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Estratégia de tendência de inversão de três velas

Autora:ChaoZhang, Data: 2024-02-18 09:48:28
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Resumo

A Estratégia de Tendência de Reversão de Três Velas é uma estratégia de negociação de curto prazo que identifica reversões em tendências de curto prazo detectando três velas de alta ou baixa consecutivas seguidas por uma vela de engolimento na direção oposta, combinada com vários indicadores técnicos para filtrar sinais de entrada.

Estratégia lógica

A lógica central desta estratégia é identificar o padrão de três velas de alta ou baixa consecutivas no gráfico, o que geralmente implica uma reversão iminente na tendência de curto prazo. Quando três velas de baixa são detectadas, espere que a próxima vela de alta engulfante vá longa. Por outro lado, quando três velas de alta são detectadas, espere que a próxima vela de baixa engulfante vá curta. Isso permite capturar oportunidades de reversão em tendências de curto prazo em tempo hábil.

Além disso, vários indicadores técnicos são introduzidos para filtrar os sinais de entrada. Duas linhas SMA com configurações de parâmetros diferentes são adotadas e as posições de entrada são consideradas apenas quando a SMA mais rápida cruza a linha mais lenta. Além disso, o indicador de regressão linear é usado para julgar se o mercado está variando ou em tendência, e os negócios são feitos apenas em condições de tendência. Há também uma opção para combinar o padrão de vela com cruzes douradas SMA para sinais de entrada adicionais. Através dos julgamentos abrangentes desses indicadores, a maioria do ruído pode ser filtrada e a precisão de entrada é melhorada.

Para stop loss e take profit, a estratégia requer uma relação risco-recompensação mínima de 1:3. O indicador ATR baseado na flutuação de preços de N velas recentes é usado para determinar o nível de stop loss com uma porcentagem de compensação.

Vantagens

A estratégia de inversão de tendência de três velas tem as seguintes vantagens:

  1. Identificar reversões das tendências de curto prazo para oportunidades oportunas
  2. Precisão de entrada melhorada através de múltiplos filtros de indicadores
  3. Profil de risco-benefício razoável com stop loss e take profit adequados
  4. Parâmetros simples para facilitar a compreensão e o funcionamento

Riscos

Há também alguns riscos a considerar para esta estratégia:

  1. As reversões de curto prazo não implicam necessariamente reversões de tendência de longo prazo. Tendências de maior prazo devem ser monitoradas.
  2. Os padrões de um só candelabro podem produzir sinais falsos.
  3. As configurações de stop loss podem ser muito agressivas.
  4. A insuficiência de dados de backtest leva à incerteza no desempenho real das negociações.

Orientações para a melhoria

A estratégia pode ser reforçada nos seguintes aspectos:

  1. Ajustar os parâmetros das médias móveis e da regressão linear para melhor identificar as tendências.
  2. Adicionar outros indicadores como o Stoch para confirmação de sinal suplementar.
  3. Otimizar os parâmetros ATR e a percentagem de stop loss para equilibrar o risco e o retorno.
  4. Introduzir mecanismos de acompanhamento da ruptura da tendência para melhorar a rentabilidade.
  5. Estabelecer sistemas robustos de gestão de capitais para controlar os riscos comerciais.

Conclusão

Em conclusão, a Estratégia de Tendência de Reversão das Três Velas é uma estratégia de negociação simples de curto prazo que capitaliza os padrões de preços e múltiplos indicadores para capturar oportunidades de reversão, baseada em perfis de risco-recompensa adequadamente equilibrados.


/*backtest
start: 2024-01-01 00:00:00
end: 2024-01-31 23:59:59
period: 3h
basePeriod: 15m
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/
// © platsn
//
// Mainly developed for SPY trading on 1 min chart. But feel free to try on other tickers.

