Modelo de reversão de ruptura baseado na estratégia de negociação de tartarugas

Autora:ChaoZhang, Data: 2024-01-29 16:48:00
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Resumo

Esta estratégia é baseada na famosa Turtle Trading Strategy, que foi validada ao longo dos anos. Envia sinais longos e curtos com ordens de pirâmide de até 5, o que significa que a estratégia pode desencadear até 5 ordens na mesma direção. Com bom risco e gestão de dinheiro.

Deve notar-se que a estratégia combina dois sistemas que trabalham em conjunto (S1 e S2).

Estratégia lógica

O dimensionamento de posição é muito importante para os traders de tartarugas para gerenciar adequadamente o risco. Esta estratégia de dimensionamento de posição se adapta à volatilidade do mercado e à conta (ganhos e perdas).

O número de unidades a comprar é:

unit = (percentage_to_risk/100)*account/atr*syminfo.pointvalue 

Dependendo do seu apetite de risco, você pode aumentar a porcentagem da sua conta, mas os traders de tartaruga são padrão para 1%.

Existe também uma regra adicional para reduzir o risco se o valor da conta for inferior ao capital inicial: neste caso e apenas neste caso, na fórmula unitária deve ser substituída por:

account := (strategy.equity-strategy.openprofit)*(strategy.equity-strategy.openprofit)/strategy.initial_capital

Dois sistemas trabalham juntos:
Se for uma nova alta, abrimos uma posição longa e vice-versa, se for uma nova baixa, entramos em uma posição curta.

Adicionamos uma regra adicional:
Esta regra adicional permite que o comerciante esteja em tendências principais se o sinal do sistema 1 tiver sido ignorado. Se um sinal para o sistema 1 tiver sido ignorado e a próxima vela também for uma nova ruptura de 20 dias, a S1 não dará um sinal.

Análise das vantagens

A estratégia da tartaruga permite-nos adicionar unidades extras à posição se o preço se mover a nosso favor. Eu configurei a estratégia para permitir que até 5 ordens sejam adicionadas na mesma direção.

Nós estabelecemos uma SL máxima de 10% para a primeira ordem, o que significa que você não perderá mais de 10% do valor de sua primeira ordem. No entanto, é possível perder mais em suas ordens de pirâmide, pois a SL é aumentada/diminuída em 0,5*ATR(20), o que não garante uma perda de mais de 10% em suas ordens de pirâmide.

Análise de riscos

O maior risco desta estratégia são as posições de tamanho excessivo. Uma vez que as ordens de mercado são usadas para a colocação de ordens, a colocação de várias ordens de mercado enormes ao mesmo tempo terá um enorme impacto na cotação, causando um grande deslizamento. Isso levará a enormes perdas de capital.

Outro risco é a configuração inadequada de gestão de capital. Por exemplo, a configuração incorreta de stop loss ou proporções excessivas podem levar a perdas enormes. Isso precisa ser configurado com cautela de acordo com o próprio apetite de risco.

Optimização

A estratégia pode ser otimizada nos seguintes aspectos:

  1. Teste o impacto de diferentes parâmetros, como período ATR, multiplicador ATR para stop loss, etc. no retorno e na proporção de níveis.

  2. Teste diferentes regras de entrada e saída. Por exemplo, use padrões de candelabro como filtros adicionais.

  3. Tente outros tipos de stop loss, como stop loss móvel, stop loss dinâmico.

  4. Teste o número de ordens da pirâmide, quanto mais ordens, maior a alavancagem e o risco, encontre o melhor ponto de equilíbrio.

  5. Tente interromper a negociação durante períodos de tempo específicos (como antes da divulgação dos dados da folha de pagamento não agrícola dos EUA) para evitar o impacto de grandes eventos.

Resumo

Em geral, esta estratégia atinge um bom equilíbrio entre risco e recompensa, adequado para a negociação de tendências de médio e longo prazo.


