Strategi ini menggabungkan pelbagai purata bergerak untuk melaksanakan strategi trend berikut yang mudah.
Strategi ini mula-mula meratakan harga penutupan, dengan pilihan untuk menggunakan harga penutupan Heiken Ashi. Kemudian ia memanggil fungsi smoothMA untuk melapisi pelbagai purata bergerak halus. Fungsi smoothMA mula-mula memanggil fungsi varian, yang boleh menghasilkan pelbagai jenis purata bergerak seperti SMA, EMA, DEMA dan lain-lain. Selepas fungsi varian menghasilkan purata bergerak yang ditentukan, smoothMA secara berulang memanggil varian beberapa kali untuk melapisi penutupan. Ini menghasilkan purata bergerak dengan tahap kelancaran yang tinggi.
Pertimbangkan untuk menggabungkan penunjuk lain seperti MACD, KDJ untuk meningkatkan ketepatan isyarat. Mengoptimumkan parameter MA untuk mengurangkan lag. Gunakan stop loss yang munasabah untuk mengawal kerugian perdagangan tunggal. Juga mengawal kekerapan perdagangan untuk meminimumkan kos transaksi.
Strategi ini mengikuti trend melalui pelbagai lapisan purata bergerak, dengan berkesan menapis bunyi bising pasaran. Kelebihannya adalah kesederhanaan dan fleksibiliti. Tetapi bergantung hanya pada MA mempunyai keuntungan yang terhad. Pertimbangkan untuk menggabungkan dengan penunjuk lain, menguruskan risiko dan mengoptimumkan parameter untuk meningkatkan kecekapan.
/*backtest start: 2022-10-30 00:00:00 end: 2023-11-05 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=4 // Copyright (c) 2007-present Jurik Research and Consulting. All rights reserved. // Copyright (c) 2018-present, Alex Orekhov (everget) // Thanks to everget for code for more advanced moving averages // Smooth Moving Average [STRATEGY] @PuppyTherapy script may be freely distributed under the MIT license. strategy( title="Smooth Moving Average [STRATEGY] @PuppyTherapy", overlay=true ) // ---- CONSTANTS ---- lsmaOffset = 1 almaOffset = 0.85 almaSigma = 6 phase = 2 power = 2 // ---- GLOBAL FUNCTIONS ---- kama(src, len)=> xvnoise = abs(src - src[1]) nfastend = 0.666 nslowend = 0.0645 nsignal = abs(src - src[len]) nnoise = sum(xvnoise, len) nefratio = iff(nnoise != 0, nsignal / nnoise, 0) nsmooth = pow(nefratio * (nfastend - nslowend) + nslowend, 2) nAMA = 0.0 nAMA := nz(nAMA[1]) + nsmooth * (src - nz(nAMA[1])) t3(src, len)=> xe1_1 = ema(src, len) xe2_1 = ema(xe1_1, len) xe3_1 = ema(xe2_1, len) xe4_1 = ema(xe3_1, len) xe5_1 = ema(xe4_1, len) xe6_1 = ema(xe5_1, len) b_1 = 0.7 c1_1 = -b_1*b_1*b_1 c2_1 = 3*b_1*b_1+3*b_1*b_1*b_1 c3_1 = -6*b_1*b_1-3*b_1-3*b_1*b_1*b_1 c4_1 = 1+3*b_1+b_1*b_1*b_1+3*b_1*b_1 nT3Average_1 = c1_1 * xe6_1 + c2_1 * xe5_1 + c3_1 * xe4_1 + c4_1 * xe3_1 // The general form of the weights of the (2m + 1)-term Henderson Weighted Moving Average getWeight(m, j) => numerator = 315 * (pow(m + 1, 2) - pow(j, 2)) * (pow(m + 2, 2) - pow(j, 2)) * (pow(m + 3, 2) - pow(j, 2)) * (3 * pow(m + 2, 2) - 11 * pow(j, 2) - 16) denominator = 8 * (m + 2) * (pow(m + 2, 2) - 1) * (4 * pow(m + 2, 2) - 1) * (4 * pow(m + 2, 2) - 9) * (4 * pow(m + 2, 2) - 25) denominator != 0 ? numerator / denominator : 0 hwma(src, termsNumber) => sum = 0.0 weightSum = 0.0 termMult = (termsNumber - 1) / 2 for i = 0 to termsNumber - 1 weight = getWeight(termMult, i - termMult) sum := sum + nz(src[i]) * weight weightSum := weightSum + weight sum / weightSum get_jurik(length, phase, power, src)=> phaseRatio = phase < -100 ? 0.5 : phase > 100 ? 