This strategy is an improved version of the classic MACD indicator, using 11 different types of moving averages to smooth the price curve and reduce misleading signals. The indicator consists of the fast line, slow line and histogram. The fast line and slow line respectively adopt the fast moving average and slow moving average of prices. The histogram represents the difference between the fast line and slow line. Buying signals are generated when the fast line crosses the slow line from bottom to top, while selling signals are generated from top to bottom.
Calculate the fast moving average line MA12. 11 different calculation methods for moving average lines are available for selection, with Volume Variability Rate line VAR as default.
Calculate the slow moving average line MA26. 11 different calculation methods for moving average lines are available for selection, with Volume Variability Rate line VAR as default.
Calculate the difference between the fast and slow lines SRC2 = MA12 - MA26.
Calculate the trigger line MATR for SRC2 using a moving average line with length of 9. 11 different calculation methods are available for selection, with Volume Variability Rate line VAR as default.
Calculate the MACD histogram HIST = SRC2 - MATR. Buying signals are generated when the histogram changes from negative to positive. Selling signals are generated when the histogram changes from positive to negative.
11 different types of moving average lines can be selected to calculate the fast line, slow line and trigger line, which largely reduces the lagging of common moving averages and improves the accuracy of prediction signals.
The Volume Variability Rate line VAR can automatically adjust the weights of the moving average to better adapt to market changes.
The double moving average lines with buffer zone can effectively filter out market noise.
The MACD histogram as the triggering signal can overcome the lagging problem brought by the traditional crossing of fast and slow MACD lines.
MACD indicator has weak capability in judging the trending or consolidating market.
The moving average itself has a certain degree of lagging. VAR partially reduces but cannot completely solve the problem.
Error accumulation may lead to wrong signals or missing effective signals.
Choose matching moving average calculation methods for specific market conditions based on backtest results.
Optimize the length parameters of the fast line, slow line and trigger line to find the best parameter combinations to reduce wrong signals.
Add auxiliary indicators such as RSI and Bollinger Bands to confirm buy/sell signals.
This strategy is an optimized version for the classic MACD indicator. By using multiple moving average patterns to compute the MACD fast line, slow line and histogram, it greatly enhances the utility of this indicator. Meanwhile, it also has certain limitations. Continuous optimization catered to actual market conditions is needed to maximize the efficacy in trading.
/*backtest
start: 2023-11-12 00:00:00
end: 2023-12-12 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © KivancOzbilgic
//developer: Gerald Appel
//author: @kivancozbilgic
strategy("MACD ReLoaded","MACDRe", overlay=true)
src = input(close, title="Source")
length=input(12, "Short Moving Average Length", minval=1)
length1=input(26, "Long Moving Average Length", minval=1)
