Strategi ini memanfaatkan sinyal kombinasi dari beberapa indikator teknis untuk secara dinamis memperdagangkan aset yang mendasari seperti saham dan cryptocurrency. Strategi ini dapat secara otomatis mengidentifikasi tren pasar dan melacaknya. Juga, mekanisme stop loss dimasukkan untuk mengendalikan risiko.
Strategi ini terutama memanfaatkan rata-rata bergerak, indeks kekuatan relatif (RSI), rentang sebenarnya rata-rata (ATR) dan indeks gerakan arah (ADX) untuk menghasilkan sinyal perdagangan.
Secara khusus, pertama-tama mengadopsi crossover rata-rata bergerak ganda untuk membentuk sinyal. Garis cepat memiliki panjang 10 hari dan garis lambat memiliki panjang 50 hari. Golden crossovers (garis cepat yang melanggar garis lambat dari bawah) menghasilkan sinyal beli sementara crossover mati menghasilkan sinyal jual. Sistem ini dapat secara efektif mengidentifikasi pembalikan tren jangka panjang.
Di atas MAs ganda, RSI diperkenalkan untuk mengkonfirmasi sinyal tren dan menghindari breakout palsu. RSI menilai kekuatan pasar dengan perbedaan antara garis cepat dan lambat. Ketika RSI melanggar di atas 30, sinyal beli dihasilkan. Ketika melanggar di bawah 70, sinyal jual dihasilkan.
Selain itu, ATR digunakan untuk secara otomatis menyesuaikan tingkat stop loss. ATR dapat secara efektif mencerminkan volatilitas pasar. Ketika volatilitas meningkat, stop loss yang lebih luas akan diatur untuk mengurangi probabilitas dihentikan.
Akhirnya, ADX mengukur kekuatan tren. ADX menggunakan divergensi antara indikator positif DI + dan indikator negatif DI- untuk mengukur kekuatan tren. Hanya ketika ADX melanggar di atas 20, tren dianggap telah ditetapkan dan sinyal perdagangan yang sebenarnya dihasilkan.
Dengan menggabungkan sinyal dari beberapa indikator, strategi dapat lebih bijaksana dalam mengirim sinyal perdagangan, menghindari gangguan dari sinyal palsu dan dengan demikian mencapai tingkat kemenangan yang lebih tinggi.
Keuntungan dari strategi ini meliputi:
Kombinasi MA, RSI, ATR, ADX dan lainnya dapat meningkatkan akurasi dan menghindari penilaian yang salah karena indikator tunggal.
Penyesuaian stop loss berdasarkan volatilitas pasar dapat mengurangi kemungkinan berhenti keluar dan mengelola risiko secara efektif.
Dengan menilai kekuatan tren dengan ADX sebelum perdagangan yang sebenarnya, kerugian dari perdagangan melawan tren dapat dikurangi.
Parameter seperti panjang MA, panjang RSI, periode ATR dan periode ADX semuanya dapat disesuaikan dan dioptimalkan untuk pasar yang berbeda.
Mengidentifikasi tren jangka panjang menggunakan sistem MA cepat dan lambat dan mengurangi kebisingan jangka pendek dengan indikator seperti RSI, memegang tren jangka panjang menjadi mungkin untuk keuntungan yang lebih tinggi.
Ada juga beberapa risiko yang terkait dengan strategi ini:
Lebih banyak parameter berarti kesulitan yang lebih besar dalam pengoptimalan. Set parameter yang tidak sesuai dapat memperburuk kinerja strategi. Backtesting yang lebih memadai dan penyesuaian parameter dapat mengurangi risiko ini.
Semua indikator teknis memiliki kondisi pasar yang berlaku. Ketika pasar memasuki keadaan yang aneh, indikator yang digunakan dapat gagal secara bersamaan. Risiko dari peristiwa BLACK SWAN semacam itu perlu diperhatikan.
Strategi ini memungkinkan perdagangan pendek. Posisi pendek secara inheren memiliki risiko kerugian tak terbatas. Hal ini dapat dikurangi dengan mengatur stop loss yang tepat.
Indikator tidak dapat segera merespons pembalikan. posisi arah yang salah sering menimbulkan kerugian selama pembalikan. memperpendek parameter beberapa indikator dapat meningkatkan sensitivitas.
Ada ruang untuk optimasi lebih lanjut:
Menganalisis korelasi antara indikator/keadaan pasar dan mekanisme desain untuk menyesuaikan secara dinamis bobot indikator berdasarkan perubahan kondisi pasar untuk meningkatkan keputusan.
Menggunakan model pembelajaran mendalam untuk memprediksi arah pergerakan harga dan meningkatkan sistem berbasis aturan untuk meningkatkan akurasi.
