Strategi Crossover Rata-rata Gerak Dinamis Momentum Tertimbang
Penulis:ChaoZhang, Tanggal: 2024-01-12 12:04:55Tag:
Gambaran umum
Strategi ini menghasilkan sinyal beli dan jual ketika dua Moving Average of Exponential Moving Averages (MAEMA) dengan periode yang berbeda bersilang.
Prinsip-prinsip
- Menghitung MAEMA cepat (80 periode) dan MAEMA lambat (144 periode).
- Garis cepat mencerminkan tren jangka pendek dan titik pembalikan Garis lambat mencerminkan arah tren utama.
- Ketika garis cepat melintasi di atas garis lambat, sinyal beli dihasilkan.
- Strategi ini juga memetakan tiga poin yang diprediksi, yang mewakili kemungkinan nilai untuk periode berikutnya, untuk menentukan tren crossover di masa depan.
- Strategi ini memanfaatkan momentum dan fungsi prediktif MAEMA itu sendiri.
Keuntungan
- MAEMA sendiri menggabungkan faktor momentum untuk menangkap perubahan tren lebih cepat.
- Strategi rata-rata bergerak ganda menilai tren dalam jangka waktu yang berbeda.
- Menggabungkan penyeberangan garis cepat dan lambat dan titik prediktif MAEMA sendiri membuat sinyal perdagangan lebih dapat diandalkan.
- Auto-charting lengkap memberikan refleksi intuitif dari fluktuasi pasar.
Risiko
- Ketika terjadi volatilitas abnormal, sensitivitas MAEMA mungkin terlalu tinggi, menghasilkan sinyal palsu.
- Sistem rata-rata bergerak cenderung memberikan sinyal palsu selama pasar yang terikat rentang. Filter tambahan dapat ditambahkan.
- Periode untuk jalur cepat dan lambat harus ditentukan dengan menemukan parameter optimal untuk setiap produk.
Peningkatan
- Mengoptimalkan periode MAEMA cepat dan lambat untuk menemukan kombinasi parameter terbaik.
- Tambahkan kondisi filter untuk menghindari posisi pembukaan selama pasar zigzag.
- Teruslah menyesuaikan kelipatan ATR, berhenti di belakang berdasarkan hasil backtest untuk mengurangi positif palsu dan mengendalikan risiko.
Ringkasan
Strategi ini menilai perubahan tren pasar dengan menggunakan crossover rata-rata bergerak ganda MAEMA. Prinsip dasarnya sederhana dan jelas. Dikombinasikan dengan momentum dan kemampuan prediktif MAEMA itu sendiri, strategi ini efektif dalam mengidentifikasi sinyal pembalikan. Perhatian harus diberikan pada optimasi parameter dan peningkatan filter untuk meningkatkan ketahanan.
/*backtest
start: 2023-12-12 00:00:00
end: 2024-01-11 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// © informanerd
//@version=4
strategy("MultiType Shifting Predictive MAs Crossover", shorttitle = "MTSPMAC + MBHB Strategy", overlay = true)
//inputs
predict = input(true, "Show MA Prediction Tails")
trendFill = input(true, "Fill Between MAs Based on Trend")
signal = input(true, "Show Cross Direction Signals")
showMA1 = input(true, "[ Show Fast Moving Average ]══════════")
type1 = input("MAEMA (Momentum Adjusted Exponential)", "Fast MA Type", options = ["MAEMA (Momentum Adjusted Exponential)", "DEMA (Double Exponential)", "EMA (Exponential)", "HMA (Hull)", "LSMA (Least Squares)", "RMA (Adjusted Exponential)", "SMA (Simple)", "SWMA (Symmetrically Weighted)", "TEMA (Triple Exponential)", "TMA (Triangular)", "VMA / VIDYA (Variable Index Dynamic Average)", "VWMA (Volume Weighted)", "WMA (Weighted)"])
src1 = input(high, "Fast MA Source")
len1 = input(80, "Fast MA Length", minval = 2)
shift1 = input(0, "Fast MA Shift")
maThickness1 = input(2, "Fast MA Thickness", minval = 1)
trendColor1 = input(false, "Color Fast MA Based on Detected Trend")
