Qullamaggie Ausbruch V2 Strategie

Schriftsteller:ChaoZhang, Datum: 23.10.2023
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Übersicht

Diese Strategie kombiniert die Vorteile von Breakout- und Trend-following-Trailing-Stop-Strategien, um Support-/Widerstands-Breakout-Signale über längere Zeitrahmen zu erfassen und gleichzeitig gleitende Durchschnitte für Stop-Loss-Trailing zu verwenden, um in Richtung des längerfristigen Trends zu profitieren und gleichzeitig das Risiko zu kontrollieren.

Strategie Logik

  1. Die Strategie berechnet zunächst mehrere gleitende Durchschnitte mit unterschiedlichen Parametern für Trendbestimmung, Support/Resistance und Trailing Stop Loss.

  2. Es identifiziert dann die höchsten Höchst- und tiefsten Tiefpunkte innerhalb eines bestimmten Zeitraums als Support/Resistance Breakout Zonen.

  3. Die Strategie kauft, wenn der Preis über das höchste Hoch und verkauft, wenn der Preis unter das niedrigste Tief bricht.

  4. Nach dem Eintritt wird das niedrigste Tief als anfänglicher Stop-Loss für die Position verwendet.

  5. Sobald die Position profitabel wird, wechselt der Stop-Loss auf den gleitenden Durchschnitt. Wenn der Preis unter den gleitenden Durchschnitt fällt, wird der Stop auf den Tiefpunkt dieser Kerze gesetzt.

  6. Dies ermöglicht es der Position, Gewinne zu erzielen und gleichzeitig genügend Spielraum zu geben, um dem Trend zu folgen.

  7. Die Strategie umfasst auch den durchschnittlichen wahren Bereich für die Filterung, um sicherzustellen, dass nur angemessene Bereichsbrechungen vorgenommen werden, um verlängerte Brechungen zu vermeiden.

Analyse der Vorteile

  1. Kombiniert die Vorteile von Breakout und Trailing Stop Strategien.

  2. Kann Ausbrüche nach langfristigen Trends kaufen, um eine höhere Wahrscheinlichkeit zu erzielen.

  3. Die Strategie des Trailing Stop schützt die Position und lässt genügend Platz zum Laufen.

  4. Die ATR-Filterung verhindert ungünstige längere Ausbrüche.

  5. Automatischer Handel für Teilzeitgeschäfte.

  6. Anpassbare gleitende Durchschnittsparameter.

  7. Flexible Rückhaltesysteme.

Risikoanalyse

  1. Breakout-Strategien sind anfällig für falsche Breakout-Risiken.

  2. Eine ausreichende Volatilität, die notwendig ist, um Signale zu erzeugen, kann in unruhigen Märkten scheitern.

  3. Einige Ausbrüche sind vielleicht zu kurzfristig, um festzuhalten.

  4. Auf verschiedenen Märkten kann es zu häufig sein, dass sich die Haltestellen zu häufig aufhalten.

  5. Die ATR-Filterung kann einige potenzielle Trades verpassen.

Optimierungsrichtlinien

  1. Versuche verschiedene Kombinationen von gleitenden Durchschnitten für optimale Parameter.

  2. Erforschen Sie verschiedene Breakout-Bestätigungen wie Kanäle, Kerzenmuster usw.

  3. Versuchen Sie verschiedene Trailing-Stop-Mechanismen, um den besten Stop-Loss zu finden.

  4. Optimieren Sie Geldmanagement-Strategien wie Position Score.

  5. Hinzufügen von Filtern für technische Indikatoren zur Verbesserung der Signalqualität.

  6. Testen Sie die Wirksamkeit verschiedener Produkte.

  7. Einbeziehung von Algorithmen für maschinelles Lernen zur Steigerung der Strategieleistung.

Schlussfolgerung

Diese Strategie kombiniert die Philosophien der Breakout- und Trend-Following-Trailing-Stop-Strategien. Mit einer ordnungsgemäßen Trendbestimmung optimiert sie das Gewinnpotenzial bei gleichzeitiger Aufrechterhaltung eines kontrollierten Risikos. Die Schlüssel sind die Suche nach den optimalen Parameter-Sätzen und die Einbeziehung eines umsichtigen Geldmanagements. Weitere Verbesserungen können dies in eine robuste Trendfollowing-Methode verwandeln.


