ওরিয়ন ট্রেডিং কৌশল

/*backtest
start: 2023-09-17 00:00:00
end: 2023-09-21 22:00:00
period: 3m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// © OrionAlgo
//          () /? | () |\|   /\ |_ (_, ()          //
//@version=4

version = '2.0'

strategy("Orion Algo Strategy v"+version, shorttitle="Orion Algo Strategy v"+version, overlay=false, pyramiding=100)


// Getting inputs --------------------------------------------------------------
userAgreement = input(true, title='I understand that Orion Algo cannot be 100% accurate and overall performance will shift with market conditions. While Orion Algo increases my chances of entering better positions, I must use smart trade management. ', type=input.bool,group='User Agreement ─────────────',
  tooltip='In order to use Orion Algo, you must click the checkbox to acknowledge the user agreement')

src = close
//smoothing inputs -------------------------------------------------------------

//superSmooth = input(true, title='Super Smooth', inline='Super Smooth', group='Smoothing ─────────────────')
superSmooth = true
smoothType = 1
superSmoothStrength = input(10, title='Super Smooth',minval = 3, inline='Super Smooth', group='Signal ────────────────────',
  tooltip='Smooths the signal. Lower values move pivots to the left while increasing noise, higher values move pivots to the right and reduce noise. 8 is a good mix of both') // set to timeframe for decent results?
//trendSmoothing = input(30, title='Trend Smooth',minval = 3, group='Smoothing ─────────────────') // set to timeframe for decent results?
trendSmoothing = 30 // set to timeframe for decent results?

showPrediction = input(false, title='Prediction', group='Signal ────────────────────',inline='prediction')
predictionBias = input(0.45, minval = 0.,maxval=1., step=0.05, title='Bias', group='Signal ────────────────────',inline='prediction')
showPredictionCurve = input(true, title='Curve', group='Signal ────────────────────',inline='prediction', tooltip='Prediction model that attempts to predict short range reversals (0-2 bars). Adjust Bias to change the prediction curve.')

//momentum wave inputs ---------------------------------------------------------
showMomentumWave = input(true, 'Momentum Wave', group='Momentum Wave ─────────────', inline='mom')
momentumWaveLength = input(3, '', group='Momentum Wave ─────────────', inline='mom', tooltip='Secondary signal that shows medium to large movements based on the input variable. The wave will change depending on the current timeframe.')
momentumOutside = input(true, 'Position Outside', group='Momentum Wave ─────────────', inline='mom2', tooltip='Positions the wave outside of the main signal area.')

//visuals input-----------------------------------------------------------------

useDarkMode = input(true, 'Dark Mode', group='Visuals ───────────────────',inline='Colors')

// 0:backgroundlines, 1:signal, 2:bullish, 3:bearish, 4:hiddenbull, 5:hiddenbear, 6:deltav, 7:prediction, 8:predictionbull, 9:predictionbear, 10:dash, 11:mom2

visualMode = input('Pro', 'Mode',options=['Beginner', 'Pro'] ,group='Visuals ───────────────────')

dashOn = input(true, "Dashboard", group='Dashboard ─────────────────', inline='dash', tooltip='A dashboard with some usefual stats')
  
dashColor = color.new(#171a27, 100)

showPivots = input(true, title='Signal Pivots', group='Pivots ────────────────────',inline='pivots')
showPredictionPivots = input(false, title='Prediction Pivots', group='Pivots ────────────────────',inline='pivots')


// Functions -------------------------------------------------------------------

f_secureSecurity(_symbol, _res, _src) => security(_symbol, _res, _src,barmerge.gaps_on, lookahead = barmerge.lookahead_on) 

f_slope(x) =>
    slopePeriod = 1
    (x - x[slopePeriod]) / slopePeriod

f_superSmooth(inputVal,smoothType) =>
    smoothType==1? (hma(inputVal,superSmoothStrength)) :
      smoothType==2? (ema((ema((ema(inputVal,3)),3)),superSmoothStrength)):
      smoothType==3? linreg(inputVal,superSmoothStrength,0) : 
      smoothType==4? (hma(inputVal,superSmoothStrength * momentumWaveLength)) : na

f_bias(bias, min, max) =>
    (bias * (max - min) ) + min

f_resInMinutes() =>
    _resInMinutes = timeframe.multiplier * (
      timeframe.isseconds ? 1. / 60. :
      timeframe.isminutes ? 1.       :
      timeframe.isdaily   ? 1440.    :
      timeframe.isweekly  ? 10080.   :
      timeframe.ismonthly ? 43800.   : na)

f_resFromMinutes(_minutes) =>
    _minutes     <= 0.0167       ? "1S"  :
      _minutes   <= 0.0834       ? "5S"  :
      _minutes   <= 0.2500       ? "15S" :
      _minutes   <= 0.5000       ? "30S" :
      _minutes   <= 1            ? "1":
      _minutes   <= 1440         ? tostring(round(_minutes)) :
      _minutes   <= 43800        ? tostring(round(min(_minutes / 1440, 365))) + "D" :
      tostring(round(min(_minutes / 43800, 12))) + "M"
      
