Strategi ini terutamanya menggunakan prinsip crossover purata bergerak, digabungkan dengan isyarat pembalikan penunjuk RSI dan algoritma crossover purata bergerak berganda tersuai untuk melaksanakan perdagangan trend. Strategi ini mengesan dua purata bergerak dari tempoh yang berbeza, dengan MA yang lebih cepat mengesan trend jangka pendek dan MA yang lebih perlahan mengesan trend jangka panjang. Apabila MA yang lebih cepat menyeberangi MA yang lebih perlahan ke atas, ia menandakan trend menaik dan peluang untuk membeli. Apabila MA yang lebih cepat menyeberangi di bawah MA yang lebih perlahan, ia menandakan akhir trend jangka pendek dan peluang untuk menutup kedudukan.
Mengira dua kumpulan purata bergerak VWAP dengan parameter yang berbeza, mewakili trend jangka panjang dan jangka pendek masing-masing.
Ambil purata Tenkansen dan Kijunsen sebagai purata bergerak perlahan dan pantas.
Mengira Bollinger Bands untuk mengenal pasti penyatuan dan pecah.
Mengira TSV untuk menentukan tenaga volum
Mengira RSI untuk mengenal pasti keadaan overbought dan oversold
Syarat kemasukan:
Syarat keluar:
Sistem purata bergerak berganda menangkap kedua-dua trend jangka panjang dan jangka pendek
RSI mengelakkan membeli zon terlalu banyak beli dan menjual zon terlalu banyak dijual
TSV memastikan jumlah yang mencukupi untuk menyokong trend
Bollinger Bands mengenal pasti titik utama
Gabungan penunjuk membantu menapis pecah palsu
Sistem MA terdedah kepada isyarat palsu, memerlukan penapisan dengan penunjuk lain
Parameter RSI perlu dioptimumkan, jika tidak mungkin terlepas titik beli / jual
TSV juga sangat sensitif kepada parameter, memerlukan ujian yang teliti
Pecahkan BB band atas boleh menjadi pecah palsu, keperluan pengesahan
Sukar untuk mengoptimumkan banyak penunjuk, risiko terlalu sesuai
Data kereta api/ujian yang tidak mencukupi boleh menyebabkan pemasangan lengkung
Uji lebih banyak tempoh untuk mencari kombinasi parameter terbaik
Cuba penunjuk lain seperti MACD, KD untuk menggantikan atau menggabungkan dengan RSI
Menggunakan analisis berjalan ke hadapan untuk pengoptimuman parameter
Tambah stop loss untuk mengawal kerugian perdagangan tunggal
Pertimbangkan model pembelajaran mesin untuk membantu ramalan isyarat
Sesuaikan parameter untuk pasaran yang berbeza, jangan terlalu sesuai dengan satu set parameter
Strategi ini menangkap trend jangka panjang dan jangka pendek menggunakan purata bergerak berganda, dan menapis isyarat dengan RSI, TSV, Bollinger Bands dan banyak lagi. Kelebihannya adalah berdagang selaras dengan momentum menaik jangka panjang. Tetapi ia juga membawa risiko isyarat palsu, yang memerlukan penyesuaian parameter lebih lanjut dan menghentikan kerugian untuk mengurangkan risiko. Secara keseluruhan, menggabungkan trend berikut dan pembalikan purata menghasilkan hasil yang baik dalam trend menaik jangka panjang, tetapi parameter memerlukan penyesuaian untuk pasaran yang berbeza.