/*backtest
start: 2022-10-17 00:00:00
end: 2023-10-23 00:00:00
period: 1d
basePeriod: 1h
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/
// © millerrh

// The intent of this strategy is to buy breakouts with a tight stop on smaller timeframes in the direction of the longer term trend.
// Then use a trailing stop of a close below either the 10 MA or 20 MA (user choice) on that larger timeframe as the position 
// moves in your favor (i.e. whenever position price rises above the MA).
// Option of using daily ADR as a measure of finding contracting ranges and ensuring a decent risk/reward.
// (If the difference between the breakout point and your stop level is below a certain % of ATR, it could possibly find those consolidating periods.)
// V2 - updates code of original Qullamaggie Breakout to optimize and debug it a bit - the goal is to remove some of the whipsaw and poor win rate of the 
// original by incorporating some of what I learned in the Breakout Trend Follower script.

//@version=4
strategy("Qullamaggie Breakout V2", overlay=true, initial_capital=100000, currency='USD', calc_on_every_tick = true,
   default_qty_type=strategy.percent_of_equity, default_qty_value=100, commission_type=strategy.commission.percent, commission_value=0.1)
   
// === BACKTEST RANGE ===
Start = input(defval = timestamp("01 Jan 2019 06:00 +0000"), title = "Backtest Start Date", type = input.time, group = "backtest window and pivot history")
Finish = input(defval = timestamp("01 Jan 2100 00:00 +0000"), title = "Backtest End Date", type = input.time, group = "backtest window and pivot history")

// Inputs
showPivotPoints = input(title = "Show Historical Pivot Points?", type = input.bool, defval = false, group = "backtest window and pivot history",
  tooltip = "Toggle this on to see the historical pivot points that were used.  Change the Lookback Periods to adjust the frequency of these points.")
htf = input(defval="D", title="Timeframe of Moving Averages", type=input.resolution, group = "moving averages",
  tooltip = "Allows you to set a different time frame for the moving averages and your trailing stop.
  The default behavior is to identify good tightening setups on a larger timeframe
  (like daily) and enter the trade on a breakout occuring on a smaller timeframe, using the moving averages of the larger timeframe to trail your stop.")
maType = input(defval="SMA", options=["EMA", "SMA"], title = "Moving Average Type", group = "moving averages")
ma1Length = input(defval = 10, title = "1st Moving Average Length", minval = 1, group = "moving averages")
ma2Length = input(defval = 20, title = "2nd Moving Average Length", minval = 1, group = "moving averages")
ma3Length = input(defval = 50, title = "3rd Moving Average Length", minval = 1, group = "moving averages")
useMaFilter = input(title = "Use 3rd Moving Average for Filtering?", type = input.bool, defval = true, group = "moving averages",
  tooltip = "Signals will be ignored when price is under this slowest moving average.  The intent is to keep you out of bear periods and only
             buying when price is showing strength or trading with the longer term trend.")
trailMaInput = input(defval="1st Moving Average", options=["1st Moving Average", "2nd Moving Average"], title = "Trailing Stop", group = "stops",
  tooltip = "Initial stops after entry follow the range lows.  Once in profit, the trade gets more wiggle room and
  stops will be trailed when price breaches this moving average.")
trailMaTF = input(defval="Same as Moving Averages", options=["Same as Moving Averages", "Same as Chart"], title = "Trailing Stop Timeframe", group = "stops",
  tooltip = "Once price breaches the trail stop moving average, the stop will be raised to the low of that candle that breached. You can choose to use the
  chart timeframe's candles breaching or use the same timeframe the moving averages use. (i.e. if daily, you wait for the daily bar to close before setting
  your new stop level.)")
currentColorS = input(color.new(color.orange,50), title = "Current Range S/R Colors:    Support", type = input.color, group = "stops", inline = "lineColor")
currentColorR = input(color.new(color.blue,50), title = " Resistance", type = input.color, group = "stops", inline = "lineColor")

// Pivot lookback
lbHigh = 3
lbLow = 3

// MA Calculations (can likely move this to a tuple for a single security call!!)
ma(maType, src, length) =>
    maType == "EMA" ? ema(src, length) : sma(src, length) //Ternary Operator (if maType equals EMA, then do ema calc, else do sma calc)
ma1 = security(syminfo.tickerid, htf, ma(maType, close, ma1Length))
ma2 = security(syminfo.tickerid, htf, ma(maType, close, ma2Length))
ma3 = security(syminfo.tickerid, htf, ma(maType, close, ma3Length))

plot(ma1, color=color.new(color.purple, 60), style=plot.style_line, title="MA1", linewidth=2)
plot(ma2, color=color.new(color.yellow, 60), style=plot.style_line, title="MA2", linewidth=2)
plot(ma3, color=color.new(color.white, 60), style=plot.style_line, title="MA3", linewidth=2)

