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Stratégie de négociation DCA pondérée graduellement quantifiée

Auteur:ChaoZhang est là., Date: le 16 novembre 2023
Les étiquettes:

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Résumé

La stratégie de trading DCA pondérée graduelle quantifiée est une stratégie de trading quantitative qui combine des indicateurs de moyenne mobile pour déclencher le signal et des mécanismes de moyenne de coût en dollars pondérés graduels.

Principaux

La stratégie est composée de trois éléments principaux:

  1. Jugement du signal d'entrée

    Il utilise des croisements de moyennes mobiles rapides et lentes comme signal d'entrée. Les utilisateurs peuvent choisir entre SMA, EMA ou HMA pour les moyennes mobiles rapides et lentes.

  2. DCA pondérée progressivement

    Après un signal d'achat, la stratégie ouvrira immédiatement une position de base. Au fur et à mesure que le prix continue de baisser, la stratégie augmentera progressivement la taille des positions de sécurité supplémentaires de manière pondérée. Le prix de chaque nouvelle position de sécurité sera abaissé d'un pourcentage fixe par rapport à la précédente.

    Cette augmentation progressive de la taille des positions permet une forme de moyenne des coûts, obtenant un meilleur coût moyen tout en maîtrisant les risques.

  3. Profitez et arrêtez la perte

    Lorsque le prix monte au-dessus de la ligne de prise de profit, la stratégie fermera les positions pour le profit. Lorsque le prix tombe en dessous de la ligne de stop loss, la stratégie sort des positions pour contrôler la perte.

    La marge bénéficiaire est fixée au prix moyen de la position de base * (1 + pourcentage fixe).

    La ligne de stop loss fluctue en fonction du prix de la dernière position de sécurité, pourcentage fixe en dessous.

Les avantages

  1. La combinaison de la tendance et de la moyenne des coûts le rend plus stable

    L'utilisation des tendances évite les problèmes inutiles, et la moyenne des coûts offre de meilleurs coûts d'entrée.

  2. La dimensionnement progressif de la position contrôle le risque

    L'amplification fixe des dimensions des positions de sécurité, avec seuil de réentrée, maintient le risque sous contrôle.

  3. Surveillance en temps réel des fonds utilisés

    L'indicateur d'utilisation du solde intégré empêche le surendettement et les liquidations forcées.

  4. TP/SL séparé pour chaque position

    Les sorties indépendantes permettent de sécuriser les profits et de réduire les pertes.

Risques et améliorations

  1. Les baisses de prix peuvent déclencher plusieurs ordres de sécurité

    En cas de volatilité extrême, plusieurs ordres de sécurité inutiles peuvent être ajoutés, augmentant la perte.

  2. Les paramètres de moyenne mobile doivent être optimisés

    Différents instruments ont besoin de périodes de moyenne mobile différentes.

  3. Les niveaux de TP/SL doivent être optimisés pour les tests antérieurs

    Les ratios TP/SL déterminent le profil risque/rendement.

  4. Ajouter le tirage maximal ou la sortie forcée basée sur le temps de rétention

    Peut être testé en incorporant des sorties forcées basées sur le temps de prise ou de maintien pour limiter davantage les risques.

Résumé

La stratégie de trading DCA pondérée graduelle quantifiée combine les avantages du trading de tendance et de la moyenne des coûts pour produire des rendements stables dans des tendances fortes.


/*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)

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