لہر کے رجحان اور متنوع سرمایہ کاری پر مبنی ذہین سائیکل ٹریڈنگ حکمت عملی

/*backtest
start: 2024-11-19 00:00:00
end: 2024-12-18 08:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5

// Copyright (c) 2024 Seth Ethington.
// All rights reserved.
//
// If this script provides you Bread then share the Dough!
// BTC (God's Money) Address: bc1qrpxvea8ze4ayj2vtr0slp774rulm898gyhe3ss
//
// Redistribution and use in source and binary forms, 
// whether you tweak it or not, is totally fine, 
// but only if you swear on your life that BTC is God's Money! 
// 
// If you're redistributing the source code, 
// you must keep the above copyright notice and, 
// more importantly, the sacred BTC address!
//


strategy(title="Cipher DCA Strategy", shorttitle="Cipher DCA", overlay=false, initial_capital=100, pyramiding=30, currency=currency.USD,  slippage=1, commission_type=strategy.commission.percent, commission_value=0.1, default_qty_type=strategy.percent_of_equity, process_orders_on_close=true)

// Input parameters for the starting date
startDate = input(timestamp("2019-01-01 00:00:00"), title="Start Date (YYYY-MM-DD HH:MM:SS)")


// Input parameters for the indicator
fastLength = input.int(4, title="Fast Wave Length", group="Wave Calculator")  // Length for EMA smoothing of the price channel
slowLength = input.int(33, title="Slow Wave Length", group="Wave Calculator")  // Length for EMA smoothing of the trend channel
wayOverBoughtLevel = input.float(33, title="Way OverBought Level", group="Wave Calculator")
overBoughtLevel = input.float(25, title="Over Bought Level", group="Wave Calculator")
wayOverSoldLevel = input.float(-33, title="Way Over Sold Level", group="Wave Calculator")
overSoldLevel = input.float(-25, title="Over Sold Level", group="Wave Calculator")
accumulatingLevel = input.float(0, title="Accumulating Level", group="Wave Calculator")


// Calculate the average price (HLC3 = (High + Low + Close) / 3)
averagePrice = hlc3

// Compute the smoothed average price (ESA: Exponential Smoothing Average)
exponentialSmoothingAverage = ta.ema(averagePrice, fastLength)

// Compute the deviation (D) between the price and the smoothed average
priceDeviation = ta.ema(math.abs(averagePrice - exponentialSmoothingAverage), fastLength)

// Compute the commodity index (CI) which is normalized price movement
commodityIndex = (averagePrice - exponentialSmoothingAverage) / (0.015 * priceDeviation)

// Smooth the commodity index to create Wave Trend 1 (WT1)
fastWaveTrend = ta.ema(commodityIndex, slowLength)
// //log.info("fastWaveTrend= " + str.tostring(fastWaveTrend))

// Further smooth WT1 using a simple moving average to create Wave Trend 2 (WT2)
slowWaveTrend = ta.sma(fastWaveTrend, 5)
// //log.info("slowWaveTrend= " + str.tostring(slowWaveTrend))


// Plot the center line (0) for reference
plot(0, color=color.white, title="Center Line")

// Plot overbought and oversold levels
plot(wayOverBoughtLevel, color=color.red, title="Way Overbought")
plot(overBoughtLevel, color=color.red, title="Overbought")
plot(overSoldLevel, color=color.green, title="Oversold")
plot(wayOverSoldLevel, color=color.green, title="Way Oversold")

// Plot WT1 and WT2 as filled areas for better visibility
plot(fastWaveTrend, style=plot.style_area, color=color.new(color.blue, 0), title="Fast Wave")
plot(slowWaveTrend, style=plot.style_area, color=color.new(color.navy, 30), title="Slow Wave")

// Highlight the difference between fastWave vs slowWave
waveTrendDifference = fastWaveTrend - slowWaveTrend

// //log.info("waveTrendDifference=" + str.tostring(waveTrendDifference))
plot(waveTrendDifference, color=color.new(color.yellow, 30),style=plot.style_area, title="WT1 - WT2 Difference") //No transparency

// Plot buy and sell signals at crossovers
isCrossover = ta.cross(fastWaveTrend, slowWaveTrend)
// //log.info("isCrossover=" + str.tostring(isCrossover))
plot(isCrossover ? slowWaveTrend : na, color=(slowWaveTrend - fastWaveTrend > 0 ? color.red : color.green), style=plot.style_circles, linewidth=4, title="Crossover Signals")

float waveTrend = na
if (slowWaveTrend > 0 and fastWaveTrend > 0) 
    waveTrend := math.max(slowWaveTrend, fastWaveTrend)
    // //log.info("Both trends are positive. waveTrend set to max value: " + str.tostring(waveTrend))
else if (slowWaveTrend < 0 and fastWaveTrend < 0)
    waveTrend := math.min(slowWaveTrend, fastWaveTrend)
    // //log.info("Both trends are negative. waveTrend set to min value: " + str.tostring(waveTrend))
else 
    waveTrend := 0
    // //log.info("Trends are mixed. waveTrend set to 0.")