showBand1 = input(false, "Show Fast MA Range Band")
atrPer1 = input(20, "Fast Band ATR Lookback Period")
atrMult1 = input(3, "Fast Band ATR Multiplier")
showMA2 = input(true, "[ Show Slow Moving Average ]══════════")
type2 = input("MAEMA (Momentum Adjusted Exponential)", "Slow MA Type", options = ["MAEMA (Momentum Adjusted Exponential)", "DEMA (Double Exponential)", "EMA (Exponential)", "HMA (Hull)", "LSMA (Least Squares)", "RMA (Adjusted Exponential)", "SMA (Simple)", "SWMA (Symmetrically Weighted)", "TEMA (Triple Exponential)", "TMA (Triangular)", "VMA / VIDYA (Variable Index Dynamic Average)", "VWMA (Volume Weighted)", "WMA (Weighted)"])
src2 = input(close, "Slow MA Source")
len2 = input(144, "Slow MA Length", minval = 2)
shift2 = input(0, "Slow MA Shift")
maThickness2 = input(2, "Slow MA Thickness", minval = 1)
trendColor2 = input(false, "Color Slow MA Based on Detected Trend")
showBand2 = input(false, "Show Slow MA Range Band")
atrPer2 = input(20, "Slow Band ATR Lookback Period")
atrMult2 = input(3, "Slow Band ATR Multiplier")
//ma calculations
ma(type, src, len) =>
if type == "MAEMA (Momentum Adjusted Exponential)"
goldenRatio = (1 + sqrt(5)) / 2
momentumLen = round(len / goldenRatio), momentum = change(src, momentumLen), probabilityLen = len / goldenRatio / goldenRatio
ema(src + (momentum + change(momentum, momentumLen) * 0.5) * sum(change(src) > 0 ? 1 : 0, round(probabilityLen)) / probabilityLen, len)
else if type == "DEMA (Double Exponential)"
2 * ema(src, len) - ema(ema(src, len), len)
else if type == "EMA (Exponential)"
ema(src, len)
else if type == "HMA (Hull)"
wma(2 * wma(src, len / 2) - wma(src, len), round(sqrt(len)))
else if type == "LSMA (Least Squares)"
3 * wma(src, len) - 2 * sma(src, len)
else if type == "RMA (Adjusted Exponential)"
rma(src, len)
else if type == "SMA (Simple)"
sma(src, len)
else if type == "SWMA (Symmetrically Weighted)"
swma(src)
else if type == "TEMA (Triple Exponential)"
3 * ema(src, len) - 3 * ema(ema(src, len), len) + ema(ema(ema(src, len), len), len)
else if type == "TMA (Triangular)"
swma(wma(src, len))
else if type == "VMA / VIDYA (Variable Index Dynamic Average)"
smoothing = 2 / len, volIndex = abs(cmo(src, len) / 100)
vma = 0., vma := (smoothing * volIndex * src) + (1 - smoothing * volIndex) * nz(vma[1])
else if type == "VWMA (Volume Weighted)"
vwma(src, len)
else if type == "WMA (Weighted)"
wma(src, len)
ma1 = ma(type1, src1, len1)
ma2 = ma(type2, src2, len2)
//ma predictions
pma11 = len1 > 2 ? (ma(type1, src1, len1 - 1) * (len1 - 1) + src1 * 1) / len1 : na
pma12 = len1 > 3 ? (ma(type1, src1, len1 - 2) * (len1 - 2) + src1 * 2) / len1 : na
pma13 = len1 > 4 ? (ma(type1, src1, len1 - 3) * (len1 - 3) + src1 * 3) / len1 : na
pma21 = len2 > 2 ? (ma(type2, src2, len2 - 1) * (len2 - 1) + src2 * 1) / len2 : na
pma22 = len2 > 3 ? (ma(type2, src2, len2 - 2) * (len2 - 2) + src2 * 2) / len2 : na
pma23 = len2 > 4 ? (ma(type2, src2, len2 - 3) * (len2 - 3) + src2 * 3) / len2 : na
//ma range bands
r1 = atr(atrPer1) * atrMult1
hBand1 = ma1 + r1
lBand1 = ma1 - r1
r2 = atr(atrPer2) * atrMult2
hBand2 = ma2 + r2
lBand2 = ma2 - r2
//drawings
ma1Plot = plot(showMA1 ? ma1 : na, "Fast MA", trendColor1 and ma1 > src1 ? color.maroon : trendColor1 and ma1 < src1 ? color.lime : trendColor1 ? color.gray : color.red, maThickness1, offset = shift1)
ma2Plot = plot(showMA2 ? ma2 : na, "Slow MA", trendColor2 and ma2 > src2 ? color.maroon : trendColor2 and ma2 < src2 ? color.lime : trendColor2 ? color.gray : color.green, maThickness2, offset = shift2)