length2=input(9, "Trigger Length", minval=1)
T3a1 = input(0.7, "TILLSON T3 Volume Factor", step=0.1)
barcoloring = input(title="Bar Coloring On/Off ?", type=input.bool, defval=true)
mav = input(title="Moving Average Type", defval="VAR", options=["SMA", "EMA", "WMA", "DEMA", "TMA", "VAR", "WWMA", "ZLEMA", "TSF", "HULL", "TILL"])
Var_Func(src,length)=>
valpha=2/(length+1)
vud1=src>src[1] ? src-src[1] : 0
vdd1=src<src[1] ? src[1]-src : 0
vUD=sum(vud1,9)
vDD=sum(vdd1,9)
vCMO=nz((vUD-vDD)/(vUD+vDD))
VAR=0.0
VAR:=nz(valpha*abs(vCMO)*src)+(1-valpha*abs(vCMO))*nz(VAR[1])
VAR=Var_Func(src,length)
DEMA = ( 2 * ema(src,length)) - (ema(ema(src,length),length) )
Wwma_Func(src,length)=>
wwalpha = 1/ length
WWMA = 0.0
WWMA := wwalpha*src + (1-wwalpha)*nz(WWMA[1])
WWMA=Wwma_Func(src,length)
Zlema_Func(src,length)=>
zxLag = length/2==round(length/2) ? length/2 : (length - 1) / 2
zxEMAData = (src + (src - src[zxLag]))
ZLEMA = ema(zxEMAData, length)
ZLEMA=Zlema_Func(src,length)
Tsf_Func(src,length)=>
lrc = linreg(src, length, 0)
lrc1 = linreg(src,length,1)
lrs = (lrc-lrc1)
TSF = linreg(src, length, 0)+lrs
TSF=Tsf_Func(src,length)
HMA = wma(2 * wma(src, length / 2) - wma(src, length), round(sqrt(length)))
T3e1=ema(src, length)
T3e2=ema(T3e1,length)
T3e3=ema(T3e2,length)
T3e4=ema(T3e3,length)
T3e5=ema(T3e4,length)
T3e6=ema(T3e5,length)
T3c1=-T3a1*T3a1*T3a1
T3c2=3*T3a1*T3a1+3*T3a1*T3a1*T3a1
T3c3=-6*T3a1*T3a1-3*T3a1-3*T3a1*T3a1*T3a1
T3c4=1+3*T3a1+T3a1*T3a1*T3a1+3*T3a1*T3a1
T3=T3c1*T3e6+T3c2*T3e5+T3c3*T3e4+T3c4*T3e3
getMA(src, length) =>
ma = 0.0
if mav == "SMA"
ma := sma(src, length)
ma
if mav == "EMA"
ma := ema(src, length)
ma
if mav == "WMA"
ma := wma(src, length)
ma
if mav == "DEMA"
ma := DEMA
ma
if mav == "TMA"
ma := sma(sma(src, ceil(length / 2)), floor(length / 2) + 1)
ma
if mav == "VAR"
ma := VAR
ma
if mav == "WWMA"
ma := WWMA
ma
if mav == "ZLEMA"
ma := ZLEMA
ma
if mav == "TSF"
ma := TSF
ma
if mav == "HULL"
ma := HMA
ma
if mav == "TILL"
ma := T3
ma
ma
MA12=getMA(src, length)
Var_Func1(src,length1)=>
valpha1=2/(length1+1)
vud11=src>src[1] ? src-src[1] : 0
vdd11=src<src[1] ? src[1]-src : 0
vUD1=sum(vud11,9)
vDD1=sum(vdd11,9)
vCMO1=nz((vUD1-vDD1)/(vUD1+vDD1))
VAR1=0.0
VAR1:=nz(valpha1*abs(vCMO1)*src)+(1-valpha1*abs(vCMO1))*nz(VAR1[1])
VAR1=Var_Func1(src,length1)
DEMA1 = ( 2 * ema(src,length1)) - (ema(ema(src,length1),length1) )
Wwma_Func1(src,length1)=>
wwalpha1 = 1/ length1
WWMA1 = 0.0
WWMA1 := wwalpha1*src + (1-wwalpha1)*nz(WWMA1[1])
WWMA1=Wwma_Func1(src,length1)
Zlema_Func1(src,length1)=>
zxLag1 = length1/2==round(length1/2) ? length1/2 : (length1 - 1) / 2
zxEMAData1 = (src + (src - src[zxLag1]))
ZLEMA1 = ema(zxEMAData1, length1)
ZLEMA1=Zlema_Func1(src,length1)
Tsf_Func1(src,length1)=>
lrc1 = linreg(src, length1, 0)
lrc11 = linreg(src,length1,1)
lrs1 = (lrc1-lrc11)
TSF1 = linreg(src, length1, 0)+lrs1
TSF1=Tsf_Func1(src,length1)
HMA1 = wma(2 * wma(src, length1 / 2) - wma(src, length1), round(sqrt(length1)))
T3e11=ema(src, length1)
T3e21=ema(T3e11,length1)
T3e31=ema(T3e21,length1)
T3e41=ema(T3e31,length1)
T3e51=ema(T3e41,length1)
T3e61=ema(T3e51,length1)
T3c11=-T3a1*T3a1*T3a1
T3c21=3*T3a1*T3a1+3*T3a1*T3a1*T3a1
T3c31=-6*T3a1*T3a1-3*T3a1-3*T3a1*T3a1*T3a1
T3c41=1+3*T3a1+T3a1*T3a1*T3a1+3*T3a1*T3a1
T31=T3c11*T3e61+T3c21*T3e51+T3c31*T3e41+T3c41*T3e31
getMA1(src, length1) =>
ma1 = 0.0
if mav == "SMA"
ma1 := sma(src, length1)
ma1
if mav == "EMA"
ma1 := ema(src, length1)