// Basic idea of this strategy is to look for 3 candle reversal pattern within trending market structure. The 3 candle reversal pattern consist of 3 consecutive bullish or bearish candles, 
// followed by an engulfing candle in the opposite direction. This pattern usually signals a reversal of short term trend. This strategy also uses multiple moving averages to filter long or short
// entries. ie. if the 21 smoothed moving average is above the 50, only look for long (bullish) entries, and vise versa. There is option change these moving average periods to suit your needs. 
// I also choose to use Linear Regression to determine whether the market is ranging or trending. It seems the 3 candle pattern is more successful under trending market. Hence I use it as a filter.

// There is also an option to combine this strategy with moving average crossovers. The idea is to look for 3 canddle pattern right after a fast moving average crosses over a slow moving average.
// By default , 21 and 50 smoothed moving averages are used. This gives additional entry opportunites and also provides better results. 

// This strategy aims for 1:3 risk to reward ratio. Stop losses are calculated using the closest low or high values for long or short entries, respectively, with an offset using a percentage of
// the daily ATR value. This allows some price flucuation without being stopped out prematurely. Price target is calculated by multiplying the difference between the entry price and the stop loss
// by a factor of 3. When price target is reach, this strategy will set stop loss at the price target and wait for exit considion to maximize potential profit. 

// This strategy will exit an order if an opposing 3 candle pattern is detected, this could happend before stop loss or price target is reached, and may also happen after price target is reached.

// *Note that this strategy is designed for same day SPY option scalping. I haven't determined an easy way to calculate the # of contracts to represent the equivalent option values. Plus the option
// prices varies greatly depending on which strike and expiry that may suits your trading style. Therefore, please be mindful of the net profit shown. By default, each entry is approxiately equal 
// to buying 10 of same day or 1 day expiry call or puts at strike $1 - $2 OTM. This strategy will close all open trades at 3:45pm EST on Mon, Wed, and Fri. 

// **Note that this strategy also takes into account of extended market data.

// ***Note pyramiding is set to 2 by default, so it allows for multiple entries on the way towards price target. 

// Remember that market conditions are always changing. This strategy was only able to be backtested using 1 month of data. This strategy may not work the next month. Please keep that in mind. 

// *****************************************************************************************************************************************************************************************************

//@version=5
strategy("3 Candle Strike Stretegy", overlay=true, pyramiding=2, initial_capital=5000, commission_type=strategy.commission.cash_per_contract, commission_value = 0.01) 

// ******************** Period **************************************
startY = input(title='Start Year', defval=2011, group = "Trading window")
startM = input.int(title='Start Month', defval=1, minval=1, maxval=12, group = "Trading window")
startD = input.int(title='Start Day', defval=1, minval=1, maxval=31, group = "Trading window")
finishY = input(title='Finish Year', defval=2050, group = "Trading window")
finishM = input.int(title='Finish Month', defval=12, minval=1, maxval=12, group = "Trading window")
finishD = input.int(title='Finish Day', defval=31, minval=1, maxval=31, group = "Trading window")
timestart = timestamp(startY, startM, startD, 00, 00)
timefinish = timestamp(finishY, finishM, finishD, 23, 59)
t1 = time(timeframe.period, "0930-1545:23456")
window = true

// *****************************************************

isSPY = input.bool(defval=true,title="SPY trading only", group = "Trading Options")
SPY_option = input.int(defval=10,title="# of SPY options per trade", group = "Trading Options")
reinvest = input.bool(defval=false,title="reinvest profit?", group = "Trading Options")
src = close

// ***************************************************************************************************** Daily ATR *****************************************************
// Inputs
atrlen = input.int(14, minval=1, title="ATR period", group = "Daily ATR")
iPercent = input.float(5, minval=1, maxval=100, step=0.1, title="% ATR to use for SL / PT", group = "Daily ATR")
// PTPercent = input.int(100, minval=1, title="% ATR for PT")

// Logic
percentage = iPercent * 0.01
datr = request.security(syminfo.tickerid, "1D", ta.rma(ta.tr, atrlen))
datrp = datr * percentage
// datrPT = datr * PTPercent * 0.01

plot(datr,"Daily ATR")
plot(datrp, "Daily % ATR")

