Quantifizierte schrittweise gewichtete DCA-Handelsstrategie

Schriftsteller:ChaoZhang, Datum: 2023-11-16 11:32:12
Tags:

Übersicht

Die Quantized Gradual Weighted DCA Trading Strategy ist eine quantitative Handelsstrategie, die gleitende Durchschnittsindikatoren für das Auslösen von Signalen und schrittweise gewichtete Dollar-Kostendurchschnittsmechanismen kombiniert.

Grundsätze

Die Strategie besteht aus drei Hauptbestandteilen:

Beurteilung des Eingangssignals

Es verwendet schnelle und langsame gleitende Durchschnittskreuzungen als Einstiegssignal. Benutzer können zwischen SMA, EMA oder HMA für die schnellen und langsamen gleitenden Durchschnitte wählen. Wenn der schnelle MA über den langsamen MA überschreitet, wird ein Kaufsignal generiert. Wenn der schnelle MA unter dem langsamen MA überschreitet, wird ein Verkaufssignal generiert.
Graduell gewichtete DCA

Nach einem Kaufsignal wird die Strategie sofort eine Basisposition eröffnen. Da der Preis weiter sinkt, wird die Strategie die Größe zusätzlicher Sicherheitspositionen schrittweise gewichtet erhöhen. Der Preis jeder neuen Sicherheitsposition wird um einen festen Prozentsatz gegenüber der vorherigen gesenkt. Außerdem werden die für jede neue Sicherheitsposition zugewiesenen Mittel um einen Faktor vergrößert.

Diese allmähliche Erhöhung der Positionsgröße ermöglicht eine Form der Kostendurchschnittsbildung, die eine bessere Durchschnittskostenquote bei gleichzeitiger Kontrolle der Risiken ermöglicht.
Gewinn und Stop-Loss

Wenn der Preis über die Take-Profit-Linie steigt, schließt die Strategie Positionen zum Gewinn. Wenn der Preis unter die Stop-Loss-Linie fällt, tritt die Strategie aus, um den Verlust zu kontrollieren.

Die Gewinngrenze wird zum Durchschnittspreis der Basisposition * (1 + fester Prozentsatz) festgesetzt.

Die Stop-Loss-Linie schwankt basierend auf dem Preis der letzten Sicherheitsposition, festes Prozent darunter.

Vorteile

Durch die Kombination von Trend und Kostendurchschnitt wird es stabiler

Die Verwendung von Trends vermeidet sinnlose Schlagzeilen, und die Kostendurchschnittswerte liefern bessere Einstiegskosten.
Graduelle Positionsdimensionierung steuert das Risiko

Eine feste Verstärkung der Größen der Sicherheitspositionen mit Rücktrittsschwelle hält das Risiko in Schach.
Echtzeitüberwachung der verwendeten Mittel

Der integrierte Indikator für die Bilanznutzung verhindert eine übermäßige Verschuldung und Zwangsliquidationen.
Für jede Position getrennte TP/SL

Unabhängige Ausgänge ermöglichen es, Gewinne zu sichern und Verluste zu reduzieren.

Risiken und Verbesserungen

Preisschwankungen können mehrere Sicherheitsbestellungen auslösen

Bei extremer Volatilität können mehrere unnötige Sicherheitsbestellungen hinzugefügt werden, wodurch der Verlust steigt.
Bewegliche Durchschnittsparameter müssen optimiert werden

Verschiedene Instrumente benötigen unterschiedliche gleitende Durchschnittsperioden.
TP/SL-Werte müssen im Rücktest optimiert werden

Die TP/SL-Verhältnisse bestimmen das Risiko/Rendite-Profil.
Hinzufügen von maximaler Auslastung oder Haltedauer basierend auf Zwangsausgang

Kann die Einbeziehung von Zwangsausgängen basierend auf der Abzugszeit oder der Haltzeit testen, um die Risiken weiter zu begrenzen.