ma1
if mav == "WMA"
ma1 := wma(src, length1)
ma1
if mav == "DEMA"
ma1 := DEMA1
ma1
if mav == "TMA"
ma1 := sma(sma(src, ceil(length1 / 2)), floor(length1 / 2) + 1)
ma1
if mav == "VAR"
ma1 := VAR1
ma1
if mav == "WWMA"
ma1:= WWMA1
ma1
if mav == "ZLEMA"
ma1 := ZLEMA1
ma1
if mav == "TSF"
ma1 := TSF1
ma1
if mav == "HULL"
ma1 := HMA1
ma1
if mav == "TILL"
ma1 := T31
ma1
ma1
MA26=getMA1(src, length1)
src2=MA12-MA26
Var_Func2(src2,length2)=>
valpha2=2/(length2+1)
vud12=src2>src2[1] ? src2-src2[1] : 0
vdd12=src2<src2[1] ? src2[1]-src2 : 0
vUD2=sum(vud12,9)
vDD2=sum(vdd12,9)
vCMO2=nz((vUD2-vDD2)/(vUD2+vDD2))
VAR2=0.0
VAR2:=nz(valpha2*abs(vCMO2)*src2)+(1-valpha2*abs(vCMO2))*nz(VAR2[1])
VAR2=Var_Func2(src2,length2)
DEMA2 = ( 2 * ema(src2,length2)) - (ema(ema(src2,length2),length2) )
Wwma_Func2(src2,length2)=>
wwalpha2 = 1/ length2
WWMA2 = 0.0
WWMA2 := wwalpha2*src2 + (1-wwalpha2)*nz(WWMA2[1])
WWMA2=Wwma_Func2(src2,length2)
Zlema_Func2(src2,length2)=>
zxLag2 = length2/2==round(length2/2) ? length2/2 : (length2 - 1) / 2
zxEMAData2 = (src2 + (src2 - src2[zxLag2]))
ZLEMA2 = ema(zxEMAData2, length2)
ZLEMA2=Zlema_Func2(src2,length2)
Tsf_Func2(src2,length2)=>
lrc2 = linreg(src2, length2, 0)
lrc12 = linreg(src2,length2,1)
lrs2 = (lrc2-lrc12)
TSF2 = linreg(src2, length2, 0)+lrs2
TSF2=Tsf_Func2(src2,length2)
HMA2 = wma(2 * wma(src2, length2 / 2) - wma(src2, length2), round(sqrt(length2)))
T3e12=ema(src2, length2)
T3e22=ema(T3e12,length2)
T3e32=ema(T3e22,length2)
T3e42=ema(T3e32,length2)
T3e52=ema(T3e42,length2)
T3e62=ema(T3e52,length2)
T3c12=-T3a1*T3a1*T3a1
T3c22=3*T3a1*T3a1+3*T3a1*T3a1*T3a1
T3c32=-6*T3a1*T3a1-3*T3a1-3*T3a1*T3a1*T3a1
T3c42=1+3*T3a1+T3a1*T3a1*T3a1+3*T3a1*T3a1
T32=T3c12*T3e62+T3c22*T3e52+T3c32*T3e42+T3c42*T3e32
getMA2(src2, length2) =>
ma2 = 0.0
if mav == "SMA"
ma2 := sma(src2, length2)
ma2
if mav == "EMA"
ma2 := ema(src2, length2)
ma2
if mav == "WMA"
ma2 := wma(src2, length2)
ma2
if mav == "DEMA"
ma2 := DEMA2
ma2
if mav == "TMA"
ma2 := sma(sma(src2, ceil(length2 / 2)), floor(length2 / 2) + 1)
ma2
if mav == "VAR"
ma2 := VAR2
ma2
if mav == "WWMA"
ma2 := WWMA2
ma2
if mav == "ZLEMA"
ma2 := ZLEMA2
ma2
if mav == "TSF"
ma2 := TSF2
ma2
if mav == "HULL"
ma2 := HMA2
ma2
if mav == "TILL"
ma2 := T32
ma2
ma2
MATR=getMA2(MA12-MA26, length2)
hist = src2 - MATR
FromMonth = input(defval = 9, title = "From Month", minval = 1, maxval = 12)
FromDay = input(defval = 1, title = "From Day", minval = 1, maxval = 31)
FromYear = input(defval = 2018, title = "From Year", minval = 999)
ToMonth = input(defval = 1, title = "To Month", minval = 1, maxval = 12)
ToDay = input(defval = 1, title = "To Day", minval = 1, maxval = 31)
ToYear = input(defval = 9999, title = "To Year", minval = 999)
start = timestamp(FromYear, FromMonth, FromDay, 00, 00)
finish = timestamp(ToYear, ToMonth, ToDay, 23, 59)
window() => time >= start and time <= finish ? true : false
buySignal = crossover(hist, 0)
if (crossover(hist, 0))
strategy.entry("MacdLong", strategy.long, comment="MacdLong")
sellSignal = crossunder(hist, 0)
if (crossunder(hist, 0))
strategy.entry("MacdShort", strategy.short, comment="MacdShort")
buy1= barssince(buySignal)
sell1 = barssince(sellSignal)
color1 = buy1[1] < sell1[1] ? color.green : buy1[1] > sell1[1] ? color.red : na
barcolor(barcoloring ? color1 : na)
//plot(strategy.equity, title="equity", color=color.red, linewidth=2, style=plot.style_areabr)