// === USE ADR FOR FILTERING ===
// The idea here is that you want to buy in a consolodating range for best risk/reward. So here you can compare the current distance between 
// support/resistance vs. the ADR and make sure you aren't buying at a point that is too extended.
useAdrFilter = input(title = "Use ADR for Filtering?", type = input.bool, defval = false, group = "adr filtering",
  tooltip = "Signals will be ignored if the distance between support and resistance is larger than a user-defined percentage of ADR (or monthly volatility
  in the stock screener). This allows the user to ensure they are not buying something that is too extended and instead focus on names that are consolidating more.")
adrPerc = input(defval = 120, title = "% of ADR Value", minval = 1, group = "adr filtering")
tableLocation = input(defval="Bottom", options=["Top", "Bottom"], title = "ADR Table Visibility", group = "adr filtering",
  tooltip = "Place ADR table on the top of the pane, the bottom of the pane, or off.")
adrValue = security(syminfo.tickerid, "D", sma((high-low)/abs(low) * 100, 21)) // Monthly Volatility in Stock Screener (also ADR)
adrCompare = (adrPerc * adrValue) / 100

// === PLOT SWING HIGH/LOW AND MOST RECENT LOW TO USE AS STOP LOSS EXIT POINT ===
ph = pivothigh(high, lbHigh, lbHigh)
pl = pivotlow(low, lbLow, lbLow)
highLevel = valuewhen(ph, high[lbHigh], 0)
lowLevel = valuewhen(pl, low[lbLow], 0)
barsSinceHigh = barssince(ph) + lbHigh
barsSinceLow = barssince(pl) + lbLow
timeSinceHigh = time[barsSinceHigh]
timeSinceLow = time[barsSinceLow]

//Removes color when there is a change to ensure only the levels are shown (i.e. no diagonal lines connecting the levels)
pvthis = fixnan(ph)
pvtlos = fixnan(pl)
hipc = change(pvthis) != 0 ? na : color.new(color.maroon, 0)
lopc = change(pvtlos) != 0 ? na : color.new(color.green, 0)

// Display Pivot lines
plot(showPivotPoints ? pvthis : na, color=hipc, linewidth=1, offset=-lbHigh, title="Top Levels")
plot(showPivotPoints ? pvthis : na, color=hipc, linewidth=1, offset=0, title="Top Levels 2")
plot(showPivotPoints ? pvtlos : na, color=lopc, linewidth=1, offset=-lbLow, title="Bottom Levels")
plot(showPivotPoints ? pvtlos : na, color=lopc, linewidth=1, offset=0, title="Bottom Levels 2")

// BUY AND SELL CONDITIONS
buyLevel = valuewhen(ph, high[lbHigh], 0) //Buy level at Swing High

// Conditions for entry
stopLevel = float(na) // Define stop level here as "na" so that I can reference it in the ADR calculation before the stopLevel is actually defined.
buyConditions = (useMaFilter ? buyLevel > ma3 : true) and
  (useAdrFilter ? (buyLevel - stopLevel[1]) < adrCompare : true) 
buySignal = crossover(high, buyLevel) and buyConditions

// Trailing stop points - when price punctures the moving average, move stop to the low of that candle - Define as function/tuple to only use one security call
trailMa = trailMaInput == "1st Moving Average" ? ma1 : ma2
f_getCross() =>
    maCrossEvent = crossunder(low, trailMa)
    maCross = valuewhen(maCrossEvent, low, 0)
    maCrossLevel = fixnan(maCross)
    maCrossPc = change(maCrossLevel) != 0 ? na : color.new(color.blue, 0) //Removes color when there is a change to ensure only the levels are shown (i.e. no diagonal lines connecting the levels)
    [maCrossEvent, maCross, maCrossLevel, maCrossPc]
crossTF = trailMaTF == "Same as Moving Averages" ? htf : ""
[maCrossEvent, maCross, maCrossLevel, maCrossPc] = security(syminfo.tickerid, crossTF, f_getCross())

plot(showPivotPoints ? maCrossLevel : na, color = maCrossPc, linewidth=1, offset=0, title="Ma Stop Levels")