// Time to Sell
isCrossingDown = waveTrendDifference < 0

// Time to Buy
isCrossingUp = waveTrendDifference > 0


//-----------------------------------------------------------


// Detect Bull Market and Bear Market using the Awesome Oscillator
// User input for AO thresholds
ao_threshold = input.float(-10, "AO Bull Market Threshold", minval=-50, maxval=50, step=1, group = "Bear and Bull Thresholds")
ao_cycletop_threshold = input.float(5, "AO Bear Market Threshold", minval=0, maxval=200, step=1, group = "Bear and Bull Thresholds")

// Define the Awesome Oscillator
ao = ta.sma(hl2, fastLength) - ta.sma(hl2, slowLength)

// Convert current bar time to the first day of the month for monthly calculations
currentMonthStart = timestamp(year, month, 1, 0, 0)
prevMonthStart = time - (time - currentMonthStart)

// Calculate AO for the start of the month and previous month
aoCurrentMonth = request.security(syminfo.tickerid, 'M', ao[0])
aoPrevMonth1    = request.security(syminfo.tickerid, 'M', ao[1])
aoPrevMonth2    = request.security(syminfo.tickerid, 'M', ao[2])

// Detect bull market based on monthly AO
isBullMarket = aoCurrentMonth > aoPrevMonth1 and aoPrevMonth1 > aoPrevMonth2 and aoCurrentMonth > ao_threshold

// Detect cycle top based on monthly AO
isBearMarket = aoCurrentMonth > ao_cycletop_threshold and aoPrevMonth1 > aoCurrentMonth

// Detect when a bull market is starting
var bool isBullMarketStarting = na
if (not isBullMarket[1] and isBullMarket)
    isBullMarketStarting := true
else
    isBullMarketStarting := false

// Logging
//log.info("isBullMarket is " + str.tostring(isBullMarket))
//log.info("isCycleTop is " + str.tostring(isBearMarket))

// Plot transparent overlays for Bull Market and Cycle Top
overlayColor = isBullMarket ? color.new(color.green, 80) : isBearMarket ? color.new(color.red, 60) : na
bgcolor(overlayColor, title="Market Condition Overlay")


//----------------------------------------------------------


// Calculate Potential Liquidations and Golden Buy Zones
volLength = input.int(20, "Volume Length", minval=1, group="Golden Buy Indicator")
volStdDevThreshold = input.float(2.0, "Volume Standard Diviation Threshold", step=0.1, group="Golden Buy Indicator")
aoWeeklyThreshold = input.int(0, "Awesome Oscillator Oversold Threshold", step=1, group="Golden Buy Indicator")


// Start Accumulating when the price is oversold or price action is flat
isStartAccumulating = waveTrend <= accumulatingLevel and not isBearMarket

// Start Selling when we are now in a Bull Market
isStartSelling = waveTrend > accumulatingLevel

// Calculate Overbought and Oversold Levels
isOverSold = waveTrend < overSoldLevel
isWayOverSold = waveTrend < wayOverSoldLevel
isOverBought = waveTrend > overBoughtLevel
isWayOverBought = waveTrend > wayOverBoughtLevel
//log.info("isOverSold= " + str.tostring(isOverSold) + " isWayOverSold= " + str.tostring(isWayOverSold) + " isOverBought= " + str.tostring(isOverBought) + " isWayOverBought= " + str.tostring(isWayOverBought))

//Weekly Awesome Oscillator to detect oversold levels
aoWeekly = request.security(syminfo.tickerid, "W", ao)

// Get standard deviation of volume over last 20 bars
volumeStDev = ta.stdev(volume, volLength)

