Tren Mengikuti Strategi Berdasarkan Rata-rata Bergerak
Penulis:ChaoZhang, Tanggal: 2024-01-24 14:24:36Tag:
Gambaran umum
Ini adalah tren sederhana mengikuti strategi berdasarkan moving average. Ini menilai arah tren saat ini dan durasi dengan membandingkan hubungan ukuran antara moving average dari siklus yang berbeda. Ini pergi panjang ketika siklus pendek moving average melintasi di atas siklus panjang satu, dan pergi pendek ketika sebaliknya terjadi. Pada saat yang sama, titik stop loss dan take profit diatur untuk mengendalikan risiko.
Logika Strategi
Strategi ini menggunakan 4 rata-rata bergerak dengan siklus yang berbeda: garis 5 hari, 10 hari, 15 hari dan 25 hari. Mereka disebut MA1, MA2, MA3 dan MA4.
Ketika MA1>MA2>MA3>MA4, itu menunjukkan tren naik dan pergi panjang. Ketika MA1
Kondisi posisi terbuka untuk posisi panjang dan pendek harus memenuhi filter stop loss ATR pada saat yang sama, yaitu nilai ATR harus lebih besar dari SMA 40 hari ATR. Hal ini menghindari menghasilkan sinyal yang salah ketika fluktuasi harga terlalu kecil.
Analisis Keuntungan
Strategi ini memiliki keuntungan berikut:
- Logikanya sederhana dan mudah diterapkan.
- Menggunakan beberapa rata-rata bergerak untuk menentukan arah tren dapat diandalkan.
- Menetapkan titik stop loss dan take profit dapat secara efektif mengontrol kerugian maksimum per perdagangan.
- Filter stop loss ATR menghindari sinyal yang salah ketika fluktuasi harga kecil.
Analisis Risiko
Strategi ini juga memiliki risiko berikut:
- Sangat mudah untuk menghasilkan sinyal yang salah di pasar yang sebagian besar terkejut.
- Pengaturan parameter yang tidak benar (siklus rata-rata bergerak, dll.) dapat menyebabkan kinerja strategi yang buruk.
- Hal ini tidak mempertimbangkan dampak dari fundamental dan berita penting pada harga.
Untuk mengurangi risiko ini, parameter dapat dioptimalkan dengan tepat, atau kondisi filter tambahan dapat ditambahkan untuk meningkatkan stabilitas strategi.
Arahan Optimasi
Arah optimalisasi strategi meliputi:
- Uji kombinasi yang berbeda dari parameter siklus rata-rata bergerak untuk menemukan parameter yang optimal.
- Tambahkan filter indikator teknis lainnya seperti MACD dan KDJ untuk menilai keandalan sinyal.
- Tambahkan filter volume perdagangan, hanya perdagangan ketika volume perdagangan berkembang.
- Parameter penyesuaian berdasarkan perbedaan antara varietas.
- Tambahkan algoritma pembelajaran mesin untuk menilai sinyal.
Kesimpulan
Secara umum, ini adalah tren yang relatif sederhana mengikuti strategi. Ini menilai arah tren melalui moving average dan menetapkan stop loss yang wajar dan mengambil keuntungan untuk mengontrol tingkat risiko. Masih banyak ruang untuk optimasi, seperti menyesuaikan parameter, menambahkan filter dll untuk lebih meningkatkan stabilitas dan profitabilitas strategi.
/*backtest
start: 2023-01-17 00:00:00
end: 2024-01-23 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © fpemehd
// @version=5
// # ========================================================================= #
// # | STRATEGY |
// # ========================================================================= #
strategy(title = 'MA Simple Strategy with SL & TP & ATR Filters',
shorttitle = 'MA Strategy',
overlay = true,
pyramiding = 0,
default_qty_type = strategy.percent_of_equity,
default_qty_value = 100,
commission_type = strategy.commission.percent,
commission_value = 0.1,
initial_capital = 100000,
max_lines_count = 150,
max_labels_count = 300)
// # ========================================================================= #
// # Inputs
// # ========================================================================= #
// 1. Time
i_start = input (defval = timestamp("20 Jan 1990 00:00 +0900"), title = "Start Date", tooltip = "Choose Backtest Start Date", inline = "Start Date", group = "Time" )
i_end = input (defval = timestamp("20 Dec 2030 00:00 +0900"), title = "End Date", tooltip = "Choose Backtest End Date", inline = "End Date", group = "Time" )
c_timeCond = true
// 2. Inputs for direction: Long? Short? Both?