fill(ma1Plot, ma2Plot, trendFill and ma1 > ma2 ? color.lime : trendFill and ma1 < ma2 ? color.maroon : na, 90)
plot(showMA1 and predict ? pma11 : na, "PossibleMA1-1", trendColor1 and ma1 > src1 ? color.maroon : trendColor1 and ma1 < src1 ? color.lime : trendColor1 ? color.gray : color.red, style = plot.style_circles, offset = shift1 + 1, show_last = 1)
plot(showMA1 and predict ? pma12 : na, "PossibleMA1-2", trendColor1 and ma1 > src1 ? color.maroon : trendColor1 and ma1 < src1 ? color.lime : trendColor1 ? color.gray : color.red, style = plot.style_circles, offset = shift1 + 2, show_last = 1)
plot(showMA1 and predict ? pma13 : na, "PossibleMA1-3", trendColor1 and ma1 > src1 ? color.maroon : trendColor1 and ma1 < src1 ? color.lime : trendColor1 ? color.gray : color.red, style = plot.style_circles, offset = shift1 + 3, show_last = 1)
plot(showMA2 and predict ? pma21 : na, "PossibleMA2-1", trendColor2 and ma2 > src2 ? color.maroon : trendColor2 and ma2 < src2 ? color.lime : trendColor2 ? color.gray : color.green, style = plot.style_circles, offset = shift2 + 1, show_last = 1)
plot(showMA2 and predict ? pma22 : na, "PossibleMA2-2", trendColor2 and ma2 > src2 ? color.maroon : trendColor2 and ma2 < src2 ? color.lime : trendColor2 ? color.gray : color.green, style = plot.style_circles, offset = shift2 + 2, show_last = 1)
plot(showMA2 and predict ? pma23 : na, "PossibleMA2-3", trendColor2 and ma2 > src2 ? color.maroon : trendColor2 and ma2 < src2 ? color.lime : trendColor2 ? color.gray : color.green, style = plot.style_circles, offset = shift2 + 3, show_last = 1)
plot(showBand1 ? hBand1 : na, "Fast Higher Band", trendColor1 and ma1 > src1 ? color.maroon : trendColor1 and ma1 < src1 ? color.lime : trendColor1 ? color.gray : color.red, offset = shift1)
plot(showBand1 ? lBand1 : na, "Fast Lower Band", trendColor1 and ma1 > src1 ? color.maroon : trendColor1 and ma1 < src1 ? color.lime : trendColor1 ? color.gray : color.red, offset = shift1)
plot(showBand2 ? hBand2 : na, "Slow Higher Band", trendColor2 and ma2 > src2 ? color.maroon : trendColor2 and ma2 < src2 ? color.lime : trendColor2 ? color.gray : color.green, offset = shift2)
plot(showBand2 ? lBand2 : na, "Slow Lower Band", trendColor2 and ma2 > src2 ? color.maroon : trendColor2 and ma2 < src2 ? color.lime : trendColor2 ? color.gray : color.green, offset = shift2)
//crosses & alerts
up = crossover(ma1, ma2)
down = crossover(ma2, ma1)
plotshape(signal ? up : na, "Buy", shape.triangleup, location.belowbar, color.green, offset = shift1, size = size.small)
plotshape(signal ? down : na, "Sell", shape.triangledown, location.abovebar, color.red, offset = shift1, size = size.small)
alertcondition(up, "Buy", "Buy")
alertcondition(down, "Sell", "Sell")
// @version=1
// Title: "Multi Bollinger Heat Bands - EMA/Breakout options".
// Author: JayRogers
//
// * Description *
// Short: It's your Basic Bollinger Bands, but 3 of them, and some pointy things.
//
// Long: Three stacked sma based Bollinger Bands designed just to give you a quick visual on the "heat" of movement.
// Set inner band as you would expect, then set your preferred additional multiplier increments for the outer 2 bands.
// Option to use EMA as alternative basis, rather than SMA.
// Breakout indication shapes, which have their own multiplier seperate from the BB's; but still tied to same length/period.
