Donchian breakout strategy backtest results

The short answer

Answers here: Do the turtle rules still work? · 20/10 or 55/20? · What is the win rate? · Long only, or both ways?

What the script does

Donchian Breakout Strategy (turtle), from the strategy library.

The numbers, run by run

Net and holding the symbol are after costs over the same period. Held-out is the verdict on the last third of the history judged alone: survived, decayed, did not survive, or too few trades to judge.

Year by year

20-day entry, 10-day exit on SPY, long and short, the same rule long only, and SPY itself, each calendar year after costs. A partial first or last year counts the sessions it has.

Every trade

The 117 trades of 20-day entry, 10-day exit on SPY, long and short, oldest first: side, entry and exit days, fill prices after slippage, and the return after both commissions. The other runs' trades open below.

The script

Pine v6, exactly as it ran for 20-day entry, 10-day exit on SPY, long and short. The variants change only the inputs listed in the table.

//@version=6
strategy("Donchian Breakout Strategy", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=100, initial_capital=100000, commission_type=strategy.commission.percent, commission_value=0.05, slippage=1, margin_long=0, margin_short=0)

entryLen = input.int(20, "Entry channel length", minval=2, group="Setup")
exitLen  = input.int(10, "Exit channel length", minval=1, group="Setup")
trendLen = input.int(0, "Trend filter SMA length (0 = off)", minval=0, group="Setup")
useLong  = input.bool(true, "Trade longs", group="Direction")
useShort = input.bool(true, "Trade shorts", group="Direction")
atrLen   = input.int(14, "ATR length", minval=1, group="Risk")
stopMult = input.float(2, "Stop (ATR multiples)", minval=0, step=0.5, group="Risk")

// channels of the previous bars, so a breakout compares against history
entryHigh = ta.highest(high, entryLen)[1]
entryLow  = ta.lowest(low, entryLen)[1]
exitHigh  = ta.highest(high, exitLen)[1]
exitLow   = ta.lowest(low, exitLen)[1]
atr       = ta.atr(atrLen)
// the trend filter is computed every bar and only consulted when it is on
trendMa   = ta.sma(close, math.max(trendLen, 1))
okLong    = trendLen == 0 or close > trendMa
okShort   = trendLen == 0 or close < trendMa

longSig   = ta.crossover(close, entryHigh) and okLong and barstate.isconfirmed
shortSig  = ta.crossunder(close, entryLow) and okShort and barstate.isconfirmed
exitLong  = ta.crossunder(close, exitLow) and barstate.isconfirmed
exitShort = ta.crossover(close, exitHigh) and barstate.isconfirmed

plot(entryHigh, "Entry high", color=color.new(#16A56A, 0), linewidth=1)
plot(entryLow, "Entry low", color=color.new(#E5484D, 0), linewidth=1)
plot(exitLow, "Exit low", color=color.new(#16A56A, 60), linewidth=1, style=plot.style_stepline)
plot(exitHigh, "Exit high", color=color.new(#E5484D, 60), linewidth=1, style=plot.style_stepline)
plot(trendLen > 0 ? trendMa : na, "Trend filter", color=color.new(#A3A39E, 0), linewidth=1)

if longSig and useLong
    strategy.entry("Long", strategy.long)
    strategy.exit("Long stop", "Long", stop=stopMult > 0 ? close - stopMult * atr : na)
if shortSig and useShort
    strategy.entry("Short", strategy.short)
    strategy.exit("Short stop", "Short", stop=stopMult > 0 ? close + stopMult * atr : na)
if exitLong
    strategy.close("Long")
if exitShort
    strategy.close("Short")

How it was tested

Alpaca daily data since 2016, 0.05% commission and 0.025% slippage on every fill, the last third of the history held out, textbook settings and nothing tuned. The engine, fills and what it does not model are written out once, in data and methodology.

Questions