Merancang modul penyesuaian adaptif untuk parameter indikator berdasarkan data historis jendela geser sehingga strategi dapat lebih mudah beradaptasi.
Mengintegrasikan analisis periode variabel seperti Teori Gelombang Elliott untuk membantu menilai tren jangka menengah dan panjang dan meningkatkan profitabilitas.
Secara singkat, strategi ini mengintegrasikan MA, RSI, ATR, ADX dan banyak lagi ke dalam sistem yang relatif komprehensif, yang dapat mengidentifikasi tren jangka panjang melalui sistem MA dan mengurangi gangguan kebisingan dengan indikator jangka pendek seperti RSI. Juga, ruang optimasi yang besar ada untuk peningkatan kinerja. Strategi ini meningkatkan keputusan dengan menggabungkan indikator dan mengendalikan risiko.
/*backtest start: 2023-01-28 00:00:00 end: 2024-02-03 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ // This source code to my testing // © sgb //@version=5 strategy(title='Soren test 2', overlay=true, initial_capital=100, pyramiding=1, calc_on_order_fills=true, calc_on_every_tick=true, default_qty_type=strategy.percent_of_equity, default_qty_value=50, commission_value=0.04) //SOURCE ============================================================================================================================================================================================================================================================================================================= src = input(open) // INPUTS ============================================================================================================================================================================================================================================================================================================ //ADX -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ADX_options = input.string('MASANAKAMURA', title='Adx Type', options=['CLASSIC', 'MASANAKAMURA'], group='ADX') ADX_len = input.int(38, title='Adx lenght', minval=1, group='ADX') th = input.float(23, title='Adx Treshold', minval=0, step=0.5, group='ADX') // Volume ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ volume_f = input.float(1.2, title='Volume mult.', minval=0, step=0.1, group='Volume') sma_length = input.int(35, title='Volume lenght', minval=1, group='Volume') //RSI---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- len_3 = input.int(25, title='RSI lenght', group='Relative Strenght Indeks') src_3 = input.source(low, title='RSI Source', group='Relative Strenght Indeks') RSI_VWAP_length = input(25, title='Rsi vwap lenght') // Range Filter --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- per_ = input.int(26, title='SAMPLING PERIOD', minval=1, group='Range Filter') mult = input.float(2.3, title='RANGE MULTIPLIER', minval=0.1, step=0.1, group='Range Filter') // Cloud -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- len = input.int(1, title='Cloud Length', group='Cloud') //RMI ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- RMI_len = input.int(26, title='Rmi Lenght', minval=1, group='Relative Momentum Index') mom = input.int(17, title='Rmi Momentum', minval=1, group='Relative Momentum Index') RMI_os = input.int(33, title='Rmi oversold', minval=0, group='Relative Momentum Index') RMI_ob = input.int(68, title='Rmi overbought', minval=0, group='Relative Momentum Index') // Indicators Calculations ======================================================================================================================================================================================================================================================================================================== // Range Filter ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- var bool L_RF = na var bool S_RF = na Range_filter(_src, _per_, _mult) => var float _upward = 0.0 var float _downward = 0.0 wper = _per_ * 2 - 1 avrng = ta.ema(math.abs(_src - _src[1]), _per_) _smoothrng = ta.ema(avrng, wper) * _mult _filt = _src _filt := _src > nz(_filt[1]) ? _src - _smoothrng < nz(_filt[1]) ? nz(_filt[1]) : _src - _smoothrng : _src + _smoothrng > nz(_filt[1]) ? nz(_filt[1]) : _src + _smoothrng _upward := _filt > _filt[1] ? nz(_upward[1]) + 1 : _filt < _filt[1] ? 0 : nz(_upward[1]) _downward := _filt < _filt[1] ? nz(_downward[1]) + 1 : _filt > _filt[1] ? 