Zusammenfassung

Die Quantized Gradual Weighted DCA Trading Strategy kombiniert die Vorteile des Trendhandels und der Kostendurchschnittsrechnung, um bei starken Trends eine stetige Rendite zu erzielen. Mit optimierten Parametern, Positionsgrößen und Wiedereintrittsschwellen kann sie stabile Trades mit kontrolliertem Risiko erzielen. Anwendbar für Hedgefonds, CTAs und marktneutrale Strategien.

/*backtest
start: 2022-11-09 00:00:00
end: 2023-11-15 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/
// © MGTG

//@version=5
Strategy = input.string('Long', options=['Long'], group='Strategy', inline='1',
 tooltip='Long bots profit when asset prices rise, Short bots profit when asset prices fall'
 + '\n\n' + 'Please note: to run a Short bot on a spot exchange account, you need to own the asset you want to trade. The bot will sell the asset at the current chart price and buy it back at a lower price - the profit made is actually trapped equity released from an asset you own that is declining in value.')

Profit_currency = input.string('Quote (USDT)', 'Profit currency', options=['Quote (USDT)', 'Quote (BTC)', 'Quote (BUSD)'], group='Strategy', inline='1')
Base_order_size = input.int(10, 'Base order Size', group='Strategy', inline='2', 
 tooltip='The Base Order is the first order the bot will create when starting a new deal.')
Safety_order_size = input.int(20, 'Safety order Size', group='Strategy', inline='2',
 tooltip="Enter the amount of funds your Safety Orders will use to Average the cost of the asset being traded, this can help your bot to close deals faster with more profit. Safety Orders are also known as Dollar Cost Averaging and help when prices moves in the opposite direction to your bot's take profit target.")

Triger_Type = input.string('Over', 'Entry at Cross Over / Under', options=['Over', 'Under'], group='Deal start condition > Trading View custom signal', inline='1',
 tooltip='Deal start condition decision')

Short_Moving_Average  = input.string('SMA', 'Short Moving Average', group='Deal start condition > Trading View custom signal', inline='2',
 options=["SMA", "EMA", "HMA"])
Short_Period         = input.int(5, 'Period', group='Deal start condition > Trading View custom signal', inline='2')
Long_Moving_Average  = input.string('HMA', 'Long Moving Average', group='Deal start condition > Trading View custom signal', inline='3',
 options=["SMA", "EMA", "HMA"])

Long_Period          = input.int(50, 'Period', group='Deal start condition > Trading View custom signal', inline='3')

Target_profit = input.float(1.5, 'Target profit (%)', step=0.05, group='Take profit / Stop Loss', inline='1') * 0.01
Stop_Loss = input.int(15, 'Stop Loss (%)', group='Take profit / Stop Loss', inline='1',
 tooltip='This is the percentage that price needs to move in the opposite direction to your take profit target, at which point the bot will execute a Market Order on the exchange account to close the deal for a smaller loss than keeping the deal open.'
 + '\n' + 'Please note, the Stop Loss is calculated from the price the Safety Order at on the exchange account and not the Dollar Cost Average price.') * 0.01

Max_safety_trades_count = input.int(10, 'Max safety trades count', maxval=10, group='Safety orders', inline='1')
Price_deviation = input.float(0.4, 'Price deviation to open safety orders (% from initial order)', step=0.01, group='Safety orders', inline='2') * 0.01
Safety_order_volume_scale = input.float(1.8, 'Safety order volume scale', step=0.01, group='Safety orders', inline='3')
Safety_order_step_scale = input.float(1.19, 'Safety order step scale', step=0.01, group='Safety orders', inline='3')

// daily_volume  = input.int(500, "Don't start deal(s) if the daily volume is less than", group='Advanced settings', inline='1')
// Minimum_price  = input.int(500, "Minimum price to open deal", group='Advanced settings', inline='1')
// Maximum_price  = input.int(500, "Maximum price to open deal", group='Advanced settings', inline='1')