i_longEnabled = input.bool(defval = true , title = "Long?", tooltip = "Enable Long Position Trade?", inline = "Long / Short", group = "Long / Short" )
i_shortEnabled = input.bool(defval = true , title = "Short?", tooltip = "Enable Short Position Trade?", inline = "Long / Short", group = "Long / Short" )
// 3. Use Filters? What Filters?
i_ATRFilterOn = input.bool(defval = true , title = "ATR Filter On?", tooltip = "ATR Filter On?", inline = "ATR Filter", group = "Filters")
i_ATRSMALen = input.int(defval = 40 , title = "SMA Length for ATR SMA", minval = 1 , maxval = 100000 , step = 1 , tooltip = "ATR should be bigger than this", inline = "ATR Filter", group = "Filters")
// 3. Shared inputs for Long and Short
//// 3-1. Inputs for Stop Loss Type: normal? or trailing?
//// If trailing, always trailing or trailing after take profit order executed?
i_useSLTP = input.bool(defval = true, title = "Enable SL & TP?", tooltip = "", inline = "Enable SL & TP & SL Type", group = "Shared Inputs")
i_tslEnabled = input.bool(defval = false , title = "Enable Trailing SL?", tooltip = "Enable Stop Loss & Take Profit? \n\Enable Trailing SL?", inline = "Enable SL & TP & SL Type", group = "Shared Inputs")
// i_tslAfterTP = input.bool(defval = true , title = "Enable Trailing SL after TP?", tooltip = "Enable Trailing SL after TP?", inline = "Trailing SL Execution", group = "Shared Inputs")
i_slType = input.string(defval = "ATR", title = "Stop Loss Type", options = ["Percent", "ATR"], tooltip = "Stop Loss based on %? ATR?", inline = "Stop Loss Type", group = "Shared Inputs")
i_slATRLen = input.int(defval = 14, title = "ATR Length", minval = 1 , maxval = 200 , step = 1, inline = "Stop Loss ATR", group = "Shared Inputs")
i_tpType = input.string(defval = "R:R", title = "Take Profit Type", options = ["Percent", "ATR", "R:R"], tooltip = "Take Profit based on %? ATR? R-R ratio?", inline = "Take Profit Type", group = "Shared Inputs")
//// 3-2. Inputs for Quantity
i_tpQuantityPerc = input.float(defval = 50, title = 'Take Profit Quantity %', minval = 0.0, maxval = 100, step = 1.0, tooltip = '% of position when tp target is met.', group = 'Shared Inputs')
// 4. Inputs for Long Stop Loss & Long Take Profit
i_slPercentLong = input.float(defval = 3, title = "SL Percent", tooltip = "", inline = "Percent > Long Stop Loss / Take Profit Percent", group = "Long Stop Loss / Take Profit")
i_tpPercentLong = input.float(defval = 3, title = "TP Percent", tooltip = "Long Stop Loss && Take Profit Percent?", inline = "Percent > Long Stop Loss / Take Profit Percent", group = "Long Stop Loss / Take Profit")
i_slATRMultLong = input.float(defval = 3, title = "SL ATR Multiplier", minval = 1 , maxval = 200 , step = 0.1, tooltip = "", inline = "Long Stop Loss / Take Profit ATR", group = "Long Stop Loss / Take Profit")
i_tpATRMultLong = input.float(defval = 3, title = "TP ATR Multiplier", minval = 1 , maxval = 200 , step = 0.1, tooltip = "ATR > Long Stop Loss && Take Profit ATR Multiplier? \n\Stop Loss = i_slATRMultLong * ATR (i_slATRLen) \n\Take Profit = i_tpATRMultLong * ATR (i_tpATRLen)", inline = "Long Stop Loss / Take Profit ATR", group = "Long Stop Loss / Take Profit")