0 : nz(_downward[1]) [_smoothrng, _filt, _upward, _downward] [smoothrng, filt, upward, downward] = Range_filter(src, per_, mult) hband = filt + smoothrng lband = filt - smoothrng L_RF := high > hband and upward > 0 S_RF := low < lband and downward > 0 //ADX------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- calcADX(_len) => up = ta.change(high) down = -ta.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 = ta.rma(ta.tr, _len) _plus = fixnan(100 * ta.rma(plusDM, _len) / truerange) _minus = fixnan(100 * ta.rma(minusDM, _len) / truerange) sum = _plus + _minus _adx = 100 * ta.rma(math.abs(_plus - _minus) / (sum == 0 ? 1 : sum), _len) [_plus, _minus, _adx] calcADX_Masanakamura(_len) => SmoothedTrueRange = 0.0 SmoothedDirectionalMovementPlus = 0.0 SmoothedDirectionalMovementMinus = 0.0 TrueRange = math.max(math.max(high - low, math.abs(high - nz(close[1]))), math.abs(low - nz(close[1]))) DirectionalMovementPlus = high - nz(high[1]) > nz(low[1]) - low ? math.max(high - nz(high[1]), 0) : 0 DirectionalMovementMinus = nz(low[1]) - low > high - nz(high[1]) ? math.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 = math.abs(DIP - DIM) / (DIP + DIM) * 100 adx = ta.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 // Volume ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Volume_condt = volume > ta.sma(volume, sma_length) * volume_f //RSI------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ up_3 = ta.rma(math.max(ta.change(src_3), 0), len_3) down_3 = ta.rma(-math.min(ta.change(src_3), 0), len_3) rsi_3 = down_3 == 0 ? 100 : up_3 == 0 ? 0 : 100 - 100 / (1 + up_3 / down_3) L_rsi = rsi_3 < 70 S_rsi = rsi_3 > 30 RSI_VWAP = ta.rsi(ta.vwap(close), RSI_VWAP_length) RSI_VWAP_overSold = 13 RSI_VWAP_overBought = 68 L_VAP = ta.crossover(RSI_VWAP, RSI_VWAP_overSold) S_VAP = ta.crossunder(RSI_VWAP, RSI_VWAP_overBought) //Cloud -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- PI = 2 * math.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 / math.atan(Im / Re) mesaPeriod if mesaPeriod > 1.5 * nz(mesaPeriod[1]) mesaPeriod := 1.5 * nz(mesaPeriod[1]) mesaPeriod if mesaPeriod < 0.67 * nz(mesaPeriod[1]) mesaPeriod := 0.67 * nz(mesaPeriod[1]) mesaPeriod if mesaPeriod < 6 mesaPeriod := 6 mesaPeriod if mesaPeriod > 50 mesaPeriod := 50 mesaPeriod mesaPeriod := 0.2 * mesaPeriod + 0.8 * nz(mesaPeriod[1]) phase = 0.0 if I1 != 0 phase := 180 / PI * math.atan(Q1 / I1) phase deltaPhase = nz(phase[1]) - phase if deltaPhase < 1 deltaPhase := 1 deltaPhase alpha = fastLimit / deltaPhase if alpha < slowLimit alpha := slowLimit alpha [alpha, alpha / 2.0] er = math.abs(ta.change(src, len)) / math.sum(math.abs(ta.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 = math.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] // RMI ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- RMI(len, m) => up = ta.ema(math.max(close - close[m], 0), len) dn = ta.ema(math.max(close[m] - close, 0), len) RMI = dn == 0 ? 0 : 100 - 100 / (1 + up / dn) RMI L_rmi = ta.crossover(RMI(RMI_len, mom), RMI_os) S_rmi = ta.crossunder(RMI(RMI_len, mom), RMI_ob) //STRATEGY ========================================================================================================================================================================================================================================================================================================== L_1 = L_VAP and L_RF and not S_adx S_1 = S_VAP and S_RF and not L_adx L_2 = L_adx and Volume_condt and L_rsi and L_cloud S_2 = S_adx and Volume_condt and S_rsi and S_cloud L_3 = L_rmi and L_RF and not S_adx S_3 = S_rmi and S_RF and not L_adx L_basic_condt = L_1 or L_2 or L_3 S_basic_condt = S_1 or S_2 or S_3 var bool longCondition = na var bool shortCondition = na var float last_open_longCondition = na var float last_open_shortCondition = na var int last_longCondition = 0 var int last_shortCondition = 0 longCondition := L_basic_condt shortCondition := S_basic_condt last_open_longCondition := longCondition ? close : nz(last_open_longCondition[1]) last_open_shortCondition := shortCondition ? close : nz(last_open_shortCondition[1]) last_longCondition := longCondition ? time : nz(last_longCondition[1]) last_shortCondition := shortCondition ? time : nz(last_shortCondition[1]) in_longCondition = last_longCondition > last_shortCondition in_shortCondition = last_shortCondition > last_longCondition // SWAP-SL --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- var int last_long_sl = na var int last_short_sl = na sl = input.float(2, 'Swap % period', minval=0, step=0.1, group='strategy settings') long_sl = ta.crossunder(low, (1 - sl / 100) * last_open_longCondition) and in_longCondition and not longCondition short_sl = ta.crossover(high, (1 + sl / 100) * last_open_shortCondition) and in_shortCondition and not shortCondition last_long_sl := long_sl ? time : nz(last_long_sl[1]) last_short_sl := short_sl ? time : nz(last_short_sl[1]) var bool CondIni_long_sl = 0 CondIni_long_sl := long_sl ? 