// Close_deal_after_timeout  = input.int(5, "Close deal after timeout (Hrs)", group='Advanced settings', inline='1')

initial_capital = 8913

strategy(
 title='3Commas Visible DCA Strategy', 
 overlay=true, 
 initial_capital=initial_capital, 
 pyramiding=11, 
 process_orders_on_close=true, 
 commission_type=strategy.commission.percent, 
 commission_value=0.01, 
 max_bars_back=5000, 
 max_labels_count=50)


// Position
status_none  = strategy.position_size == 0
status_long  = strategy.position_size[1] == 0 and strategy.position_size > 0
status_long_offset  = strategy.position_size[2] == 0 and strategy.position_size[1] > 0
status_short = strategy.position_size[1] == 0 and strategy.position_size < 0
status_increase = strategy.opentrades[1] < strategy.opentrades

Short_Moving_Average_Line = 
 Short_Moving_Average == 'SMA' ? ta.sma(close, Short_Period) :
 Short_Moving_Average == 'EMA' ? ta.ema(close, Short_Period) :
 Short_Moving_Average == 'HMA' ? ta.sma(close, Short_Period) : na

Long_Moving_Average_Line = 
 Long_Moving_Average == 'SMA' ? ta.sma(close, Long_Period) :
 Long_Moving_Average == 'EMA' ? ta.ema(close, Long_Period) :
 Long_Moving_Average == 'HMA' ? ta.sma(close, Long_Period) : na
 
Base_order_Condition      = Triger_Type == "Over" ? ta.crossover(Short_Moving_Average_Line, Long_Moving_Average_Line) : ta.crossunder(Short_Moving_Average_Line, Long_Moving_Average_Line) // Buy when close crossing lower band

safety_order_deviation(index) => Price_deviation * math.pow(Safety_order_step_scale,  index - 1)

pd = Price_deviation
ss = Safety_order_step_scale

step(i) =>
 i == 1 ? pd :
 i == 2 ? pd + pd * ss :
 i == 3 ? pd + (pd + pd * ss) * ss :
 i == 4 ? pd + (pd + (pd + pd * ss) * ss) * ss : 
 i == 5 ? pd + (pd + (pd + (pd + pd * ss) * ss) * ss) * ss : 
 i == 6 ? pd + (pd + (pd + (pd + (pd + pd * ss) * ss) * ss) * ss) * ss : 
 i == 7 ? pd + (pd + (pd + (pd + (pd + (pd + pd * ss) * ss) * ss) * ss) * ss) * ss : 
 i == 8 ? pd + (pd + (pd + (pd + (pd + (pd + (pd + pd * ss) * ss) * ss) * ss) * ss) * ss) * ss : 
 i == 9 ? pd + (pd + (pd + (pd + (pd + (pd + (pd + (pd + pd * ss) * ss) * ss) * ss) * ss) * ss) * ss) * ss : 
 i == 10 ? pd + (pd + (pd + (pd + (pd + (pd + (pd + (pd + (pd + pd * ss) * ss) * ss) * ss) * ss) * ss) * ss) * ss) * ss : na

long_line(i) =>
 close[1] - close[1] * (step(i))


Safe_order_line(i) =>
 i == 0 ? ta.valuewhen(status_long, long_line(0), 0) :
 i == 1 ? ta.valuewhen(status_long, long_line(1), 0) :
 i == 2 ? ta.valuewhen(status_long, long_line(2), 0) :
 i == 3 ? ta.valuewhen(status_long, long_line(3), 0) :
 i == 4 ? ta.valuewhen(status_long, long_line(4), 0) :
 i == 5 ? ta.valuewhen(status_long, long_line(5), 0) :
 i == 6 ? ta.valuewhen(status_long, long_line(6), 0) :
 i == 7 ? ta.valuewhen(status_long, long_line(7), 0) :
 i == 8 ? ta.valuewhen(status_long, long_line(8), 0) : 
 i == 9 ? ta.valuewhen(status_long, long_line(9), 0) :
 i == 10 ? ta.valuewhen(status_long, long_line(10), 0) : na