// ***************************************************************************************************************** Moving Averages ************************

len0 = input.int(8, minval=1, title='Fast EMA', group= "Moving Averages")
ema1 = ta.ema(src, len0)

len1 = input.int(21, minval=1, title='Fast SMMA', group= "Moving Averages")
smma1 = 0.0
sma_1 = ta.sma(src, len1)
smma1 := na(smma1[1]) ? sma_1 : (smma1[1] * (len1 - 1) + src) / len1

len2 = input.int(50, minval=1, title='Slow SMMA', group= "Moving Averages")
smma2 = 0.0
sma_2 = ta.sma(src, len2)
smma2 := na(smma2[1]) ? sma_2 : (smma2[1] * (len2 - 1) + src) / len2

len3 = input.int(200, minval=1, title='Slow SMMA', group= "Moving Averages")
smma3 = 0.0
sma_3 = ta.sma(src, len3)
smma3 := na(smma3[1]) ? sma_3 : (smma3[1] * (len3 - 1) + src) / len3

ma_bull = smma1 > smma2 and smma1 > smma1[1]
ma_bear = smma1 < smma2 and smma1 < smma1[1]

ma_bull_macro = smma1 > smma3 and smma2 > smma3
ma_bear_macro = smma1 < smma3 and smma2 < smma3

// plot(ma_bull? 1 : 0, "MA bull")
// plot(ma_bear? 1 : 0 , "MA bear")

// **************************************************************************************************************** Linear Regression *************************

//Input
clen = input.int(defval = 50, minval = 1, title = "Linear Regression Period", group = "Linear Regression")
slen = input.int(defval=50, minval=1, title="LR Slope Period" , group = "Linear Regression")
glen = input.int(defval=14, minval=1, title="LR Signal Period", group = "Linear Regression")
LR_thres = input.float(0.03, minval=0, step=0.001, title="LR Threshold for Ranging vs Trending" , group = "Linear Regression")
 
//Linear Regression Curve
lrc = ta.linreg(src, clen, 0)
//Linear Regression Slope
lrs = (lrc-lrc[1])/1
//Smooth Linear Regression Slope
slrs = ta.ema(lrs, slen)
//Signal Linear Regression Slope
alrs = ta.sma(slrs, glen)

up_accel = lrs > alrs and lrs > 0 
down_accel = lrs < alrs and lrs < 0 

LR_ranging  = math.abs(slrs) <= LR_thres
LR_trending = math.abs(slrs) > LR_thres

plot(slrs, "LR slope")
plot(LR_trending?1:0, "LR Trending")

// *********************************************************************************************************************************** Candle conditions **************************

bull_3s = close[3] <= open[3] and close[2] <= open[2] and close[1] <= open[1] and close > open[1]
bear_3s = close[3] >= open[3] and close[2] >= open[2] and close[1] >= open[1] and close < open[1]

plotshape(bull_3s, style=shape.triangleup, color=color.new(color.green, 0), location=location.belowbar, size=size.small, text='3s-Bull', title='3 Line Strike Up')
plotshape(bear_3s, style=shape.triangledown, color=color.new(color.red, 0), location=location.abovebar, size=size.small, text='3s-Bear', title='3 Line Strike Down')

// ***************************************************************************************************************************************** SL & PT ***********************************
RR = input.float(3.0, minval = 1, step = 0.1, title="Reward to Risk Ratio", group = "Trading Options")

barsSinceLastEntry()=>
    strategy.opentrades > 0 ? (bar_index - strategy.opentrades.entry_bar_index(strategy.opentrades-1)) : na

last_high = math.max(high, high[1], high[2], high[3])
last_low = math.min(low, low[1], low[2], low[3])

long_SL = last_low - datrp
short_SL = last_high + datrp

long_PT = last_high
short_PT = last_low

last_entry = strategy.opentrades.entry_price(strategy.opentrades-1)
risk = last_entry - long_SL

if strategy.opentrades > 0
    long_SL := math.min(long_SL[barsSinceLastEntry()], last_low)
    short_SL := math.max(short_SL[barsSinceLastEntry()], last_high)
    risk := last_entry - long_SL
    long_PT := last_entry + (last_entry - long_SL) * RR
    short_PT := last_entry - (short_SL - last_entry) * RR
else
    long_PT := open + (open - long_SL) * RR
    short_PT := open - (short_SL - open) * RR

