StochRSI رجحان سے باخبر رہنے کی حکمت عملی کے ساتھ ملٹی پیریڈ گاوسی چینل

/*backtest
start: 2024-02-19 00:00:00
end: 2025-02-16 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy(title="Demo GPT - Gaussian Channel Strategy v3.0", overlay=true, commission_type=strategy.commission.percent, commission_value=0.1, slippage=0, default_qty_type=strategy.percent_of_equity, default_qty_value=250)

// ============================================
// Gaussian Functions (Must be at top)
// ============================================
f_filt9x(_a, _s, _i) =>
    var int _m2 = 0, var int _m3 = 0, var int _m4 = 0, var int _m5 = 0, var int _m6 = 0,
    var int _m7 = 0, var int _m8 = 0, var int _m9 = 0, var float _f = 0.0
    _x = 1 - _a
    _m2 := _i == 9 ? 36 : _i == 8 ? 28 : _i == 7 ? 21 : _i == 6 ? 15 : _i == 5 ? 10 : _i == 4 ? 6 : _i == 3 ? 3 : _i == 2 ? 1 : 0
    _m3 := _i == 9 ? 84 : _i == 8 ? 56 : _i == 7 ? 35 : _i == 6 ? 20 : _i == 5 ? 10 : _i == 4 ? 4 : _i == 3 ? 1 : 0
    _m4 := _i == 9 ? 126 : _i == 8 ? 70 : _i == 7 ? 35 : _i == 6 ? 15 : _i == 5 ? 5 : _i == 4 ? 1 : 0
    _m5 := _i == 9 ? 126 : _i == 8 ? 56 : _i == 7 ? 21 : _i == 6 ? 6 : _i == 5 ? 1 : 0
    _m6 := _i == 9 ? 84 : _i == 8 ? 28 : _i == 7 ? 7 : _i == 6 ? 1 : 0
    _m7 := _i == 9 ? 36 : _i == 8 ? 8 : _i == 7 ? 1 : 0
    _m8 := _i == 9 ? 9 : _i == 8 ? 1 : 0
    _m9 := _i == 9 ? 1 : 0
    _f := math.pow(_a, _i) * nz(_s) + _i * _x * nz(_f[1]) - (_i >= 2 ? _m2 * math.pow(_x, 2) * nz(_f[2]) : 0) + (_i >= 3 ? _m3 * math.pow(_x, 3) * nz(_f[3]) : 0) - (_i >= 4 ? _m4 * math.pow(_x, 4) * nz(_f[4]) : 0) + (_i >= 5 ? _m5 * math.pow(_x, 5) * nz(_f[5]) : 0) - (_i >= 6 ? _m6 * math.pow(_x, 6) * nz(_f[6]) : 0) + (_i >= 7 ? _m7 * math.pow(_x, 7) * nz(_f[7]) : 0) - (_i >= 8 ? _m8 * math.pow(_x, 8) * nz(_f[8]) : 0) + (_i == 9 ? _m9 * math.pow(_x, 9) * nz(_f[9]) : 0)
    _f

f_pole(_a, _s, _i) =>
    _f1 = f_filt9x(_a, _s, 1)
    _f2 = _i >= 2 ? f_filt9x(_a, _s, 2) : 0.0
    _f3 = _i >= 3 ? f_filt9x(_a, _s, 3) : 0.0
    _f4 = _i >= 4 ? f_filt9x(_a, _s, 4) : 0.0
    _f5 = _i >= 5 ? f_filt9x(_a, _s, 5) : 0.0
    _f6 = _i >= 6 ? f_filt9x(_a, _s, 6) : 0.0
    _f7 = _i >= 7 ? f_filt9x(_a, _s, 7) : 0.0
    _f8 = _i >= 8 ? f_filt9x(_a, _s, 8) : 0.0
    _f9 = _i == 9 ? f_filt9x(_a, _s, 9) : 0.0
    _fn = _i == 1 ? _f1 : _i == 2 ? _f2 : _i == 3 ? _f3 : _i == 4 ? _f4 : _i == 5 ? _f5 : _i == 6 ? _f6 : _i == 7 ? _f7 : _i == 8 ? _f8 : _i == 9 ? _f9 : na
    [_fn, _f1]

// ============================================
// Date Filter
// ============================================
startDate = input(timestamp("1 Jan 2018"), "Start Date", group="Time Settings")
endDate = input(timestamp("31 Dec 2069"), "End Date", group="Time Settings")
timeCondition = true

// ============================================
// Stochastic RSI (Hidden Calculations)
// ============================================
stochRsiK = input.int(3, "Stoch RSI K", group="Stochastic RSI", tooltip="Only for calculations, not visible")
stochRsiD = input.int(3, "Stoch RSI D", group="Stochastic RSI")
rsiLength = input.int(14, "RSI Length", group="Stochastic RSI")
stochLength = input.int(14, "Stochastic Length", group="Stochastic RSI")

rsiValue = ta.rsi(close, rsiLength)
k = ta.sma(ta.stoch(rsiValue, rsiValue, rsiValue, stochLength), stochRsiK)
d = ta.sma(k, stochRsiD)

// ============================================
// Gaussian Channel
// ============================================
gaussianSrc = input(hlc3, "Source", group="Gaussian")
poles = input.int(4, "Poles", minval=1, maxval=9, group="Gaussian")
samplingPeriod = input.int(144, "Sampling Period", minval=2, group="Gaussian")
multiplier = input.float(1.414, "Multiplier", step=0.1, group="Gaussian")
reducedLag = input.bool(false, "Reduced Lag Mode", group="Gaussian")
fastResponse = input.bool(false, "Fast Response Mode", group="Gaussian")

// Gaussian Calculations
beta = (1 - math.cos(4 * math.asin(1) / samplingPeriod)) / (math.pow(1.414, 2 / poles) - 1)
alpha = -beta + math.sqrt(math.pow(beta, 2) + 2 * beta)
lag = (samplingPeriod - 1) / (2 * poles)

srcData = reducedLag ? gaussianSrc + (gaussianSrc - gaussianSrc[lag]) : gaussianSrc
trData = reducedLag ? ta.tr(true) + (ta.tr(true) - ta.tr(true)[lag]) : ta.tr(true)

[mainFilter, filter1] = f_pole(alpha, srcData, poles)
[trFilter, trFilter1] = f_pole(alpha, trData, poles)

finalFilter = fastResponse ? (mainFilter + filter1) / 2 : mainFilter
finalTrFilter = fastResponse ? (trFilter + trFilter1) / 2 : trFilter

upperBand = finalFilter + finalTrFilter * multiplier
lowerBand = finalFilter - finalTrFilter * multiplier

// ============================================
// Trading Logic
// ============================================
longCondition = 
  finalFilter > finalFilter[1] and      // Green Channel
  close > upperBand and                 // Price above upper band
  (k >= 80 or k <= 20) and             // Stoch RSI condition
  timeCondition

exitCondition = ta.crossunder(close, upperBand)

if longCondition
    strategy.entry("Long", strategy.long)

if exitCondition
    strategy.close("Long")

// ============================================
// Visuals (Gaussian Only)
// ============================================
bandColor = finalFilter > finalFilter[1] ? color.new(#00ff00, 0) : color.new(#ff0000, 0)
plot(finalFilter, "Filter", bandColor, 2)
plot(upperBand, "Upper Band", bandColor)
plot(lowerBand, "Lower Band", bandColor)
fill(plot(upperBand), plot(lowerBand), color.new(bandColor, 90))

barcolor(close > open and close > upperBand ? color.green : 
         close < open and close < lowerBand ? color.red : na)