// Detect volume spikes
volumeSpike = volume > (ta.sma(volume, volLength) + volStdDevThreshold * volumeStDev)

isGoldenBuyZone = volumeSpike and aoWeekly < aoWeeklyThreshold and not isBearMarket
plotshape(series=isGoldenBuyZone ? -60 : na, style=shape.triangleup, location=location.absolute, color=color.yellow, size=size.tiny, offset=0, title="Golden Buy Zone")

isMarketTop = volumeSpike and aoWeekly > -aoWeeklyThreshold and isBullMarket
plotshape(series=isMarketTop ? 60 : na, style=shape.triangledown, location=location.absolute, color=color.purple, size=size.tiny, offset=0, title="Market Top")



//---------------------------------------------------------

// Buying and Selling Input parameters for the indicator
isBullMarketStartingPercent = input.float(1.0, title="Starting a Bull Market Percent", step=0.01, group="Buy and Sell")
goldenBuyPercent = input.float(0.00006, title="Golden Buy Percent", step=0.01, group="Buy and Sell")
wayOverSoldPercent = input.float(0.00004, title="Way Over Sold Percent", step=0.01, group="Buy and Sell") 
overSoldPercent = input.float(0.00002, title="Over Sold Percent", step=0.01, group="Buy and Sell")
crossOverPercent = input.float(0.00002, title="Cross Over Percent", step=0.01, group="Buy and Sell")
overBoughtPercent = input.float(0.00005, title="Over Bought Percent", step=0.01, group="Buy and Sell")
wayOverBoughtPercent = input.float(0.00006, title="Way Over Bought Percent", step=0.01, group="Buy and Sell")

//Execute Buy and Sell Strategy
// Execute only if the bar's time is after the start date
if (true)
    if ((isCrossover and isCrossingUp and isStartAccumulating) or isGoldenBuyZone or isBullMarketStarting)
        if (isGoldenBuyZone) 
            strategy.entry("Golden Buy", strategy.long, qty = goldenBuyPercent * strategy.initial_capital)
            //log.info("Golden Buy " + str.tostring(goldenBuyPercent))
        else if (isBullMarketStarting)
            strategy.entry("Bull Buy", strategy.long, qty = isBullMarketStartingPercent * strategy.initial_capital)
            //log.info("Way Over Sold Buy " + str.tostring(wayOverSoldPercent))    
        else if (isWayOverSold) 
            strategy.entry(str.tostring(strategy.opentrades), strategy.long, qty = wayOverSoldPercent * strategy.initial_capital)
            //log.info("Way Over Sold Buy " + str.tostring(wayOverSoldPercent))
        else if (isOverSold)  
            strategy.entry(str.tostring(strategy.opentrades), strategy.long, qty = overSoldPercent * strategy.initial_capital)
            //log.info("Over Sold Buy " + str.tostring(overSoldPercent))
        else if (isCrossover)  
            strategy.entry(str.tostring(strategy.opentrades), strategy.long, qty = crossOverPercent * strategy.initial_capital)
            //log.info("Crossover Buy " + str.tostring(crossOverPercent))
    else if (isCrossover and isCrossingDown and isStartSelling) or isBearMarket or isMarketTop
        if (isBearMarket)
            strategy.close_all("Close all")
            //log.info("Closing All Open Positions")
        else if (isWayOverBought or isMarketTop) 
            int openTrades = strategy.opentrades  // Get the number of open trades
            int tradesToClose = math.floor(openTrades * wayOverBoughtPercent)
            //log.info("# of tradesToClose= " + str.tostring(tradesToClose))
    
            // Loop through and close 100% of the open trades determined
            for i = 0 to tradesToClose
                // Close the trade by referencing the correct index
                strategy.close(str.tostring(openTrades - 1 - i), qty_percent = 100)
                //log.info("Sell 100%: Closed trade # " + str.tostring(openTrades - 1 - i))
        else if (isOverBought) 
            int openTrades = strategy.opentrades  // Get the number of open trades
            int tradesToClose = math.floor(openTrades * overBoughtPercent) 
            //log.info("# of tradesToClose= " + str.tostring(tradesToClose))
    
            // Loop through and close 100% of the open trades determined
            for i = 0 to tradesToClose
                // Close the trade by referencing the correct index
                strategy.close(str.tostring(openTrades - 1 - i), qty_percent = 100)
                //log.info("Sell 100%: Closed trade # " + str.tostring(openTrades - 1 - i))
        else if (isStartSelling)
            strategy.close(str.tostring(strategy.opentrades - 1), qty_percent =50)
            //log.info("Sell 100% of Last Trade: Closed trade # " + str.tostring(strategy.opentrades - 1))