2.5 : phase / 100 + 1.5 beta = 0.45 * (length - 1) / (0.45 * (length - 1) + 2) alpha = pow(beta, power) jma = 0.0 e0 = 0.0 e0 := (1 - alpha) * src + alpha * nz(e0[1]) e1 = 0.0 e1 := (src - e0) * (1 - beta) + beta * nz(e1[1]) e2 = 0.0 e2 := (e0 + phaseRatio * e1 - nz(jma[1])) * pow(1 - alpha, 2) + pow(alpha, 2) * nz(e2[1]) jma := e2 + nz(jma[1]) variant(src, type, len ) => v1 = sma(src, len) // Simple v2 = ema(src, len) // Exponential v3 = 2 * v2 - ema(v2, len) // Double Exponential v4 = 3 * (v2 - ema(v2, len)) + ema(ema(v2, len), len) // Triple Exponential v5 = wma(src, len) // Weighted v6 = vwma(src, len) // Volume Weighted v7 = na(v5[1]) ? sma(src, len) : (v5[1] * (len - 1) + src) / len // Smoothed v8 = wma(2 * wma(src, len / 2) - wma(src, len), round(sqrt(len))) // Hull v9 = linreg(src, len, lsmaOffset) // Least Squares v10 = alma(src, len, almaOffset, almaSigma) // Arnaud Legoux v11 = kama(src, len) // KAMA ema1 = ema(src, len) ema2 = ema(ema1, len) v13 = t3(src, len) // T3 v14 = ema1+(ema1-ema2) // Zero Lag Exponential v15 = hwma(src, len) // Henderson Moving average thanks to @everget ahma = 0.0 ahma := nz(ahma[1]) + (src - (nz(ahma[1]) + nz(ahma[len])) / 2) / len //Ahrens Moving Average v16 = ahma v17 = get_jurik( len, phase, power, src) type=="EMA"?v2 : type=="DEMA"?v3 : type=="TEMA"?v4 : type=="WMA"?v5 : type=="VWMA"?v6 : type=="SMMA"?v7 : type=="Hull"?v8 : type=="LSMA"?v9 : type=="ALMA"?v10 : type=="KAMA"?v11 : type=="T3"?v13 : type=="ZEMA"?v14 : type=="HWMA"?v15 : type=="AHMA"?v16 : type=="JURIK"?v17 : v1 smoothMA(c, maLoop, type, len) => ma_c = 0.0 if maLoop == 1 ma_c := variant(c, type, len) if maLoop == 2 ma_c := variant(variant(c ,type, len),type, len) if maLoop == 3 ma_c := variant(variant(variant(c ,type, len),type, len),type, len) if maLoop == 4 ma_c := variant(variant(variant(variant(c ,type, len),type, len),type, len),type, len) if maLoop == 5 ma_c := variant(variant(variant(variant(variant(c ,type, len),type, len),type, len),type, len),type, len) ma_c // Smoothing HA Function smoothHA( o, h, l, c ) => hao = 0.0 hac = ( o + h + l + c ) / 4 hao := na(hao[1])?(o + c / 2 ):(hao[1] + hac[1])/2 hah = max(h, max(hao, hac)) hal = min(l, min(hao, hac)) [hao, hah, hal, hac] // ---- Main Selection ---- haSmooth = input(false, title=" Use HA as source ? " ) length = input(60, title=" MA1 Length", minval=1, maxval=1000) maLoop = input(2, title=" Nr. of MA1 Smoothings ", minval=1, maxval=5) type = input("EMA", title="MA Type", options=["SMA", "EMA", "DEMA", "TEMA", "WMA", "VWMA", "SMMA", "Hull", "LSMA", "ALMA", "KAMA", "ZEMA", "HWMA", "AHMA", "JURIK", "T3"]) // ---- BODY SCRIPT ---- [ ha_open, ha_high, ha_low, ha_close ] = smoothHA(open, high, low, close) _close_ma = haSmooth ? ha_close : close _close_smoothed_ma = smoothMA( _close_ma, maLoop, type, length) maColor = _close_smoothed_ma > _close_smoothed_ma[1] ? color.lime : color.red plot(_close_smoothed_ma, title= "MA - Trend", color=maColor, transp=85, linewidth = 4) long = _close_smoothed_ma > _close_smoothed_ma[1] and _close_smoothed_ma[1] < _close_smoothed_ma[2] short = _close_smoothed_ma < _close_smoothed_ma[1] and _close_smoothed_ma[1] > _close_smoothed_ma[2] plotshape( short , title="Short", color=color.red, transp=80, style=shape.triangledown, location=location.abovebar, size=size.small) plotshape( long , title="Long", color=color.lime, transp=80, style=shape.triangleup, location=location.belowbar, size=size.small) //* Backtesting Period Selector | Component *// //* Source: https://www.tradingview.com/script/eCC1cvxQ-Backtesting-Period-Selector-Component *// testStartYear = input(2018, "Backtest Start Year",minval=1980) testStartMonth = input(1, "Backtest Start Month",minval=1,maxval=12) testStartDay = input(1, "Backtest Start Day",minval=1,maxval=31) testPeriodStart = timestamp(testStartYear,testStartMonth,testStartDay,0,0) testStopYear = 9999 //input(9999, "Backtest Stop Year",minval=1980) testStopMonth = 12 // input(12, "Backtest Stop Month",minval=1,maxval=12) testStopDay = 31 //input(31, "Backtest Stop Day",minval=1,maxval=31) testPeriodStop = timestamp(testStopYear,testStopMonth,testStopDay,0,0) testPeriod() => time >= testPeriodStart and time <= testPeriodStop ? true : false if testPeriod() and long strategy.entry( "long", strategy.long ) if testPeriod() and short strategy.entry( "short", strategy.short )