TP_line = strategy.position_avg_price * (1 + Target_profit) 

SL_line = Safe_order_line(Max_safety_trades_count) * (1 - Stop_Loss)

safety_order_size(i) => Safety_order_size * math.pow(Safety_order_volume_scale, i - 1)


plot(Short_Moving_Average_Line, 'Short MA', color=color.new(color.white, 0), style=plot.style_line)
plot(Long_Moving_Average_Line, 'Long MA', color=color.new(color.green, 0), style=plot.style_line)
plot(strategy.position_size > 0 and Max_safety_trades_count >= 1 ? Safe_order_line(1) : na, 'Safety order1', color=color.new(#009688, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 and Max_safety_trades_count >= 2 ? Safe_order_line(2) : na, 'Safety order2', color=color.new(#009688, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 and Max_safety_trades_count >= 3 ? Safe_order_line(3) : na, 'Safety order3', color=color.new(#009688, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 and Max_safety_trades_count >= 4 ? Safe_order_line(4) : na, 'Safety order4', color=color.new(#009688, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 and Max_safety_trades_count >= 5 ? Safe_order_line(5) : na, 'Safety order5', color=color.new(#009688, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 and Max_safety_trades_count >= 6 ? Safe_order_line(6) : na, 'Safety order6', color=color.new(#009688, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 and Max_safety_trades_count >= 7 ? Safe_order_line(7) : na, 'Safety order7', color=color.new(#009688, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 and Max_safety_trades_count >= 8 ? Safe_order_line(8) : na, 'Safety order8', color=color.new(#009688, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 and Max_safety_trades_count >= 9 ? Safe_order_line(9) : na, 'Safety order9', color=color.new(#009688, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 and Max_safety_trades_count >= 10 ? Safe_order_line(10) : na, 'Safety order10', color=color.new(#009688, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 ? TP_line : na, 'Take Profit', color=color.new(color.orange, 0), style=plot.style_linebr)
plot(strategy.position_size > 0 ? SL_line : na, 'Safety', color=color.new(color.aqua, 0), style=plot.style_linebr)


currency = 
 Profit_currency == 'Quote (USDT)' ? ' USDT' :
 Profit_currency == 'Quote (BTC)'  ? ' BTC' :
 Profit_currency == 'Quote (BUSD)' ? ' BUSD' : na
 

if Base_order_Condition
    strategy.entry('Base order', strategy.long, qty=Base_order_size/close, when=Base_order_Condition and strategy.opentrades == 0,
     comment='BO' + ' - ' + str.tostring(Base_order_size) + str.tostring(currency))

for i = 1 to Max_safety_trades_count by 1
    i_s = str.tostring(i)
    strategy.entry('Safety order' + i_s, strategy.long, qty=safety_order_size(i)/close,
     limit=Safe_order_line(i), when=(strategy.opentrades <= i) and strategy.position_size > 0, 
     comment='SO' + i_s + ' - ' + str.tostring(safety_order_size(i))  + str.tostring(currency))


for i = 1 to Max_safety_trades_count by 1
    i_s = str.tostring(i)
    // strategy.close('Base order', when=shortCondition)
    // strategy.close('Safety order' + i_s, when=shortCondition)
    // strategy.cancel('Safety order' + i_s, when=shortCondition)
    strategy.cancel('SO' + i_s, when=ta.crossunder(low, SL_line) or ta.crossover(high, TP_line) or status_none)
    strategy.exit('TP/SL','Base order', limit=TP_line, stop=SL_line, comment = Safe_order_line(100) > close ? 'SL' + i_s + ' - ' +  str.tostring(Base_order_size) + str.tostring(currency) : 'TP' + i_s + ' - ' +  str.tostring(Base_order_size) + str.tostring(currency)) 
    strategy.exit('TP/SL','Safety order' + i_s, limit=TP_line, stop=SL_line, comment = Safe_order_line(100) > close ? 'SL' + i_s + ' - ' +  str.tostring(safety_order_size(i)) + str.tostring(currency) : 'TP' + i_s + ' - ' +  str.tostring(safety_order_size(i)) + str.tostring(currency)) 
    // strategy.cancel('TP/SP' + i_s, when=Base_order_Condition)
    // strategy.exit('Stop Loss','Base order', stop=SL_line)
    // strategy.exit('Stop Loss','Safety order' + i_s, stop=SL_line)
    