i_tpRRratioLong = input.float(defval = 1.8, title = "R:R Ratio", minval = 0.1 , maxval = 200 , step = 0.1, tooltip = "R:R Ratio > Risk Reward Ratio? It will automatically set Take Profit % based on Stop Loss", inline = "R:R Ratio", group = "Long Stop Loss / Take Profit")
// 5. Inputs for Short Stop Loss & Short Take Profit
i_slPercentShort = input.float(defval = 3, title = "SL Percent", tooltip = "", inline = "Percent > Short Stop Loss / Take Profit Percent", group = "Short Stop Loss / Take Profit")
i_tpPercentShort = input.float(defval = 3, title = "TP Percent", tooltip = "Short Stop Loss && Take Profit Percent?", inline = "Percent > Short Stop Loss / Take Profit Percent", group = "Short Stop Loss / Take Profit")
i_slATRMultShort = input.float(defval = 3, title = "SL ATR Multiplier", minval = 1 , maxval = 200 , step = 0.1, tooltip = "", inline = "ATR > Short Stop Loss / Take Profit ATR", group = "Short Stop Loss / Take Profit")
i_tpATRMultShort = input.float(defval = 3, title = "TP ATR Multiplier", minval = 1 , maxval = 200 , step = 0.1, tooltip = "ATR > Short Stop Loss && Take Profit ATR Multiplier? \n\Stop Loss = i_slATRMultShort * ATR (i_slATRLen) \n\Take Profit = i_tpATRMultShort * ATR (i_tpATRLen)", inline = "ATR > Short Stop Loss / Take Profit ATR", group = "Short Stop Loss / Take Profit")
i_tpRRratioShort = input.float(defval = 1.8, title = "R:R Ratio", minval = 0.1 , maxval = 200 , step = 0.1, tooltip = "R:R Ratio > Risk Reward Ratio? It will automatically set Take Profit % based on Stop Loss", inline = "R:R Ratio", group = "Short Stop Loss / Take Profit")
// 6. Inputs for logic
i_MAType = input.string(defval = "RMA", title = "MA Type", options = ["SMA", "EMA", "WMA", "HMA", "RMA", "VWMA", "SWMA", "ALMA", "VWAP"], tooltip = "Choose MA Type", inline = "MA Type", group = 'Strategy')
i_MA1Len = input.int(defval = 5, title = 'MA 1 Length', minval = 1, inline = 'MA Length', group = 'Strategy')
i_MA2Len = input.int(defval = 10, title = 'MA 2 Length', minval = 1, inline = 'MA Length', group = 'Strategy')
i_MA3Len = input.int(defval = 15, title = 'MA 3 Length', minval = 1, inline = 'MA Length', group = 'Strategy')
i_MA4Len = input.int(defval = 25, title = 'MA 4 Length', minval = 1, inline = 'MA Length', group = 'Strategy')
i_ALMAOffset = input.float(defval = 0.7 , title = "ALMA Offset Value", tooltip = "The Value of ALMA offset", inline = "ALMA Input", group = 'Strategy')
i_ALMASigma = input.float(defval = 7 , title = "ALMA Sigma Value", tooltip = "The Value of ALMA sigma", inline = "ALMA Input", group = 'Strategy')
// # ========================================================================= #
// # Entry, Close Logic
// # ========================================================================= #
bool i_ATRFilter = ta.atr(length = i_slATRLen) >= ta.sma(source = ta.atr(length = i_slATRLen), length = i_ATRSMALen) ? true : false
// calculate Technical Indicators for the Logic
getMAValue (source, length, almaOffset, almaSigma) =>
switch i_MAType
'SMA' => ta.sma(source = source, length = length)
'EMA' => ta.ema(source = source, length = length)
'WMA' => ta.wma(source = source, length = length)
'HMA' => ta.hma(source = source, length = length)
'RMA' => ta.rma(source = source, length = length)
'SWMA' => ta.swma(source = source)
'ALMA' => ta.alma(series = source, length = length, offset = almaOffset, sigma = almaSigma)
'VWMA' => ta.vwma(source = source, length = length)
