ジャクソン・クイックフィンガースラック（QFL）のパニック買い戦略

/*backtest
start: 2025-05-01 00:00:00
end: 2025-08-26 00:00:00
period: 1m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"ETH_USDT","tradesMode":"1"}]
*/

//@version=6
strategy("Jackson Quickfingersluc (QFL) Strategy", overlay=true)

// Parameters
baseLevelMultiplier = input.float(1, title="Base Level Multiplier", minval=0.1, maxval=1.0, step=0.05)
reboundMultiplier = input.float(0.8, title="Rebound Level Multiplier", minval=0.0001, maxval=1.0, step=0.01) // Multiplier for range of past candles
lookBackPeriod = input.int(50, title="Look-back Period", minval=10)
atrPeriod = input.int(14, title="ATR Period", minval=1)
atrMultiplier = input.float(1.2, title="Panic Sell ATR Multiplier", minval=0.1, maxval=5.0, step=0.1) // Multiplier for ATR threshold
panicSellPercentage = input.float(0.005, title="Panic Sell Percentage Below Base Level", step=0.0001) // Percentage below base level for panic sell
exitProfitThreshold = input.float(0.01, title="Exit Profit Threshold", minval=0.001, maxval=0.1, step=0.001) // Minimum profit threshold (e.g., 1%)
takeProfitOption = input.string("avg_price", title="Take Profit Option", options=["avg_price", "first_entry", "each_position"]) // TP option selection
rangeBars = input.int(3, title="Number of Bars for Range Calculation", minval=1) // Input for number of bars for range calculation
cooldownBars = input.int(5, title="Cooldown Period (Bars)", minval=1) // Input for cooldown period after a buy

// Calculate Base Level
lowestClose = ta.lowest(close, lookBackPeriod)
baseLevel = lowestClose[1] * baseLevelMultiplier

// Calculate Rebound Level as a multiplier of the range of the last 'rangeBars' bars
rangeLastBars = ta.highest(high, rangeBars) - ta.lowest(low, rangeBars)
reboundLevel = reboundMultiplier * rangeLastBars + baseLevel

// Plotting base and rebound levels
plot(baseLevel, color=color.green, linewidth=2, title="Base Level")
plot(reboundLevel, color=color.red, linewidth=2, title="Rebound Level")

// Calculate ATR
atrValue = ta.atr(atrPeriod)

// Factorial average and panic sell movement calculation
var bool panicSellMovement = false

// Loop through each range and check for panic sell condition
for bar_i = 1 to rangeBars+1
    currentBarRange = high[bar_i - 1] - low[bar_i - 1]  // Current bar range
    rangeOfLastXBars = ta.highest(high, bar_i) - ta.lowest(low, bar_i)  // Range of the last `bar_i` bars
    
    // Condition 1: Check if the average range of the last `bar_i` bars exceeds ATR multiplier
    if (rangeOfLastXBars / bar_i) > atrMultiplier * atrValue
        panicSellMovement := true
        break  // Exit the loop immediately
    
    // Condition 2: Check if the current bar range exceeds ATR multiplier
    if currentBarRange > atrMultiplier * atrValue
        panicSellMovement := true
        break  // Exit the loop immediately

// Define the adjusted base level threshold for panic sell (base level - percentage)
panicSellThreshold = baseLevel[0] * (1 - panicSellPercentage)

// Define panic sell condition with base level check and the panic sell percentage threshold
isPanicSell = low < panicSellThreshold and panicSellMovement

// Define rebound condition
isRebound = close > reboundLevel

// Track the last entry bar index
var float lastEntryBar = na

// Store entry prices for each position in an array
var float[] entryPrices = na
var float[] entrySizes = na

bool exit_cond = false
if (na(entryPrices))
    entryPrices := array.new_float(0)
if (na(entrySizes))
    entrySizes := array.new_float(0)

// Strategy to simulate buys and sells (for backtesting purposes)
entry_cond = isPanicSell and (na(lastEntryBar) or (bar_index - lastEntryBar) > cooldownBars)
if entry_cond
    strategy.entry("Buy", strategy.long)
    lastEntryBar := bar_index  // Set last entry bar to current bar index
    // Store the entry price and size for this new position
    array.push(entryPrices, close)
    array.push(entrySizes, strategy.position_size)

isTakeProfitCondition(entryPrice) =>
    profitPercentage = (close - entryPrice) / entryPrice
    profitCondition = profitPercentage >= exitProfitThreshold
    reboundCondition = isRebound
    profitCondition and reboundCondition

// Check TP condition based on selected option
if takeProfitOption == "avg_price"
    avgEntryPrice = strategy.position_avg_price
    if isTakeProfitCondition(avgEntryPrice)
        exit_cond := true
        strategy.close("Buy")
else if takeProfitOption == "first_entry"
    firstEntryPrice = strategy.opentrades.entry_price(0)
    if isTakeProfitCondition(firstEntryPrice)
        exit_cond := true
        strategy.close("Buy")
else if takeProfitOption == "each_position"
    // Ensure we only check when there is at least one entry
    if array.size(entryPrices) > 0
        // Loop until there are no more entries left
        i = 0
        while i < array.size(entryPrices)
            entryPrice = array.get(entryPrices, i)
            positionSize = array.get(entrySizes, i)
            
            // Check profit condition for each position
            if isTakeProfitCondition(entryPrice)
                exit_cond := true
                // Remove the entry price and size from the arrays once the position is closed
                array.remove(entryPrices, i)
                array.remove(entrySizes, i)
                strategy.close("Buy", qty=positionSize) // Close only the position that reached the target
            else
                // Only increment the index if the current entry is not closed
                i := i + 1

// Trigger BUY alert
if entry_cond
    alert("BUY ALERT: Panic Sell condition triggered", alert.freq_once_per_bar)

// Trigger SELL alert
if exit_cond
    alert("SELL ALERT: Exit condition met (take profit or rebound)", alert.freq_once_per_bar)