雨幕（youquant）
我制定了很好的策略，只有多头和短头订单才能获得巨大的利润。策略逻辑非常简单，使用3种不同sma（7,21,55）找到正确趋势的策略
为了避免大量错误信号，我添加了两个指标，如：
- ADX-是最强大、最准确的趋势指标之一。ADX衡量趋势的强度，并能提供关于是否存在潜在交易机会的有价值信息。
- 云图-这是我正在使用的新闻集指标之一。此指标有助于战略，此指标旨在指示正确的市场趋势。通过应用这一指标的长度，我能够在稍晚的时候，但更准确地注意到趋势的变化。
此外，我还增加了尾随止损，以实现最大安全性。
老实说，这个策略看起来真的很好，很多交易，高利润和少量的指标，未来的利润可能是相似的
使用SMA的这种组合可以让我快速做出惊人的改变，同时趋势也在快速变化。不幸的是，我无法在平面图上100%地消除错误信号。
我希望这个策略对任何人都有用；）
回测测试
策略源码
/*backtest
start: 2022-02-23 00:00:00
end: 2022-05-23 00:00:00
period: 30m
basePeriod: 15m
exchanges: [{"eid":"Futures_CTP","currency":"FUTURES"}]
args: [["ContractType","i888",360008]]
*/
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © wielkieef
//@version=4
src = close
//strategy("Sma BTC killer [60MIN]", overlay = true, pyramiding=1,initial_capital = 10000, default_qty_type= strategy.percent_of_equity, default_qty_value = 100, calc_on_order_fills=false, slippage=0,commission_type=strategy.commission.percent,commission_value=0.04)
//SMAs -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Length1 = input(14, title=" 1-SMA 周期", minval=1)
Length2 = input(28, title=" 2-SMA 周期", minval=1)
Length3 = input(55, title=" 3-SMA 周期", minval=1)
xPrice = close
SMA1 = sma(xPrice, Length1)
SMA2 = sma(xPrice, Length2)
SMA3 = sma(xPrice, Length3)
//Indicators Inputs -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
ADX_options = input("MASANAKAMURA", title=" Adx 类型", options = ["CLASSIC", "MASANAKAMURA"], group="Average Directional Index")
ADX_len = input(29, title=" Adx 周期", type=input.integer, minval = 1, group="Average Directional Index")
th = input(21, title=" Adx Treshold", type=input.integer, minval = 0, group="Average Directional Index")
len = input(11, title="Cloud 长度", group="Cloud")
// ATR Inputs -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
prd = input(18, title=" PP 周期", group="Average True Range")
Factor = input(5, title=" ATR 系数", group="Average True Range")
Pd = input(6, title=" ATR 周期", group="Average True Range")
//Indicators -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
calcADX(_len) =>
up = change(high)
down = -change(low)
plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)
truerange = rma(tr, _len)
_plus = fixnan(100 * rma(plusDM, _len) / truerange)
_minus = fixnan(100 * rma(minusDM, _len) / truerange)
sum = _plus + _minus
_adx = 100 * rma(abs(_plus - _minus) / (sum == 0 ? 1 : sum), _len)
[_plus,_minus,_adx]
calcADX_Masanakamura(_len) =>
SmoothedTrueRange = 0.0
SmoothedDirectionalMovementPlus = 0.0
SmoothedDirectionalMovementMinus = 0.0
TrueRange = max(max(high - low, abs(high - nz(close[1]))), abs(low - nz(close[1])))
DirectionalMovementPlus = high - nz(high[1]) > nz(low[1]) - low ? max(high - nz(high[1]), 0) : 0
DirectionalMovementMinus = nz(low[1]) - low > high - nz(high[1]) ? max(nz(low[1]) - low, 0) : 0
SmoothedTrueRange := nz(SmoothedTrueRange[1]) - (nz(SmoothedTrueRange[1]) /_len) + TrueRange
SmoothedDirectionalMovementPlus := nz(SmoothedDirectionalMovementPlus[1]) - (nz(SmoothedDirectionalMovementPlus[1]) / _len) + DirectionalMovementPlus
SmoothedDirectionalMovementMinus := nz(SmoothedDirectionalMovementMinus[1]) - (nz(SmoothedDirectionalMovementMinus[1]) / _len) + DirectionalMovementMinus
DIP = SmoothedDirectionalMovementPlus / SmoothedTrueRange * 100
DIM = SmoothedDirectionalMovementMinus / SmoothedTrueRange * 100
DX = abs(DIP-DIM) / (DIP+DIM)*100
adx = sma(DX, _len)
[DIP,DIM,adx]
[DIPlusC,DIMinusC,ADXC] = calcADX(ADX_len)
[DIPlusM,DIMinusM,ADXM] = calcADX_Masanakamura(ADX_len)
DIPlus = ADX_options == "CLASSIC" ? DIPlusC : DIPlusM