'VWAP' => ta.vwap(source = source)
=> na
float c_MA1 = getMAValue(close, i_MA1Len, i_ALMAOffset, i_ALMASigma)
float c_MA2 = getMAValue(close, i_MA2Len, i_ALMAOffset, i_ALMASigma)
float c_MA3 = getMAValue(close, i_MA3Len, i_ALMAOffset, i_ALMASigma)
float c_MA4 = getMAValue(close, i_MA4Len, i_ALMAOffset, i_ALMASigma)
// Logic: 정배열 될 떄 들어가
var ma1Color = color.new(color.red, 0)
plot(series = c_MA1, title = 'SMA 1', color = ma1Color, linewidth = 1, style = plot.style_line)
var ma2Color = color.new(color.orange, 0)
plot(series = c_MA2, title = 'SMA 2', color = ma2Color, linewidth = 1, style = plot.style_line)
var ma3Color = color.new(color.yellow, 0)
plot(series = c_MA3, title = 'SMA 3', color = ma3Color, linewidth = 1, style = plot.style_line)
var ma4Color = color.new(color.green, 0)
plot(series = c_MA4, title = 'SMA 4', color = ma4Color, linewidth = 1, style = plot.style_line)
bool openLongCond = (c_MA1 >= c_MA2 and c_MA2 >= c_MA3 and c_MA3 >= c_MA4)
bool openShortCond = (c_MA1 <= c_MA2 and c_MA2 <= c_MA3 and c_MA3 <= c_MA4)
bool openLong = i_longEnabled and openLongCond and (not i_ATRFilterOn or i_ATRFilter)
bool openShort = i_shortEnabled and openShortCond and (not i_ATRFilterOn or i_ATRFilter)
openLongCondColor = openLongCond ? color.new(color = color.blue, transp = 80) : na
bgcolor(color = openLongCondColor)
ATRFilterColor = i_ATRFilter ? color.new(color = color.orange, transp = 80) : na
bgcolor(color = ATRFilterColor)
bool enterLong = openLong and not (strategy.opentrades.size(strategy.opentrades-1) > 0)
bool enterShort = openShort and not (strategy.opentrades.size(strategy.opentrades-1) < 0)
bool closeLong = i_longEnabled and (c_MA1[1] >= c_MA2[1] and c_MA2[1] >= c_MA3[1] and c_MA3[1] >= c_MA4[1]) and not (c_MA1 >= c_MA2 and c_MA2 >= c_MA3 and c_MA3 >= c_MA4)
bool closeShort = i_shortEnabled and (c_MA1[1] <= c_MA2[1] and c_MA2[1] <= c_MA3[1] and c_MA3[1] <= c_MA4[1]) and not (c_MA1 <= c_MA2 and c_MA2 <= c_MA3 and c_MA3 <= c_MA4)
// # ========================================================================= #
// # Position, Status Conrtol
// # ========================================================================= #
// longisActive: New Long || Already Long && not closeLong, short is the same
bool longIsActive = enterLong or strategy.opentrades.size(strategy.opentrades - 1) > 0 and not closeLong
bool shortIsActive = enterShort or strategy.opentrades.size(strategy.opentrades - 1) < 0 and not closeShort
// before longTPExecution: no trailing SL && after longTPExecution: trailing SL starts
// longTPExecution qunatity should be less than 100%
bool longTPExecuted = false
bool shortTPExecuted = false
// # ========================================================================= #
// # Long Stop Loss Logic
// # ========================================================================= #
float openAtr = ta.valuewhen(enterLong or enterShort, ta.atr(i_slATRLen), 0)
f_getLongSL (source) =>
switch i_slType
'Percent' => source * (1 - (i_slPercentLong/100))
'ATR' => source - i_slATRMultLong * openAtr
=> na
var float c_longSLPrice = na
c_longSLPrice := if (longIsActive)
if (enterLong)
f_getLongSL(close)
else
c_stopPrice = f_getLongSL(i_tslEnabled ? high : strategy.opentrades.entry_price(trade_num = strategy.opentrades - 1))
