Estratégia de negociação de tartarugas nadadoras
ChaoZhang
Visão geral
A estratégia de negociação de corvos é uma estratégia de acompanhamento de tendências baseada na famosa estratégia de negociação de corvos para melhorar e otimizar. A estratégia usa sinais de negociação formados por médias móveis duplas para realizar negociações de acompanhamento de tendências de baixo risco.
Princípio da estratégia
A estratégia de negociação de corrida estabelece um objetivo de stop loss e de ganho através da conjugação de altos de 20 dias, baixos de 20 dias, altos de 55 dias e baixos de 55 dias. Gera um sinal longo quando o preço ultrapassa os altos de 20 dias; gera um sinal de vazio quando o preço cai abaixo dos baixos de 20 dias. Além disso, a estratégia também estabelece um mecanismo de salto, que salta o sinal de negociação se o preço atual ultrapassa os altos e baixos de 20 dias, mas não ultrapassa os altos e baixos de 55 dias.
Após a entrada no mercado, a estratégia usa o valor do indicador ATR para definir o ponto de parada e o alvo de posição. Quando os prejuízos atingem o ponto de parada, a perda é ativada; quando os lucros atingem o alvo de posição, a posição é aumentada. Isso permite controlar o risco de uma única transação ao mesmo tempo em que maximiza o potencial de lucro em uma situação de tendência.
Análise de vantagens
A maior vantagem da estratégia de negociação de agilidade reside na excelente capacidade de controle de risco. As regras de entrada e saída padronizadas controlam efetivamente os prejuízos de uma única negociação, e o mecanismo de escapamento evita a possibilidade de ficar preso em situações adversas durante a noite.
Além disso, a estratégia de negociação flexível usa o indicador ATR para definir dinamicamente o ponto de parada, o que permite que a linha de parada se adapte automaticamente às mudanças na taxa de flutuação do mercado. Isso garante que a linha de parada não seja demasiado relaxada para causar grandes perdas, nem demasiado apertada para ser desencadeada pela flutuação normal do mercado.
Finalmente, o mecanismo de acréscimo de risco da estratégia permite que ela capture o lucro em condições de tendência. Isso cria a base para o crescimento estável do capital.
Análise de Riscos
O principal risco de uma estratégia de negociação livre é a incapacidade de aproveitar efetivamente os cenários de turbulência para obter lucros. Quando o mercado está em turbulência prolongada, a linha de parada pode ser freqüentemente acionada para causar perdas. E saltar o mecanismo também pode levar a sinais insuficientes e perder potenciais oportunidades de negociação.
Além disso, a estratégia depende muito de indicadores técnicos e ignora a análise fundamental, o que pode fazer com que não identifique mudanças importantes na política, o que pode levar a perdas desnecessárias.
Direção de otimização
As estratégias de negociação de Forex podem ser otimizadas em vários aspectos:
Combinação de indicadores de volatilidade para ajustar a sensibilidade do mecanismo de saltos e aumentar a frequência de negociação em situações de turbulência
Aumentar os sinais básicos como filtros para evitar interrupções de eventos inesperados
Optimizar a configuração dos parâmetros ATR para que a linha de parada seja mais adequada para oscilações reais
Combinação de indicadores de quantidade de energia para evitar a reversão de invalidez após a perda
Resumir
Em geral, a estratégia de negociação de corvos melhorou a capacidade de controle de lucro e risco da estratégia original de negociação de corvos, uma estratégia de algoritmo de baixo risco adequada para rastrear tendências. Com uma otimização adicional, a estratégia pode ser uma parte importante da construção de portfólios de lucros estáveis a longo prazo.
/*backtest
start: 2024-01-29 00:00:00
end: 2024-02-28 00:00:00
period: 3h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=5
strategy("TURTLE STRATEGY", precision=2, overlay=true, initial_capital=1000, commission_type=strategy.commission.percent, commission_value=0.18, slippage=3, pyramiding=5, close_entries_rule="ANY", margin_long=100, margin_short=100)
//------------------------------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) => (time >= start) and (time <= end)
//---------------------------------------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-------------------------------//
//Checking if the date belong to the range
inRange := true
strategy.initial_capital = 50000
//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 and unit>0
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 and unit>0
//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 and unit>0
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 and unit>0
//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 and units_to_add>0
//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 and units_to_add>0
//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)