > longStopPrevl ? max(longStopl, longStopPrevl) : longStopl

shortStopl = hl2 + atrl
shortStopPrevl = nz(shortStopl[1], shortStopl)
shortStopl := close[1] < shortStopPrevl ? min(shortStopl, shortStopPrevl) : shortStopl

dirl = 1
dirl := nz(dirl[1], dirl)
dirl := dirl == -1 and close > shortStopPrevl ? 1 : dirl == 1 and close < longStopPrevl ? -1 : dirl

///////////// Super Trend Short /////////////
_2 = input(false,  "═════ Super Trend S ═════")
lengths = input(title="ATR Period", type=input.integer, defval=3)
mults = input(title="ATR Multiplier", type=input.float, step=0.1, defval=1.3)

atrs = mults * atr(lengths)

longStops = hl2 - atrs
longStopPrevs = nz(longStops[1], longStops)
longStops :=  close[1] > longStopPrevs ? max(longStops, longStopPrevs) : longStops

shortStops = hl2 + atrs
shortStopPrevs = nz(shortStops[1], shortStops)
shortStops := close[1] < shortStopPrevs ? min(shortStops, shortStopPrevs) : shortStops

dirs = 1
dirs := nz(dirs[1], dirs)
dirs := dirs == -1 and close > shortStopPrevs ? 1 : dirs == 1 and close < longStopPrevs ? -1 : dirs

///////////// Rate Of Change Long ///////////// 
_3 = input(false,  "═════ Rate of Change L ═════")
sourcel = close
roclengthl = input(30, "ROC Length",  minval=1)
pcntChangel = input(6, "ROC % Change", minval=1)
rocl = 100 * (sourcel - sourcel[roclengthl]) / sourcel[roclengthl]
emarocl = ema(rocl, roclengthl / 2)
isMovingl() => emarocl > (pcntChangel / 2) or emarocl < (0 - (pcntChangel / 2))

///////////// Rate Of Change Short ///////////// 
_4 = input(false,  "═════ Rate of Change S ═════")
sources = close
roclengths = input(76, "ROC Length",  minval=1)
pcntChanges = input(6, "ROC % Change", minval=1)
rocs = 100 * (sources - sources[roclengths]) / sources[roclengths]
emarocs = ema(rocs, roclengths / 2)
isMovings() => emarocs > (pcntChanges / 2) or emarocs < (0 - (pcntChanges / 2))

/////////////// Strategy /////////////// 
long = dirl == 1 and dirl[1] == -1 and isMovingl()
short = dirs == -1 and dirs[1] == 1 and isMovings()

last_long = 0.0
last_short = 0.0
last_long := long ? time : nz(last_long[1])
last_short := short ? time : nz(last_short[1])

long_signal = crossover(last_long, last_short)
short_signal = crossover(last_short, last_long)

last_open_long_signal = 0.0
last_open_short_signal = 0.0
last_open_long_signal := long_signal ? open : nz(last_open_long_signal[1])
last_open_short_signal := short_signal ? open : nz(last_open_short_signal[1])

last_long_signal = 0.0
last_short_signal = 0.0
last_long_signal := long_signal ? time : nz(last_long_signal[1])
last_short_signal := short_signal ? time : nz(last_short_signal[1])

in_long_signal = last_long_signal > last_short_signal
in_short_signal = last_short_signal > last_long_signal

last_high = 0.0
last_low = 0.0
last_high := not in_long_signal ? na : in_long_signal and (na(last_high[1]) or high > nz(last_high[1])) ? high : nz(last_high[1])
last_low := not in_short_signal ? na : in_short_signal and (na(last_low[1]) or low < nz(last_low[1])) ? low : nz(last_low[1])

since_longEntry = barssince(last_open_long_signal != last_open_long_signal[1]) 
since_shortEntry = barssince(last_open_short_signal != last_open_short_signal[1]) 

/////////////// Stop Losses Long ///////////////
_5 = input(false,  "═══════ Stop Loss L ══════")
SL_typel = input("Fixed", options=["Fixed", "ATR Derived"], title="Stop Loss Type")
sl_inpl = input(5.0, title='Fixed Stop Loss %') / 100
atrLkbl = input(20, minval=1, title='ATR Stop Period')
atrMultl = input(1.5, step=0.25, title='ATR Stop Multiplier') 
atr1l = atr(atrLkbl)

longStop1l = 0.0
longStop1l :=  short_signal ? na : long_signal ? close - (atr1l * atrMultl) : longStop1l[1]

slLongl = in_long_signal ? strategy.position_avg_price * (1 - sl_inpl) : na
long_sll = in_long_signal ? slLongl : na

/////////////// Stop Losses Short ///////////////
_6 = input(false,  "═══════ Stop Loss S ══════")
SL_types = input("Fixed", options=["Fixed", "ATR Derived"], title="Stop Loss Type")
sl_inps = input(6.0, title='Fixed Stop Loss %') / 100
atrLkbs = input(20, minval=1, title='ATR Stop Period')
atrMults = input(1.5, step=0.25, title='ATR Stop Multiplier') 
atr1s = atr(atrLkbs)

shortStop1s = 0.0
shortStop1s := long_signal ? na : short_signal ? close + (atr1s * atrMults) : shortStop1s[1]

slShorts = strategy.position_avg_price * (1 + sl_inps)
short_sls = in_short_signal ? slShorts : na

_7 = input(false,  "══════ Longs or Shorts ═════")
useLongs = input(true, title="Use Longs")
useShorts = input(true, title="Use Shorts")

/////////////// Execution ///////////////
if testPeriod()
    if useLongs
        strategy.entry("L", strategy.long, when=long)
        strategy.exit("L SL", "L", stop = SL_typel == "Fixed" ? long_sll : longStop1l, when=since_longEntry > 0)
    if useShorts
        strategy.exit("S SL", "S", stop = SL_types == "Fixed" ? short_sls : shortStop1s, when=since_shortEntry > 0)
        strategy.entry("S", strategy.short, when=short)
    if not useShorts
        strategy.close("L", when=short)
    if not useLongs
        strategy.close("S", when=long)

/////////////// Plotting /////////////// 
bgcolor(long_signal ? color.lime : short_signal ? color.red : na, transp=40)
bgcolor(not isMovings() ? color.white : not isMovingl() ? color.aqua : na)
p0 = plot(close, color=color.black)
p1 = plot(strategy.position_size <= 0 ? na : SL_typel == "Fixed" ? long_sll : longStop1l, title="Long Stop Loss", color=color.yellow, style=plot.style_linebr, linewidth=2)
p2 = plot(strategy.position_size >= 0 ? na : SL_types == "Fixed" ? short_sls : shortStop1s, title="Short Stop Loss", color=color.orange, style=plot.style_linebr, linewidth=2)
p3 = plot(strategy.position_size <= 0 ? na : strategy.position_avg_price, style=plot.style_linebr, title="Long Entry", color=color.green, linewidth=2)
p4 = plot(strategy.position_size >= 0 ? na : strategy.position_avg_price, style=plot.style_linebr, title="Short Entry", color=color.red, linewidth=2)
fill(p0, p3, color = color.lime, transp=60)
fill(p0, p4, color = color.red, transp=60)


Published by ChaoZhang on the FMZ strategy square · last modified 2022-05-26. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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