math.max(c_stopPrice, nz(c_longSLPrice[1]))
else
na
// # ========================================================================= #
// # Short Stop Loss Logic
// # ========================================================================= #
f_getShortSL (source) =>
switch i_slType
'Percent' => source * (1 + (i_slPercentShort)/100)
'ATR' => source + i_slATRMultShort * openAtr
=> na
var float c_shortSLPrice = na
c_shortSLPrice := if (shortIsActive)
if (enterShort)
f_getShortSL (close)
else
c_stopPrice = f_getShortSL(i_tslEnabled ? low : strategy.opentrades.entry_price(strategy.opentrades - 1))
math.min(c_stopPrice, nz(c_shortSLPrice[1], 999999.9))
else
na
// # ========================================================================= #
// # Long Take Profit Logic
// # ========================================================================= #
f_getLongTP () =>
switch i_tpType
'Percent' => close * (1 + (i_tpPercentLong/100))
'ATR' => close + i_tpATRMultLong * openAtr
'R:R' => close + i_tpRRratioLong * (close - f_getLongSL(close))
=> na
var float c_longTPPrice = na
c_longTPPrice := if (longIsActive and not longTPExecuted)
if (enterLong)
f_getLongTP()
else
nz(c_longTPPrice[1], f_getLongTP())
else
na
longTPExecuted := strategy.opentrades.size(strategy.opentrades - 1) > 0 and (longTPExecuted[1] or strategy.opentrades.size(strategy.opentrades - 1) < strategy.opentrades.size(strategy.opentrades - 1)[1] or strategy.opentrades.size(strategy.opentrades - 1)[1] == 0 and high >= c_longTPPrice)
// # ========================================================================= #
// # Short Take Profit Logic
// # ========================================================================= #
f_getShortTP () =>
switch i_tpType
'Percent' => close * (1 - (i_tpPercentShort/100))
'ATR' => close - i_tpATRMultShort * openAtr
'R:R' => close - i_tpRRratioShort * (close - f_getLongSL(close))
=> na
var float c_shortTPPrice = na
c_shortTPPrice := if (shortIsActive and not shortTPExecuted)
if (enterShort)
f_getShortTP()
else
nz(c_shortTPPrice[1], f_getShortTP())
else
na
shortTPExecuted := strategy.opentrades.size(strategy.opentrades - 1) < 0 and (shortTPExecuted[1] or strategy.opentrades.size(strategy.opentrades - 1) > strategy.opentrades.size(strategy.opentrades - 1)[1] or strategy.opentrades.size(strategy.opentrades - 1)[1] == 0 and low <= c_shortTPPrice)
// # ========================================================================= #
// # Make Orders
// # ========================================================================= #
if (c_timeCond)
if (enterLong)
strategy.entry(id = "Long Entry", direction = strategy.long , comment = 'Long(' + syminfo.ticker + '): Started', alert_message = 'Long(' + syminfo.ticker + '): Started')
if (enterShort)
strategy.entry(id = "Short Entry", direction = strategy.short , comment = 'Short(' + syminfo.ticker + '): Started', alert_message = 'Short(' + syminfo.ticker + '): Started')
if (closeLong)
strategy.close(id = 'Long Entry', comment = 'Close Long', alert_message = 'Long: Closed at market price')
if (closeShort)
strategy.close(id = 'Short Entry', comment = 'Close Short', alert_message = 'Short: Closed at market price')
if (longIsActive and i_useSLTP)