/*backtest
start: 2023-12-01 00:00:00
end: 2023-12-31 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © gsanson66


//This strategy is based on the famous "Turtle Strategy"
//A well-known strategy which proved its performance during past years 
//@version=5
strategy("TURTLE STRATEGY", overlay=true)


//------------------------------TOOL TIPS--------------------------------//

t1 = "Percentage of the account the trader is willing to lose. This percentage is used to define the position size based on previous gains or losses. Turtle traders default to 1%."
t2 = "ATR Length"
t3 = "ATR Multiplier to fix the Stop Loss"
t4 = "Pyramiding : ATR Multiplier to set a profit target to increase position size"
t5 = "System 1 enter long if there is a new high after this selected period of time"
t6 = "System 2 enter long if there is a new high after this selected period of time"
t7 = "Exit Long from system 1 if there is a new low after this selected period of time"
t8 = "Exit Long from system 2 if there is a new low after this selected period of time"
t9 = "System 1 enter short if there is a new low after this selected period of time"
t10 = "System 2 enter short if there is a new low after this selected period of time"
t11 = "Exit short from system 1 if there is a new high after this selected period of time"
t12 = "Exit short from system 2 if there is a new high after this selected period of time"


//----------------------------------------FUNCTIONS---------------------------------------//

//@function Displays text passed to `txt` when called.
debugLabel(txt, color) =>
    label.new(bar_index, high, text=txt, color=color, style=label.style_label_lower_right, textcolor=color.black, size=size.small)

//@function which looks if the close date of the current bar falls inside the date range
inBacktestPeriod(start, end) => true


//---------------------------------------USER INPUTS--------------------------------------//

//Risk Management and turtle system input
percentage_to_risk = input.float(1, "Risk % of capital", maxval=100, minval=0, group="Turtle Parameters", tooltip=t1) 
atr_period = input.int(20, "ATR period", minval=1, group="Turtle Parameters", tooltip=t2)
stop_N_multiplier = input.float(1.5, "Stop ATR", minval=0.1, group="Turtle Parameters", tooltip=t3)
pyramid_profit = input.float(0.5, "Pyramid Profit", minval=0.01, group="Turtle Parameters", tooltip=t4)
S1_long = input.int(20, "S1 Long", minval=1, group="Turtle Parameters", tooltip=t5)
S2_long = input.int(55, "S2 Long", minval=1, group="Turtle Parameters", tooltip=t6)
S1_long_exit = input.int(10, "S1 Long Exit", minval=1, group="Turtle Parameters", tooltip=t7)
S2_long_exit = input.int(20, "S2 Long Exit", minval=1, group="Turtle Parameters", tooltip=t8)
S1_short = input.int(15, "S1 Short", minval=1, group="Turtle Parameters", tooltip=t9)
S2_short = input.int(55, "S2 Short", minval=1, group="Turtle Parameters", tooltip=t10)
S1_short_exit = input.int(7, "S1 Short Exit", minval=1, group="Turtle Parameters", tooltip=t11)
S2_short_exit = input.int(20, "S2 Short Exit", minval=1, group="Turtle Parameters", tooltip=t12)
//Backtesting period
startDate = input(title="Start Date", defval=timestamp("1 Jan 2020 00:00:00"), group="Backtesting Period")
endDate = input(title="End Date", defval=timestamp("1 July 2034 00:00:00"), group="Backtesting Period")


//----------------------------------VARIABLES INITIALISATION-----------------------------//

//Turtle variables
atr = ta.atr(atr_period)
var float buy_price_long = na
var float buy_price_short = na
var float stop_loss_long = na
var float stop_loss_short = na
float account = na
//Entry variables
day_high_syst1 = ta.highest(high, S1_long)
day_low_syst1 = ta.lowest(low, S1_short)
day_high_syst2 = ta.highest(high, S2_long)
day_low_syst2 = ta.lowest(low, S2_short)
var bool skip = false
var bool unskip_buffer_long = false
var bool unskip_buffer_short = false
//Exit variables
exit_long_syst1 = ta.lowest(low, S1_long_exit)
exit_short_syst1 = ta.highest(high, S1_short_exit)
exit_long_syst2 = ta.lowest(low, S2_long_exit)
exit_short_syst2 = ta.highest(high, S2_short_exit)
float exit_signal = na
//Backtesting period
bool inRange = na


//------------------------------CHECKING SOME CONDITIONS ON EACH SCRIPT EXECUTION-------------------------------//
strategy.initial_capital = 50000
//Checking if the date belong to the range
inRange := inBacktestPeriod(startDate, endDate)