/*backtest start: 2022-10-23 00:00:00 end: 2023-10-29 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ // @version=4 // Credits // "Vwap with period" code which used in this strategy to calculate the leadLine was written by "neolao" active on https://tr.tradingview.com/u/neolao/ // "TSV" code which used in this strategy was written by "liw0" active on https://www.tradingview.com/u/liw0. The code is corrected by "vitelot" December 2018. // "Vidya" code which used in this strategy was written by "everget" active on https://tr.tradingview.com/u/everget/ strategy("HYE Combo Market [Strategy] (Vwap Mean Reversion + Trend Hunter)", overlay = true, initial_capital = 1000, default_qty_value = 100, default_qty_type = strategy.percent_of_equity, commission_value = 0.025) //Strategy inputs source = input(title = "Source", defval = close, group = "Mean Reversion Strategy Inputs") smallcumulativePeriod = input(title = "Small VWAP", defval = 8, group = "Mean Reversion Strategy Inputs") bigcumulativePeriod = input(title = "Big VWAP", defval = 10, group = "Mean Reversion Strategy Inputs") meancumulativePeriod = input(title = "Mean VWAP", defval = 50, group = "Mean Reversion Strategy Inputs") percentBelowToBuy = input(title = "Percent below to buy %", defval = 2, group = "Mean Reversion Strategy Inputs") rsiPeriod = input(title = "Rsi Period", defval = 2, group = "Mean Reversion Strategy Inputs") rsiEmaPeriod = input(title = "Rsi Ema Period", defval = 5, group = "Mean Reversion Strategy Inputs") rsiLevelforBuy = input(title = "Maximum Rsi Level for Buy", defval = 30, group = "Mean Reversion Strategy Inputs") slowtenkansenPeriod = input(9, minval=1, title="Slow Tenkan Sen VWAP Line Length", group = "Trend Hunter Strategy Inputs") slowkijunsenPeriod = input(13, minval=1, title="Slow Kijun Sen VWAP Line Length", group = "Trend Hunter Strategy Inputs") fasttenkansenPeriod = input(3, minval=1, title="Fast Tenkan Sen VWAP Line Length", group = "Trend Hunter Strategy Inputs") fastkijunsenPeriod = input(7, minval=1, title="Fast Kijun Sen VWAP Line Length", group = "Trend Hunter Strategy Inputs") BBlength = input(20, minval=1, title= "Bollinger Band Length", group = "Trend Hunter Strategy Inputs") BBmult = input(2.0, minval=0.001, maxval=50, title="Bollinger Band StdDev", group = "Trend Hunter Strategy Inputs") tsvlength = input(20, minval=1, title="TSV Length", group = "Trend Hunter Strategy Inputs") tsvemaperiod = input(7, minval=1, title="TSV Ema Length", group = "Trend Hunter Strategy Inputs") length = input(title="Vidya Length", type=input.integer, defval=20, group = "Trend Hunter Strategy Inputs") src = input(title="Vidya Source", type=input.source, defval= hl2 , group = "Trend Hunter Strategy Inputs") // Vidya Calculation getCMO(src, length) => mom = change(src) upSum = sum(max(mom, 0), length) downSum = sum(-min(mom, 0), length) out = (upSum - downSum) / (upSum + downSum) out cmo = abs(getCMO(src, length)) alpha = 2 / (length + 1) vidya = 0.0 vidya := src * alpha * cmo + nz(vidya[1]) * (1 - alpha * cmo) // Make input options that configure backtest date range startDate = input(title="Start Date", type=input.integer, defval=1, minval=1, maxval=31, group = "Strategy Date Range") startMonth = input(title="Start Month", type=input.integer, defval=1, minval=1, maxval=12, group = "Strategy Date Range") startYear = input(title="Start Year", type=input.integer, defval=2000, minval=1800, maxval=2100, group = "Strategy Date Range") endDate = input(title="End Date", type=input.integer, defval=31, minval=1, maxval=31, group = "Strategy Date Range") endMonth = input(title="End Month", type=input.integer, defval=12, minval=1, maxval=12, group = "Strategy Date Range") endYear = input(title="End Year", type=input.integer, defval=2021, minval=1800, maxval=2100, group = "Strategy Date Range") inDateRange = true // Mean Reversion Strategy Calculation typicalPriceS = (high + low + close) / 3 typicalPriceVolumeS = typicalPriceS * volume cumulativeTypicalPriceVolumeS = sum(typicalPriceVolumeS, smallcumulativePeriod) cumulativeVolumeS = sum(volume, smallcumulativePeriod) smallvwapValue = cumulativeTypicalPriceVolumeS / cumulativeVolumeS typicalPriceB = (high + low + close) / 3 typicalPriceVolumeB = typicalPriceB * volume cumulativeTypicalPriceVolumeB = sum(typicalPriceVolumeB, bigcumulativePeriod) cumulativeVolumeB = sum(volume, bigcumulativePeriod) bigvwapValue = cumulativeTypicalPriceVolumeB / cumulativeVolumeB typicalPriceM = (high + low + close) / 3 typicalPriceVolumeM = typicalPriceM * volume