strategy.exit(id = 'Long Take Profit / Stop Loss', from_entry = 'Long Entry', qty_percent = i_tpQuantityPerc, limit = c_longTPPrice, stop = c_longSLPrice, alert_message = 'Long(' + syminfo.ticker + '): Take Profit or Stop Loss executed')
strategy.exit(id = 'Long Stop Loss', from_entry = 'Long Entry', stop = c_longSLPrice, alert_message = 'Long(' + syminfo.ticker + '): Stop Loss executed')
if (shortIsActive and i_useSLTP)
strategy.exit(id = 'Short Take Profit / Stop Loss', from_entry = 'Short Entry', qty_percent = i_tpQuantityPerc, limit = c_shortTPPrice, stop = c_shortSLPrice, alert_message = 'Short(' + syminfo.ticker + '): Take Profit or Stop Loss executed')
strategy.exit(id = 'Short Stop Loss', from_entry = 'Short Entry', stop = c_shortSLPrice, alert_message = 'Short(' + syminfo.ticker + '): Stop Loss executed')
// # ========================================================================= #
// # Plot
// # ========================================================================= #
var posColor = color.new(color.white, 0)
plot(series = strategy.opentrades.entry_price(strategy.opentrades - 1), title = 'Position', color = posColor, linewidth = 1, style = plot.style_linebr)
var stopLossColor = color.new(color.maroon, 0)
plot(series = c_longSLPrice, title = 'Long Stop Loss', color = stopLossColor, linewidth = 1, style = plot.style_linebr, offset = 1)
plot(series = c_shortSLPrice, title = 'Short Stop Loss', color = stopLossColor, linewidth = 1, style = plot.style_linebr, offset = 1)
longTPExecutedColor = longTPExecuted ? color.new(color = color.green, transp = 80) : na
//bgcolor(color = longTPExecutedColor)
shortTPExecutedColor = shortTPExecuted ? color.new(color = color.red, transp = 80) : na
//bgcolor(color = shortTPExecutedColor)
// isPositionOpenedColor = strategy.opentrades.size(strategy.opentrades-1) != 0 ? color.new(color = color.yellow, transp = 90) : na
// bgcolor(color = isPositionOpenedColor)
var takeProfitColor = color.new(color.teal, 0)
plot(series = c_longTPPrice, title = 'Long Take Profit', color = takeProfitColor, linewidth = 1, style = plot.style_linebr, offset = 1)
plot(series = c_shortTPPrice, title = 'Short Take Profit', color = takeProfitColor, linewidth = 1, style = plot.style_linebr, offset = 1)
Lebih banyak
- Strategi EMA Dual Trailing Stop yang Dinamis
- Strategi perdagangan kuantitatif gabungan multi-indikator
- Contrarian Donchian Channel Touch Entry Strategy dengan Post-Stop Loss Pause dan Trailing Stop Loss
- Strategi Trading Jangka Pendek Indikator Lilin Tunggal Intraday
- Strategi perdagangan lintas rata-rata bergerak
- RSI Bollinger Bands Strategi Perdagangan
- Tren Mengikuti Strategi Berdasarkan EMA Dual
- Strategi Penembusan Rata-rata Bergerak Ganda
- RSI dan Moving Average Breakout Strategy
- Strategi Pelacakan EMA
- SMA Crossover Ichimoku Strategi Perdagangan Kuantitatif Berdasarkan Volume
- Tren Pelacakan Stop Loss Take Profit Strategi
- Bi-directional Crossing Zero Axis Qstick Indicator Backtest Strategi
- Strategi perdagangan lintas rata-rata bergerak
- Strategi Divergensi Rata-rata yang Bergerak
- Strategi perdagangan frekuensi tinggi pembalikan berdasarkan garis bayangan
- Strategi perdagangan kuantitatif berdasarkan RSI regresi linier
- Strategi ini adalah dua arah adaptif rentang penyaringan strategi pelacakan momentum
- Strategi Pelacakan Tren Rata-rata Bergerak Ganda
- Strategi Terobosan Kekuatan