//Checking if the current equity is higher or lower than the initial capital to adjusted position size
if strategy.equity - strategy.openprofit < strategy.initial_capital
    account := (strategy.equity-strategy.openprofit)*(strategy.equity-strategy.openprofit)/strategy.initial_capital
else
    account := strategy.equity - strategy.openprofit

//Checking if we close all trades in case where we exit the backtesting period
if strategy.position_size!=0 and not inRange
    strategy.close_all()
    debugLabel("END OF BACKTESTING PERIOD : we close the trade", color=color.rgb(116, 116, 116))


//--------------------------------------SKIP MANAGEMENT------------------------------------//
    
//Checking if a long signal has been skiped and system2 is not triggered
if skip and high>day_high_syst1[1] and high<day_high_syst2[1]
    unskip_buffer_long := true

//Checking if a short signal has been skiped and system2 is not triggered
if skip and low<day_low_syst1[1] and low>day_low_syst2[1]
    unskip_buffer_short := true

//Checking if current high is lower than previous 20_day_high after a skiped long signal to set skip to false
if unskip_buffer_long
    if high<day_high_syst1[1]
        skip := false
        unskip_buffer_long := false

//Checking if current low is higher than previous 20_day_low after a skiped short signal to set skip to false
if unskip_buffer_short
    if low>day_low_syst1[1]
        skip := false
        unskip_buffer_short := false

//Checking if we have an open position to reset skip and unskip buffers
if strategy.position_size!=0 and skip
    skip := false
    unskip_buffer_long := false
    unskip_buffer_short := false


//--------------------------------------------ENTRY CONDITIONS--------------------------------------------------//

//We calculate the position size based on turtle calculation
unit = (percentage_to_risk/100)*account/atr*syminfo.pointvalue

//Long order for system 1
if not skip and not (strategy.position_size>0) and inRange
    strategy.cancel("Long Syst 2")
    //We check that position size doesn't exceed available equity
    if unit*day_high_syst1>account
        unit := account/day_high_syst1
    stop_loss_long := day_high_syst1 - stop_N_multiplier*atr
    //We adjust SL if it's greater than 10% of trade value and fix it to 10%
    if stop_loss_long < day_high_syst1*0.9
        stop_loss_long := day_high_syst1*0.9
    strategy.order("Long Syst 1", strategy.long, unit, stop=day_high_syst1)
    buy_price_long := day_high_syst1

//Long order for system 2
if skip and not (strategy.position_size>0) and inRange
    //We check that position size doesn't exceed available equity
    if unit*day_high_syst2>account
        unit := account/day_high_syst2
    stop_loss_long := day_high_syst2 - stop_N_multiplier*atr
    //We adjust SL if it's greater than 10% of trade value and fix it to 10%
    if stop_loss_long < day_high_syst2*0.9
        stop_loss_long := day_high_syst2*0.9
    strategy.order("Long Syst 2", strategy.long, unit, stop=day_high_syst2)
    buy_price_long := day_high_syst2

//Short order for system 1
if not skip and not (strategy.position_size<0) and inRange
    strategy.cancel("Short Syst 2")
    //We check that position size doesn't exceed available equity
    if unit*day_low_syst1>account
        unit := account/day_low_syst1
    stop_loss_short := day_low_syst1 + stop_N_multiplier*atr
    //We adjust SL if it's greater than 10% of trade value and fix it to 10%
    if stop_loss_short > day_low_syst1*1.1
        stop_loss_short := day_low_syst1*1.1
    strategy.order("Short Syst 1", strategy.short, unit, stop=day_low_syst1)
    buy_price_short := day_low_syst1

//Short order for system 2
if skip and not (strategy.position_size<0) and inRange
    //We check that position size doesn't exceed available equity
    if unit*day_low_syst2>account
        unit := account/day_low_syst2
    stop_loss_short := day_low_syst2 + stop_N_multiplier*atr
    //We adjust SL if it's greater than 10% of trade value and fix it to 10%
    if stop_loss_short > day_low_syst2*1.1
        stop_loss_short := day_low_syst2*1.1
    strategy.order("Short Syst 2", strategy.short, unit, stop=day_low_syst2)
    buy_price_short := day_low_syst2