DIMinus = ADX_options == "CLASSIC" ? DIMinusC : DIMinusM
ADX = ADX_options == "CLASSIC" ? ADXC : ADXM
L_adx = DIPlus > DIMinus and ADX > th
S_adx = DIPlus < DIMinus and ADX > th
ADX_COLOR = L_adx ? color.lime : S_adx ? color.red : color.orange
PI = 2 * asin(1)
hilbertTransform(src) =>
0.0962 * src + 0.5769 * nz(src[2]) - 0.5769 * nz(src[4]) - 0.0962 * nz(src[6])
computeComponent(src, mesaPeriodMult) =>
hilbertTransform(src) * mesaPeriodMult
computeAlpha(src, fastLimit, slowLimit) =>
mesaPeriod = 0.0
mesaPeriodMult = 0.075 * nz(mesaPeriod[1]) + 0.54
smooth = 0.0
smooth := (4 * src + 3 * nz(src[1]) + 2 * nz(src[2]) + nz(src[3])) / 10
detrender = 0.0
detrender := computeComponent(smooth, mesaPeriodMult)
I1 = nz(detrender[3])
Q1 = computeComponent(detrender, mesaPeriodMult)
jI = computeComponent(I1, mesaPeriodMult)
jQ = computeComponent(Q1, mesaPeriodMult)
I2 = 0.0
Q2 = 0.0
I2 := I1 - jQ
Q2 := Q1 + jI
I2 := 0.2 * I2 + 0.8 * nz(I2[1])
Q2 := 0.2 * Q2 + 0.8 * nz(Q2[1])
Re = I2 * nz(I2[1]) + Q2 * nz(Q2[1])
Im = I2 * nz(Q2[1]) - Q2 * nz(I2[1])
Re := 0.2 * Re + 0.8 * nz(Re[1])
Im := 0.2 * Im + 0.8 * nz(Im[1])
if Re != 0 and Im != 0
mesaPeriod := 2 * PI / atan(Im / Re)
if mesaPeriod > 1.5 * nz(mesaPeriod[1])
mesaPeriod := 1.5 * nz(mesaPeriod[1])
if mesaPeriod < 0.67 * nz(mesaPeriod[1])
mesaPeriod := 0.67 * nz(mesaPeriod[1])
if mesaPeriod < 6
mesaPeriod := 6
if mesaPeriod > 50
mesaPeriod := 50
mesaPeriod := 0.2 * mesaPeriod + 0.8 * nz(mesaPeriod[1])
phase = 0.0
if I1 != 0
phase := (180 / PI) * atan(Q1 / I1)
deltaPhase = nz(phase[1]) - phase
if deltaPhase < 1
deltaPhase := 1
alpha = fastLimit / deltaPhase
if alpha < slowLimit
alpha := slowLimit
[alpha,alpha/2.0]
er = abs(change(src,len)) / sum(abs(change(src)),len)
[a,b] = computeAlpha(src, er, er*0.1)
mama = 0.0
mama := a * src + (1 - a) * nz(mama[1])
fama = 0.0
fama := b * mama + (1 - b) * nz(fama[1])
alpha = pow((er * (b - a)) + a, 2)
kama = 0.0
kama := alpha * src + (1 - alpha) * nz(kama[1])
L_cloud = kama > kama[1]
S_cloud = kama < kama[1]
float ph = pivothigh(prd, prd)
float pl = pivotlow(prd, prd)
var float center = na
float lastpp = ph ? ph : pl ? pl : na
if lastpp
if na(center)
center := lastpp
else
center := (center * 2 + lastpp) / 3
Up = center - (Factor * atr(Pd))
Dn = center + (Factor * atr(Pd))
float TUp = na
float TDown = na
Trend = 0
TUp := close[1] > TUp[1] ? max(Up, TUp[1]) : Up
TDown := close[1] < TDown[1] ? min(Dn, TDown[1]) : Dn
Trend := close > TDown[1] ? 1: close < TUp[1]? -1: nz(Trend[1], 1)
Trailingsl = Trend == 1 ? TUp : TDown
bsignal = Trend == 1 and Trend[1] == -1
ssignal = Trend == -1 and Trend[1] == 1
L_ATR = Trend == 1
S_ATR = Trend == -1
// Strategy logic ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
var bool longCond = na, var bool shortCond = na
var int CondIni_long = 0, var int CondIni_short = 0
var bool _Final_longCondition = na, var bool _Final_shortCondition = na
var float last_open_longCondition = na, var float last_open_shortCondition = na
var int last_longCondition = na, var int last_shortCondition = na
var int last_Final_longCondition = na, var int last_Final_shortCondition = na
var int nLongs = na, var int nShorts = na
Long_MA =L_adx and L_cloud and (SMA1 < close and SMA2 < close and SMA3 < close )
Short_MA =S_adx and S_cloud and (SMA1 > close and SMA2 > close and SMA3 > close )
longCond := Long_MA
shortCond := Short_MA
CondIni_long := longCond[1] ? 1 : shortCond[1] ? -1 : nz(CondIni_long[1] )
CondIni_short := longCond[1] ? 1 : shortCond[1] ? -1 : nz(CondIni_short[1] )