// plot(short_SL,title = "Short SL", color=color.new(color.purple,30))
// plot(long_SL,title = "Long SL", color=color.new(color.purple,30))
// plot(long_PT,title = "Long PT", color=color.new(color.white,50))
// plot(short_PT,title = "Short PT", color=color.new(color.white,50))
// plot(last_entry, title = "Last entry")
// plot(risk, title = "Risk")

// **************************************************************************************************************************************** Trade Pauses ****************************************
bool trade_pause = false
bool trade_pause2 = false

if high - low > datr*0.3
    trade_pause := true
else
    trade_pause := false

no_longat10 = input.bool(true, title="No long entry between 10 - 10:30 (Avoid 10 am dump)", group = "Trading Options")

// ************************************************************************************************************************************ Entry conditions **************************

trade_3s = input.bool(title='Trade 3s candle pattern', defval=true, group = "Trading Options")
L_entry1 = bull_3s and ma_bull and LR_trending 
S_entry1 = bear_3s and ma_bear and LR_trending

trade_ma_reversal = input.bool(title='Trade MA Cross Reversal Signal', defval=true, group = "Trading Options")
L_entry2 = ma_bear_macro and ema1 > smma1 and bull_3s and ta.barssince(ta.cross(ema1,smma1)) < 10
S_entry2 = ma_bull_macro and ema1 < smma1 and bear_3s and ta.barssince(ta.cross(ema1,smma1)) < 10

// ************************************************************************************************************************************** Exit Conditions ********************************

// bsle_thres = input.int(0, "Bar since entry threshold")

// exit0 = barsSinceLastEntry() >= bsle_thres
exit0 = true

L_exit1 = bear_3s
S_exit1 = bull_3s

// ************************************************************************************************************************************ Entry and Exit orders *****************************
strategy.initial_capital = 50000
trade_amount = math.floor(strategy.initial_capital / close)

if isSPY 
    if strategy.netprofit > 0 and reinvest
        trade_amount := math.floor((strategy.initial_capital + strategy.netprofit) * 0.2 / 600) * 10 * SPY_option
    else
        trade_amount := math.floor(strategy.initial_capital * 0.2 / 600) * 10 * SPY_option


if not(trade_pause) and not(trade_pause2) and time(timeframe.period, "0930-1540:23456")
    if trade_3s
        if not(time(timeframe.period, "1000-1030:23456")) and no_longat10
            strategy.entry("Long", strategy.long, 1, when = L_entry1 and window, comment="Long 3s" + " SL=" + str.tostring(math.round(long_SL,2)) + " PT=" + str.tostring(math.round(long_PT,2)))
        strategy.entry("Short", strategy.short, 1, when = S_entry1 and window, comment = "Short 3s" + " SL=" + str.tostring(math.round(short_SL,2)) + " PT=" + str.tostring(math.round(short_PT,2)))
    if trade_ma_reversal
        strategy.entry("Long", strategy.long, 1, when = L_entry2 and window, comment="Long MA cross" + " SL=" + str.tostring(math.round(long_SL,2)) + " PT=" + str.tostring(math.round(long_PT,2)))
        strategy.entry("Short", strategy.short, 1, when = S_entry2 and window, comment = "Short MA corss" + " SL=" + str.tostring(math.round(short_SL,2)) + " PT=" + str.tostring(math.round(short_PT,2)))

if high > long_PT
    long_SL := low[1]
    strategy.exit("Exit", "Long", when = exit0 and low < long_PT, stop= long_SL, comment = "Exit Long SL/PT hit")
strategy.close("Long", when = L_exit1, comment = "Exit on Bear Signal")

if low < short_PT
    short_SL := high[1]
    strategy.exit("Exit", "Short", when= exit0 and high > short_PT, stop= short_SL, comment = "Exit Short SL/PT hit")
strategy.close("Short", when = S_exit1, comment = "Exit on Bull Signal")

if time(timeframe.period, "1545-1600:246")
    strategy.close_all()


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