// == STOP AND PRICE LEVELS ==
inPosition = strategy.position_size > 0
buyLevel := inPosition ? buyLevel[1] : buyLevel
stopDefine = valuewhen(pl, low[lbLow], 0) //Stop Level at Swing Low
inProfit = strategy.position_avg_price <= stopDefine[1]
// stopLevel := inPosition ? stopLevel[1] : stopDefine // Set stop loss based on swing low and leave it there
stopLevel := inPosition and not inProfit ? stopDefine : inPosition and inProfit ? stopLevel[1] : stopDefine // Trail stop loss until in profit
trailStopLevel = float(na)

// trying to figure out a better way for waiting on the trail stop - it can trigger if above the stopLevel even if the MA hadn't been breached since opening the trade
notInPosition = strategy.position_size == 0
inPositionBars = barssince(notInPosition)
maCrossBars = barssince(maCrossEvent)
trailCross = inPositionBars > maCrossBars
// trailCross = trailMa > stopLevel
trailStopLevel := inPosition and trailCross ? maCrossLevel : na

plot(inPosition ? stopLevel : na, style=plot.style_linebr, color=color.new(color.orange, 50), linewidth = 2, title = "Historical Stop Levels", trackprice=false)
plot(inPosition ? trailStopLevel : na, style=plot.style_linebr, color=color.new(color.blue, 50), linewidth = 2, title = "Historical Trail Stop Levels", trackprice=false)

// == PLOT SUPPORT/RESISTANCE LINES FOR CURRENT CHART TIMEFRAME ==
// Use a function to define the lines
// f_line(x1, y1, y2, _color) =>
//     var line id = na
//     line.delete(id)
//     id := line.new(x1, y1, time, y2, xloc.bar_time, extend.right, _color)

// highLine = f_line(timeSinceHigh, highLevel, highLevel, currentColorR)
// lowLine = f_line(timeSinceLow, lowLevel, lowLevel, currentColorS)


// == ADR TABLE ==
tablePos = tableLocation == "Top" ? position.top_right : position.bottom_right
var table adrTable = table.new(tablePos, 2, 1, border_width = 3)
lightTransp = 90
avgTransp   = 80
heavyTransp = 70
posColor = color.rgb(38, 166, 154)
negColor = color.rgb(240, 83, 80)
volColor = color.new(#999999, 0)

f_fillCellVol(_table, _column, _row, _value) =>
    _transp = abs(_value) > 7 ? heavyTransp : abs(_value) > 4 ? avgTransp : lightTransp
    _cellText = tostring(_value, "0.00") + "%\n" + "ADR"
    table.cell(_table, _column, _row, _cellText, bgcolor = color.new(volColor, _transp), text_color = volColor, width = 6)

srDistance = (highLevel - lowLevel)/highLevel * 100

f_fillCellCalc(_table, _column, _row, _value) =>
    _c_color = _value >= adrCompare ? negColor : posColor
    _transp = _value >= adrCompare*0.8 and _value <= adrCompare*1.2 ? lightTransp : 
      _value >= adrCompare*0.5 and _value < adrCompare*0.8 ? avgTransp :
      _value < adrCompare*0.5 ? heavyTransp :
      _value > adrCompare*1.2 and _value <= adrCompare*1.5 ? avgTransp :
      _value > adrCompare*1.5 ? heavyTransp : na
    _cellText = tostring(_value, "0.00") + "%\n" + "Range"
    table.cell(_table, _column, _row, _cellText, bgcolor = color.new(_c_color, _transp), text_color = _c_color, width = 6)

if barstate.islast
    f_fillCellVol(adrTable, 0, 0, adrValue)
    f_fillCellCalc(adrTable, 1, 0, srDistance)
    // f_fillCellVol(adrTable, 0, 0, inPositionBars)
    // f_fillCellCalc(adrTable, 1, 0, maCrossBars)

// == STRATEGY ENTRY AND EXIT ==
strategy.entry("Buy", strategy.long, stop = buyLevel, when = buyConditions)

stop = stopLevel > trailStopLevel ? stopLevel : close[1] > trailStopLevel and close[1] > trailMa ? trailStopLevel : stopLevel
strategy.exit("Sell", from_entry = "Buy", stop=stop)



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