longCondition = (longCond[1] and nz(CondIni_long[1]) == -1 )
shortCondition = (shortCond[1] and nz(CondIni_short[1]) == 1 )
var float sum_long = 0.0, var float sum_short = 0.0
var float Position_Price = 0.0
var bool Final_long_BB = na, var bool Final_short_BB = na
var int last_long_BB = na, var int last_short_BB = na
last_open_longCondition := longCondition or Final_long_BB[1] ? close[1] : nz(last_open_longCondition[1] )
last_open_shortCondition := shortCondition or Final_short_BB[1] ? close[1] : nz(last_open_shortCondition[1] )
last_longCondition := longCondition or Final_long_BB[1] ? time : nz(last_longCondition[1] )
last_shortCondition := shortCondition or Final_short_BB[1] ? time : nz(last_shortCondition[1] )
in_longCondition = last_longCondition > last_shortCondition
in_shortCondition = last_shortCondition > last_longCondition
last_Final_longCondition := longCondition ? time : nz(last_Final_longCondition[1] )
last_Final_shortCondition := shortCondition ? time : nz(last_Final_shortCondition[1] )
nLongs := nz(nLongs[1] )
nShorts := nz(nShorts[1] )
if longCondition or Final_long_BB
nLongs := nLongs + 1
nShorts := 0
sum_long := nz(last_open_longCondition) + nz(sum_long[1])
sum_short := 0.0
if shortCondition or Final_short_BB
nLongs := 0
nShorts := nShorts + 1
sum_short := nz(last_open_shortCondition)+ nz(sum_short[1])
sum_long := 0.0
Position_Price := nz(Position_Price[1])
Position_Price := longCondition or Final_long_BB ? sum_long/nLongs : shortCondition or Final_short_BB ? sum_short/nShorts : na
ATR_L_STOP = ssignal and in_longCondition
ATR_S_STOP = bsignal and in_shortCondition
// Plots and colors 010101010101010010101010101010101010101001010101010101001010101001010100101100111100101010010100110110010011100101010101010010101010101001011110011010101010101001010100101100110101010001001010101001010101001110110010101010100101010101010100111110101010101010101010100101010101100
colors = (in_longCondition ? color.green : in_shortCondition ? color.red : color.orange)
bgcolor(color=colors)
//barcolor (color = colors)
plotshape(longCondition, title="Long", style=shape.triangleup, location=location.belowbar, color=color.blue, size=size.small , transp = 0 )
plotshape(shortCondition, title="Short", style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small , transp = 0 )
mama_p = plot(mama, title="Cloud A", style= plot.style_stepline, color=colors )
fama_p = plot(fama, title="Cloud B", style= plot.style_stepline, color=colors )
fill (mama_p,fama_p, color=colors )
plot(SMA1, color=color.white,style= plot.style_stepline, title="5", linewidth=1)
plot(SMA2, color=color.gray,style= plot.style_stepline, title="15", linewidth=2)
plot(SMA3, color=color.black,style= plot.style_stepline, title="55", linewidth=3)
plotshape(ATR_L_STOP, title = "ATR LONG CLOSE", style=shape.arrowdown, location=location.abovebar, color=color.red, size=size.small , text="ATR LONG CLOSE", textcolor=color.red, transp = 0 )
plotshape(ATR_S_STOP, title = "ATR SHORT CLOSE", style=shape.arrowup, location=location.belowbar, color=color.blue, size=size.small, text="ATR SHORT CLOSE", textcolor=color.blue, transp = 0 )
// Strategy -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
if Long_MA
strategy.entry ("L", strategy.long)
if Short_MA
strategy.entry ("S", strategy.short)
strategy.close_all( when = ATR_L_STOP or ATR_S_STOP)
// By wielkieef
相关推荐
- 最佳TV策略
- 二重超级趋势
- Chande Kroll 止损
- 吊灯出场
- baguette by multigrain 策略
- EMA和ADX的三倍超趋势策略
- 彩色的移动平均指标EMA/SMA
- 超级投机者
- K的反转指示器I
- SAR + 3SMMA 和 SL & TP
更多内容