// strategy(shorttitle="[JR]MBHB_EBO", title="[JR] Multi Bollinger Heat Bands - EMA/Breakout options", overlay=true)
// Bollinger Bands Inputs
bb_use_ema = input(false, title="Use EMA Basis?")
bb_length = input(80, minval=1, title="Bollinger Length")
bb_source = input(close, title="Bollinger Source")
bb_mult = input(1.0, title="Base Multiplier", minval=0.001, maxval=50)
bb_mult_inc = input(1, title="Multiplier Increment", minval=0.001, maxval=2)
// Breakout Indicator Inputs
break_mult = input(3, title="Breakout Multiplier", minval=0.001, maxval=50)
breakhigh_source = input(high, title="High Break Source")
breaklow_source = input(low, title="Low Break Source")
bb_basis = bb_use_ema ? ema(bb_source, bb_length) : sma(bb_source, bb_length)
// Deviation
// * I'm sure there's a way I could write some of this cleaner, but meh.
dev = stdev(bb_source, bb_length)
bb_dev_inner = bb_mult * dev
bb_dev_mid = (bb_mult + bb_mult_inc) * dev
bb_dev_outer = (bb_mult + (bb_mult_inc * 2)) * dev
break_dev = break_mult * dev
// Upper bands
inner_high = bb_basis + bb_dev_inner
mid_high = bb_basis + bb_dev_mid
outer_high = bb_basis + bb_dev_outer
// Lower Bands
inner_low = bb_basis - bb_dev_inner
mid_low = bb_basis - bb_dev_mid
outer_low = bb_basis - bb_dev_outer
// Breakout Deviation
break_high = bb_basis + break_dev
break_low = bb_basis - break_dev
// plot basis
plot(bb_basis, title="Basis Line", color=color.yellow, transp=50)
// plot and fill upper bands
ubi = plot(inner_high, title="Upper Band Inner", color=color.red, transp=90)
ubm = plot(mid_high, title="Upper Band Middle", color=color.red, transp=85)
ubo = plot(outer_high, title="Upper Band Outer", color=color.red, transp=80)
fill(ubi, ubm, title="Upper Bands Inner Fill", color=color.red, transp=90)
fill(ubm, ubo, title="Upper Bands Outer Fill",color=color.red, transp=80)
// plot and fill lower bands
lbi = plot(inner_low, title="Lower Band Inner", color=color.green, transp=90)
lbm = plot(mid_low, title="Lower Band Middle", color=color.green, transp=85)
lbo = plot(outer_low, title="Lower Band Outer", color=color.green, transp=80)
fill(lbi, lbm, title="Lower Bands Inner Fill", color=color.green, transp=90)
fill(lbm, lbo, title="Lower Bands Outer Fill", color=color.green, transp=80)
// center channel fill
fill(ubi, lbi, title="Center Channel Fill", color=color.silver, transp=100)
// plot breakouts
plotshape(breakhigh_source >= break_high, title="High Breakout", style=shape.triangledown, location=location.abovebar, size=size.tiny, color=color.white, transp=0)
plotshape(breaklow_source <= break_low, title="Low Breakout", style=shape.triangleup, location=location.belowbar, size=size.tiny, color=color.white, transp=0)
High_Break = breakhigh_source >= break_high
Low_Break = breaklow_source <= break_low
// Conditions
Stop_Momentum = low < ma1
//Strategy Tester
strategy.entry("long", strategy.long, when=(up and (hlc3 < inner_high)))
strategy.close("long", when=down)
strategy.entry("longwickdown", strategy.long, when=Low_Break)
strategy.close("longwickdown", when=(high > ma1))
//true signals test
//var winCount = 0, var loseCount = 0, testBarIndex = 1
//if (up[testBarIndex] and close > close[testBarIndex]) or (down[testBarIndex] and close < close[testBarIndex])
// label.new(bar_index, 0, "W", yloc = yloc.abovebar, color = color.green)
// winCount := winCount + 1
//else if (up[testBarIndex] and close < close[testBarIndex]) or (down[testBarIndex] and close > close[testBarIndex])
// label.new(bar_index, 0, "L", yloc = yloc.abovebar, color = color.red)
// loseCount := loseCount + 1
//winRate = label.new(time + (time - time[1]) * 2, ohlc4, tostring(round(winCount / (winCount + loseCount) * 100)) + "%", xloc = xloc.bar_time, color = color.orange, style = label.style_label_left)
//if not na(winRate[1])
// label.delete(winRate[1])
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