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MACD dan Strategi Dagangan Pintar Sinyal Ganda Regresi Linear

Penulis:ChaoZhang, Tarikh: 2024-12-11 15:46:20
Tag:MACDLRSWMATEMAEMASMA

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/*backtest
start: 2024-11-10 00:00:00
end: 2024-12-09 08:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=6
strategy('SIMPLIFIED MACD & LRS Backtest by NHBProd', overlay=false)

// Function to calculate TEMA (Triple Exponential Moving Average)
tema(src, length) =>
    ema1 = ta.ema(src, length)
    ema2 = ta.ema(ema1, length)
    ema3 = ta.ema(ema2, length)
    3 * (ema1 - ema2) + ema3

// MACD Calculation Function
macdfx(src, fast_length, slow_length, signal_length, method) =>
    fast_ma = method == 'SMA' ? ta.sma(src, fast_length) :
              method == 'EMA' ? ta.ema(src, fast_length) :
              method == 'WMA' ? ta.wma(src, fast_length) :
              tema(src, fast_length)
    slow_ma = method == 'SMA' ? ta.sma(src, slow_length) :
              method == 'EMA' ? ta.ema(src, slow_length) :
              method == 'WMA' ? ta.wma(src, slow_length) :
              tema(src, slow_length)
    macd = fast_ma - slow_ma
    signal = method == 'SMA' ? ta.sma(macd, signal_length) :
             method == 'EMA' ? ta.ema(macd, signal_length) :
             method == 'WMA' ? ta.wma(macd, signal_length) :
             tema(macd, signal_length)
    hist = macd - signal
    [macd, signal, hist]

// MACD Inputs
useMACD = input(true, title="Use MACD for Signals")
src = input(close, title="MACD Source")
fastp = input(12, title="MACD Fast Length")
slowp = input(26, title="MACD Slow Length")
signalp = input(9, title="MACD Signal Length")
macdMethod = input.string('EMA', title='MACD Method', options=['EMA', 'SMA', 'WMA', 'TEMA'])

// MACD Calculation
[macd, signal, hist] = macdfx(src, fastp, slowp, signalp, macdMethod)

// Linear Regression Inputs
useLR = input(true, title="Use Linear Regression for Signals")
lrLength = input(24, title="Linear Regression Length")
lrSource = input(close, title="Linear Regression Source") 
lrSignalSelector = input.string('Rising Linear', title='Signal Selector', options=['Price Above Linear', 'Rising Linear', 'Both'])

// Linear Regression Calculation
linReg = ta.linreg(lrSource, lrLength, 0)
linRegPrev = ta.linreg(lrSource, lrLength, 1)
slope = linReg - linRegPrev

// Linear Regression Buy Signal
lrBuySignal = lrSignalSelector == 'Price Above Linear' ? (close > linReg) :
              lrSignalSelector == 'Rising Linear' ? (slope > 0 and slope > slope[1]) :
              lrSignalSelector == 'Both' ? (close > linReg and slope > 0) : false

// MACD Crossover Signals
macdCrossover = ta.crossover(macd, signal)

// Buy Signals based on user choices
macdSignal = useMACD and macdCrossover
lrSignal = useLR and lrBuySignal

// Buy condition: Use AND condition if both are selected, OR condition if only one is selected
buySignal = (useMACD and useLR) ? (macdSignal and lrSignal) : (macdSignal or lrSignal)

// Plot MACD
hline(0, title="Zero Line", color=color.gray)
plot(macd, color=color.blue, title="MACD Line", linewidth=2)
plot(signal, color=color.orange, title="Signal Line", linewidth=2)
plot(hist, color=hist >= 0 ? color.green : color.red, style=plot.style_columns, title="MACD Histogram")

// Plot Linear Regression Line and Slope
plot(slope, color=slope > 0 ? color.purple : color.red, title="Slope", linewidth=2)
plot(linReg,title="lingreg")
// Signal Plot for Visualization
plotshape(buySignal, style=shape.labelup, location=location.bottom, color=color.new(color.green, 0), title="Buy Signal", text="Buy")

// Sell Signals for Exiting Long Positions
macdCrossunder = ta.crossunder(macd, signal)  // MACD Crossunder for Sell Signal
lrSellSignal = lrSignalSelector == 'Price Above Linear' ? (close < linReg) :
               lrSignalSelector == 'Rising Linear' ? (slope < 0 and slope < slope[1]) :
               lrSignalSelector == 'Both' ? (close < linReg and slope < 0) : false

// User Input for Exit Signals: Select indicators to use for exiting trades
useMACDSell = input(true, title="Use MACD for Exit Signals")
useLRSell = input(true, title="Use Linear Regression for Exit Signals")

// Sell condition: Use AND condition if both are selected to trigger a sell at the same time, OR condition if only one is selected
sellSignal = (useMACDSell and useLRSell) ? (macdCrossunder and lrSellSignal) : 
             (useMACDSell ? macdCrossunder : false) or 
             (useLRSell ? lrSellSignal : false)

// Plot Sell Signals for Visualization (for exits, not short trades)
plotshape(sellSignal, style=shape.labeldown, location=location.top, color=color.new(color.red, 0), title="Sell Signal", text="Sell")

// Alerts
alertcondition(buySignal, title="Buy Signal", message="Buy signal detected!")
alertcondition(sellSignal, title="Sell Signal", message="Sell signal detected!")

// Take Profit and Stop Loss Inputs
takeProfit = input.float(10.0, title="Take Profit (%)")  // Take Profit in percentage
stopLoss = input.float(0.10, title="Stop Loss (%)")        // Stop Loss in percentage

// Backtest Date Range
startDate = input(timestamp("2024-01-01 00:00"), title="Start Date")
endDate = input(timestamp("2025-12-12 00:00"), title="End Date")
inBacktestPeriod = true
// Entry Rules (Only Long Entries)
if (buySignal and inBacktestPeriod)
    strategy.entry("Buy", strategy.long)

// Exit Rules (Only for Long Positions)
strategy.exit("Exit Buy", from_entry="Buy", limit=close * (1 + takeProfit / 100), stop=close * (1 - stopLoss / 100))

// Exit Long Position Based on Sell Signals
if (sellSignal and inBacktestPeriod)
    strategy.close("Buy", comment="Exit Signal")

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