//-------------------------------PYRAMIDAL------------------------------------//

//Pyramid for long orders
if close > buy_price_long + (pyramid_profit*atr) and strategy.position_size>0
    //We calculate the remaining capital
    remaining_capital = account - strategy.position_size*strategy.position_avg_price*(1-0.0018)
    //We calculate units to add to the long position
    units_to_add = (percentage_to_risk/100)*remaining_capital/atr*syminfo.pointvalue
    if remaining_capital > units_to_add
        //We set the new Stop loss
        stop_loss_long := stop_loss_long + pyramid_profit*atr
        strategy.entry("Pyramid Long", strategy.long, units_to_add)
        buy_price_long := close

//Pyramid for short orders
if close < buy_price_short - (pyramid_profit*atr) and strategy.position_size<0
    //We calculate the remaining capital
    remaining_capital = account + strategy.position_size*strategy.position_avg_price*(1-0.0018)
    //We calculate units to add to the short position
    units_to_add = (percentage_to_risk/100)*remaining_capital/atr*syminfo.pointvalue
    if remaining_capital > units_to_add
        //We set the new Stop loss
        stop_loss_short := stop_loss_short - pyramid_profit*atr
        strategy.entry("Pyramid Short", strategy.short, units_to_add)
        buy_price_short := close


//----------------------------EXIT ORDERS-------------------------------//

//Checking if exit_long_syst1 is higher than stop_loss_long
if strategy.opentrades.entry_id(0)=="Long Syst 1"
    if exit_long_syst1[1] > stop_loss_long
        exit_signal := exit_long_syst1[1]
    else
        exit_signal := stop_loss_long

//Checking if exit_long_syst2 is higher than stop_loss_long
if strategy.opentrades.entry_id(0)=="Long Syst 2"
    if exit_long_syst2[1] > stop_loss_long
        exit_signal := exit_long_syst2[1]
    else
        exit_signal := stop_loss_long

//Checking if exit_short_syst1 is lower than stop_loss_short
if strategy.opentrades.entry_id(0)=="Short Syst 1"
    if exit_short_syst1[1] < stop_loss_short
        exit_signal := exit_short_syst1[1]
    else
        exit_signal := stop_loss_short

//Checking if exit_short_syst2 is lower than stop_loss_short
if strategy.opentrades.entry_id(0)=="Short Syst 2"
    if exit_short_syst2[1] < stop_loss_short
        exit_signal := exit_short_syst2[1]
    else
        exit_signal := stop_loss_short

//If the exit order is configured to close the position at a profit, we set 'skip' to true (we substract commission)
if strategy.position_size*exit_signal>strategy.position_size*strategy.position_avg_price*(1-0.0018)
    strategy.cancel("Long Syst 1")    
    strategy.cancel("Short Syst 1")
    skip := true
if strategy.position_size*exit_signal<=strategy.position_size*strategy.position_avg_price*(1-0.0018)
    skip := false

//We place stop exit orders
if strategy.position_size > 0
    strategy.exit("Exit Long", stop=exit_signal)

if strategy.position_size < 0
    strategy.exit("Exit Short", stop=exit_signal)


//------------------------------PLOTTING ELEMENTS-------------------------------//

plotchar(atr, "ATR", "", location.top, color.rgb(131, 5, 83))
//Plotting enter threshold
plot(day_high_syst1[1], "20 day high", color.rgb(118, 217, 159))
plot(day_high_syst2[1], "55 day high", color.rgb(4, 92, 53))
plot(day_low_syst1[1], "20 day low", color.rgb(234, 108, 108))
plot(day_low_syst2[1], "55 day low", color.rgb(149, 17, 17))
//Plotting Exit Signal
plot(exit_signal, "Exit Signal", color.blue, style=plot.style_circles)
//Plotting our position
exit_long_syst2_plot = plot(exit_long_syst2[1], color=na)
day_high_syst2_plot = plot(day_high_syst2[1], color=na)
exit_short_syst2_plot = plot(exit_short_syst2[1], color=na)
day_low_syst2_plot = plot(day_low_syst2[1], color=na)
fill(exit_long_syst2_plot, day_high_syst2_plot, color=strategy.position_size>0 ? color.new(color.lime, 90) : na)
fill(exit_short_syst2_plot, day_low_syst2_plot, color=strategy.position_size<0 ? color.new(color.red, 90) : na)



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