1 : longCondition ? -1 : nz(CondIni_long_sl[1]) var bool CondIni_short_sl = 0 CondIni_short_sl := short_sl ? 1 : shortCondition ? -1 : nz(CondIni_short_sl[1]) Final_Long_sl = long_sl and nz(CondIni_long_sl[1]) == -1 and in_longCondition and not longCondition Final_Short_sl = short_sl and nz(CondIni_short_sl[1]) == -1 and in_shortCondition and not shortCondition var int sectionLongs = 0 sectionLongs := nz(sectionLongs[1]) var int sectionShorts = 0 sectionShorts := nz(sectionShorts[1]) // RE-ENTRY --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- if longCondition or Final_Long_sl sectionLongs += 1 sectionShorts := 0 sectionShorts if shortCondition or Final_Short_sl sectionLongs := 0 sectionShorts += 1 sectionShorts var float sum_long = 0.0 var float sum_short = 0.0 if longCondition sum_long := nz(last_open_longCondition) + nz(sum_long[1]) sum_short := 0.0 sum_short if Final_Long_sl sum_long := (1 - sl / 100) * last_open_longCondition + nz(sum_long[1]) sum_short := 0.0 sum_short if shortCondition sum_short := nz(last_open_shortCondition) + nz(sum_short[1]) sum_long := 0.0 sum_long if Final_Short_sl sum_long := 0.0 sum_short := (1 + sl / 100) * last_open_shortCondition + nz(sum_short[1]) sum_short var float Position_Price = 0.0 Position_Price := nz(Position_Price[1]) Position_Price := longCondition or Final_Long_sl ? sum_long / sectionLongs : shortCondition or Final_Short_sl ? sum_short / sectionShorts : na //TP_1 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- tp = input.float(1.2, 'Tp-1 ', minval=0, step=0.1, group='strategy settings') long_tp = ta.crossover(high, (1 + tp / 100) * fixnan(Position_Price)) and in_longCondition and not longCondition short_tp = ta.crossunder(low, (1 - tp / 100) * fixnan(Position_Price)) and in_shortCondition and not shortCondition var int last_long_tp = na var int last_short_tp = na last_long_tp := long_tp ? time : nz(last_long_tp[1]) last_short_tp := short_tp ? time : nz(last_short_tp[1]) Final_Long_tp = long_tp and last_longCondition > nz(last_long_tp[1]) Final_Short_tp = short_tp and last_shortCondition > nz(last_short_tp[1]) fixnan_1 = fixnan(Position_Price) ltp = Final_Long_tp ? fixnan_1 * (1 + tp / 100) : na fixnan_2 = fixnan(Position_Price) stp = Final_Short_tp ? fixnan_2 * (1 - tp / 100) : na if Final_Short_tp or Final_Long_tp sum_long := 0.0 sum_short := 0.0 sectionLongs := 0 sectionShorts := 0 sectionShorts if Final_Long_tp CondIni_long_sl == 1 if Final_Short_tp CondIni_short_sl == 1 // COLORS & PLOTS -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ADX_COLOR = L_adx ? color.lime : S_adx ? color.red : color.orange barcolor(color=ADX_COLOR) hbandplot = plot(hband, title='RF HT', color=ADX_COLOR, transp=50) lbandplot = plot(lband, title='RF LT', color=ADX_COLOR, transp=50) fill(hbandplot, lbandplot, title='RF TR', color=ADX_COLOR, transp=90) plotshape(longCondition, title='Long', style=shape.triangleup, location=location.belowbar, color=color.new(color.blue, 0), size=size.tiny) plotshape(shortCondition, title='Short', style=shape.triangledown, location=location.abovebar, color=color.new(color.red, 0), size=size.tiny) plot(ltp, style=plot.style_circles, linewidth=5, color=color.new(color.fuchsia, 0), editable=false) plot(stp, style=plot.style_circles, linewidth=5, color=color.new(color.fuchsia, 0), editable=false) //BACKTESTING-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Q = 50 SL = input.float(0.4, 'StopLoss ', minval=0, step=0.1) strategy.entry('long', strategy.long, when=longCondition) strategy.entry('short', strategy.short, when=shortCondition) strategy.exit('TP', 'long', qty_percent=Q, limit=fixnan(Position_Price) * (1 + tp / 100)) strategy.exit('TP', 'short', qty_percent=Q, limit=fixnan(Position_Price) * (1 - tp / 100)) strategy.exit('SL', 'long', stop=fixnan(Position_Price) * (1 - SL / 100)) strategy.exit('SL', 'short', stop=fixnan(Position_Price) * (1 + SL / 100)) // // // // // // // By SGB