//----------------label A----------------//

bot_usage(i) =>
 i == 1 ? Base_order_size + safety_order_size(1) :
 i == 2 ? Base_order_size + safety_order_size(1) + safety_order_size(2) :
 i == 3 ? Base_order_size + safety_order_size(1) + safety_order_size(2) + safety_order_size(3) :
 i == 4 ? Base_order_size + safety_order_size(1) + safety_order_size(2) + safety_order_size(3) + safety_order_size(4) : 
 i == 5 ? Base_order_size + safety_order_size(1) + safety_order_size(2) + safety_order_size(3) + safety_order_size(4) + safety_order_size(5) :
 i == 6 ? Base_order_size + safety_order_size(1) + safety_order_size(2) + safety_order_size(3) + safety_order_size(4) + safety_order_size(5) + safety_order_size(6) : 
 i == 7 ? Base_order_size + safety_order_size(1) + safety_order_size(2) + safety_order_size(3) + safety_order_size(4) + safety_order_size(5) + safety_order_size(6) + safety_order_size(7) : 
 i == 8 ? Base_order_size + safety_order_size(1) + safety_order_size(2) + safety_order_size(3) + safety_order_size(4) + safety_order_size(5) + safety_order_size(6) + safety_order_size(7) + safety_order_size(8) : 
 i == 9 ? Base_order_size + safety_order_size(1) + safety_order_size(2) + safety_order_size(3) + safety_order_size(4) + safety_order_size(5) + safety_order_size(6) + safety_order_size(7) + safety_order_size(8) + safety_order_size(9) :
 i == 10 ? Base_order_size + safety_order_size(1) + safety_order_size(2) + safety_order_size(3) + safety_order_size(4) + safety_order_size(5) + safety_order_size(6) + safety_order_size(7) + safety_order_size(8) + safety_order_size(9) + safety_order_size(10) : na

equity = strategy.equity
bot_use = bot_usage(Max_safety_trades_count)
bot_dev = float(step(Max_safety_trades_count)) * 100
bot_ava = (bot_use / equity) * 100

string label_A = 
 'Balance                                      : ' + str.tostring(math.round(equity, 0), '###,###,###,###') + ' USDT' + '\n' + 
 'Max amount for bot usage           : ' + str.tostring(math.round(bot_use, 0), '###,###,###,###') + ' USDT' + '\n' + 
 'Max safety order price deviation : ' + str.tostring(math.round(bot_dev, 0), '##.##') + ' %' + '\n' + 
 '% of available balance                : ' + str.tostring(math.round(bot_ava, 0), '###,###,###,###') + ' %' 
 + (bot_ava > 100 ? '\n \n' +  '⚠ Warning! Bot will use amount greater than you have on exchange' : na) 


if status_long
    day_label = 
     label.new(
     x=time[1], 
     y=high * 1.03, 
     text=label_A, 
     xloc=xloc.bar_time, 
     yloc=yloc.price, 
     color=bot_ava > 100 ? color.new(color.yellow, 0) : color.new(color.black, 50), 
     style=label.style_label_lower_right, 
     textcolor=bot_ava > 100 ? color.new(color.red, 0) : color.new(color.silver, 0), 
     size=size.normal, 
     textalign=text.align_left)

Mehr