cumulativeTypicalPriceVolumeM = sum(typicalPriceVolumeM, meancumulativePeriod) cumulativeVolumeM = sum(volume, meancumulativePeriod) meanvwapValue = cumulativeTypicalPriceVolumeM / cumulativeVolumeM rsiValue = rsi(source, rsiPeriod) rsiEMA = ema(rsiValue, rsiEmaPeriod) buyMA = ((100 - percentBelowToBuy) / 100) * bigvwapValue[0] inTrade = strategy.position_size > 0 notInTrade = strategy.position_size <= 0 if(crossunder(smallvwapValue, buyMA) and rsiEMA < rsiLevelforBuy and close < meanvwapValue and inDateRange and notInTrade) strategy.entry("BUY-M", strategy.long) if(close > meanvwapValue or not inDateRange) strategy.close("BUY-M") // Trend Hunter Strategy Calculation // Slow Tenkan Sen Calculation typicalPriceTS = (high + low + close) / 3 typicalPriceVolumeTS = typicalPriceTS * volume cumulativeTypicalPriceVolumeTS = sum(typicalPriceVolumeTS, slowtenkansenPeriod) cumulativeVolumeTS = sum(volume, slowtenkansenPeriod) slowtenkansenvwapValue = cumulativeTypicalPriceVolumeTS / cumulativeVolumeTS // Slow Kijun Sen Calculation typicalPriceKS = (high + low + close) / 3 typicalPriceVolumeKS = typicalPriceKS * volume cumulativeTypicalPriceVolumeKS = sum(typicalPriceVolumeKS, slowkijunsenPeriod) cumulativeVolumeKS = sum(volume, slowkijunsenPeriod) slowkijunsenvwapValue = cumulativeTypicalPriceVolumeKS / cumulativeVolumeKS // Fast Tenkan Sen Calculation typicalPriceTF = (high + low + close) / 3 typicalPriceVolumeTF = typicalPriceTF * volume cumulativeTypicalPriceVolumeTF = sum(typicalPriceVolumeTF, fasttenkansenPeriod) cumulativeVolumeTF = sum(volume, fasttenkansenPeriod) fasttenkansenvwapValue = cumulativeTypicalPriceVolumeTF / cumulativeVolumeTF // Fast Kijun Sen Calculation typicalPriceKF = (high + low + close) / 3 typicalPriceVolumeKF = typicalPriceKS * volume cumulativeTypicalPriceVolumeKF = sum(typicalPriceVolumeKF, fastkijunsenPeriod) cumulativeVolumeKF = sum(volume, fastkijunsenPeriod) fastkijunsenvwapValue = cumulativeTypicalPriceVolumeKF / cumulativeVolumeKF // Slow LeadLine Calculation lowesttenkansen_s = lowest(slowtenkansenvwapValue, slowtenkansenPeriod) highesttenkansen_s = highest(slowtenkansenvwapValue, slowtenkansenPeriod) lowestkijunsen_s = lowest(slowkijunsenvwapValue, slowkijunsenPeriod) highestkijunsen_s = highest(slowkijunsenvwapValue, slowkijunsenPeriod) slowtenkansen = avg(lowesttenkansen_s, highesttenkansen_s) slowkijunsen = avg(lowestkijunsen_s, highestkijunsen_s) slowleadLine = avg(slowtenkansen, slowkijunsen) // Fast LeadLine Calculation lowesttenkansen_f = lowest(fasttenkansenvwapValue, fasttenkansenPeriod) highesttenkansen_f = highest(fasttenkansenvwapValue, fasttenkansenPeriod) lowestkijunsen_f = lowest(fastkijunsenvwapValue, fastkijunsenPeriod) highestkijunsen_f = highest(fastkijunsenvwapValue, fastkijunsenPeriod) fasttenkansen = avg(lowesttenkansen_f, highesttenkansen_f) fastkijunsen = avg(lowestkijunsen_f, highestkijunsen_f) fastleadLine = avg(fasttenkansen, fastkijunsen) // BBleadLine Calculation BBleadLine = avg(fastleadLine, slowleadLine) // Bollinger Band Calculation basis = sma(BBleadLine, BBlength) dev = BBmult * stdev(BBleadLine, BBlength) upper = basis + dev lower = basis - dev // TSV Calculation tsv = sum(close>close[1]?volume*(close-close[1]):close<close[1]?volume*(close-close[1]):0,tsvlength) tsvema = ema(tsv, tsvemaperiod) // Rules for Entry & Exit if(fastleadLine > fastleadLine[1] and slowleadLine > slowleadLine[1] and tsv > 0 and tsv > tsvema and close > upper and close > vidya and inDateRange and notInTrade) strategy.entry("BUY-T", strategy.long) if((fastleadLine < fastleadLine[1] and slowleadLine < slowleadLine[1]) or not inDateRange) strategy.close("BUY-T") // Plots plot(meanvwapValue, title="MEAN VWAP", linewidth=2, color=color.yellow) //plot(vidya, title="VIDYA", linewidth=2, color=color.green) //colorsettingS = input(title="Solid Color Slow Leadline", defval=false, type=input.bool) //plot(slowleadLine, title = "Slow LeadLine", color = colorsettingS ? color.aqua : slowleadLine > slowleadLine[1] ? color.green : color.red, linewidth=3) //colorsettingF = input(title="Solid Color Fast Leadline", defval=false, type=input.bool) //plot(fastleadLine, title = "Fast LeadLine", color = colorsettingF ? color.orange : fastleadLine > fastleadLine[1] ? color.green : color.red, linewidth=3) //p1 = plot(upper, "Upper BB", color=#2962FF) //p2 = plot(lower, "Lower BB", color=#2962FF) //fill(p1, p2, title = "Background", color=color.blue) //plot(smallvwapValue, color=#13C425, linewidth=2) //plot(bigvwapValue, color=#CA1435, linewidth=2)