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Stratégie de croisement des moyennes mobiles pondérées par dynamique

Auteur:ChaoZhang est là., Date: 12 janvier 2024
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Résumé

Cette stratégie génère des signaux d'achat et de vente lorsque deux moyennes mobiles de moyennes mobiles exponentielles (MAEMA) avec des périodes différentes se croisent.

Principaux

  1. Calculer le MAEMA rapide (80 périodes) et le MAEMA lent (144 périodes).
  2. La ligne rapide reflète la tendance à court terme et les points d'inversion.
  3. Lorsque la ligne rapide traverse au-dessus de la ligne lente, un signal d'achat est généré.
  4. La stratégie trace également 3 points prévus, représentant des valeurs possibles pour la période suivante, afin de déterminer la tendance future du croisement.
  5. La stratégie tire pleinement parti de la dynamique et de la fonctionnalité prédictive du MAEMA lui-même.

Les avantages

  1. Le MAEMA lui-même intègre le facteur de dynamique pour capturer plus rapidement les changements de tendance.
  2. La stratégie de la moyenne mobile double évalue les tendances sur différentes périodes.
  3. La combinaison de croisements de lignes rapides et lents et des points prédictifs du MAEMA lui-même rend les signaux de trading plus fiables.
  4. La cartographie automatique complète fournit un reflet intuitif des fluctuations du marché.

Les risques

  1. Lorsqu'une volatilité anormale se produit, la sensibilité du MAEMA peut être trop élevée, générant de faux signaux.
  2. Les systèmes de moyennes mobiles ont tendance à donner de faux signaux pendant les marchés à plage.
  3. Les périodes pour les lignes rapides et lentes devraient être déterminées en trouvant des paramètres optimaux pour chaque produit.

Amélioration

  1. Optimiser les périodes de MAEMA rapide et lente pour trouver les meilleures combinaisons de paramètres.
  2. Ajoutez des conditions de filtrage pour éviter d'ouvrir des positions pendant les marchés en zigzag.
  3. Continuer à ajuster les multiples ATR, les arrêts de trail basés sur les résultats des backtests afin de réduire les faux positifs et de contrôler les risques.

Résumé

La stratégie juge les changements de tendance du marché en utilisant des croisements de moyenne mobile doubles MAEMA. Les principes de base sont simples et clairs. Combinée à l'élan et aux capacités prédictives de MAEMA elle-même, elle est efficace pour identifier les signaux de renversement.

/*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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