f_output_signal()=>    
    a = ((ema(close, 12) - ema(close, 26)) - ema((ema(close, 12) - ema(close, 26)), 8))/10
    b = wpr(8)
    c = (100 * ( close + 2*stdev( close, 21) - sma( close, 21 ) ) / ( 4 * stdev( close, 21 ) ))
    d = (rsi(close - sma(close, 21)[11],8)*2)-100
    e = (rsi(fixnan(100 * rma(change(high) > change(low) and change(high) > 0 ? change(high) : 0, 1) / rma(tr, 1)) - fixnan(100 * rma(change(low) > change(high) and change(low) > 0 ? change(low) : 0, 1) / rma(tr, 1)),8)*2)-100 //causes slow down
    f = rsi((((close-( (sum(volume, 20) - volume)/sum(volume, 20)) + (volume*close/sum(volume, 20)))/((close+( (sum(volume, 20) - volume)/sum(volume, 20)) + (volume*close/sum(volume, 20)))/2)) * 100),8)-100
    g = (rsi(sma(highest(high,14)-lowest(low,14)==0.0?0.0:(close-lowest(low,14))/highest(high,14)-lowest(low,14)-0.5,max(1,int(2))),8)*2)-100 //causes slow down
    avg(a,b,c,d,e,f,g)*2
 
output_signal = f_output_signal()
output_signal := f_superSmooth(output_signal,1)

// output_signal2 = plot(f_superSmoothSlow(f_output_signal()), color=color.blue, linewidth=2)

//Orion Signal Higher Timeframe / Momentum Wave --------------------------------
f_momentumWave(wavelength,smooth) =>
    currentMinutes = f_resInMinutes()
    m = currentMinutes * wavelength //multiply current resolution by momentumWaveLength to get higher resolution
    momentumWaveRes = f_resFromMinutes(m)
    f_secureSecurity(syminfo.tickerid, momentumWaveRes,f_superSmooth(f_output_signal(),1))



// Plot ------------------------------------------------------------------------
f_color(x) =>
    if userAgreement
        white      = useDarkMode ? #e5e4f4 : #505050ff
        lightgray  = useDarkMode ? #808080 : #909090ff
        gray       = useDarkMode ? #808080 : #505050ff
        //blue       = useDarkMode ? #007EA7 : #007EA7ff
        blue       = useDarkMode ? #2862FFFF : #2862FFFF
        
        // 0:backgroundlines, 1:signal, 2:bullish, 3:bearish, 4:hiddenbull, 5:hiddenbear, 6:deltav, 7:prediction, 8:predictionbull, 9:predictionbear, 10:trendbull, 11:trendbear, 12:dash, 13:mom1, 14:mom2
        x==0? lightgray : x==1? gray : x==2? white : x==3? blue : x==4? white : x==5? blue : x==6? blue : x==7? blue : x==8? white : x==9? blue : x==10? blue : x==11? blue : na

// Lines -----------------------------------------------------------------------

h1 = plot(0, "Mid Band", color=f_color(0),editable=0, transp=80)

// Signal ----------------------------------------------------------------------

orionSignal = plot(output_signal, title="Orion Signal Curve", style=plot.style_line,linewidth=1, transp=0, color= f_color(1), offset=0,editable=0)


// Momentum Wave ---------------------------------------------------------------
momWave = f_momentumWave(momentumWaveLength,1)


p_momWave = plot(showMomentumWave? momentumOutside? (momWave/2) -150 : momWave : na, color=f_color(11), linewidth=showMomentumWave and momentumOutside ? 1 : 2, editable =0, transp=50, style=momentumOutside? plot.style_area : plot.style_line, histbase=-200) //two tone color doesnt want to work with this for some reason.

// Divergence ------------------------------------------------------------------

osc = output_signal

plFound = osc > osc [1] and osc[1] < osc[2]
phFound = osc < osc [1] and osc[1] > osc[2]

// bullish

plot(
     plFound and visualMode=='Pro'?  osc[1] - 10 : na,
     offset=0,
     title="Regular Bullish",
     linewidth=3,
     color=showPivots ? f_color(2) :na,
     transp=0,
     style=plot.style_circles,
     editable=0
     )
plotshape(
     plFound and visualMode=='Beginner'?  osc[1] - 10 : na,
     offset=0,
     title="Regular Bullish",
     size=size.tiny,
     color=showPivots ? f_color(2) :na,
     transp=0,
     style=shape.labelup,
     text = 'Buy',
     textcolor= color.black,
     location=location.absolute,
     editable=0
     )


// bearish
plot(
     phFound and visualMode=='Pro'? osc[1] + 10: na,
     offset=0,
     title="Regular Bearish",
     linewidth=3,
     color=showPivots ? f_color(3):na,
     transp=0,
     style=plot.style_circles,
     editable=0
     )
plotshape(
     phFound and visualMode=='Beginner'? osc[1] + 10: na,
     offset=0,
     title="Regular Bearish",
     size=size.tiny,
     color=showPivots ? f_color(3):na,
     transp=0,
     style=shape.labeldown,
     text = 'Sell',
     textcolor= color.white,
     location=location.absolute,
     editable=0
     )



// Delta v ---------------------------------------------------------------------

slope    = f_slope(output_signal)*1.5

// Prediction from Delta v -----------------------------------------------------
output_prediction = f_bias(predictionBias, slope, output_signal)

prediction_bullish = output_prediction>output_prediction[1] and output_prediction[1]<output_prediction[2] ?true:false
prediction_bearish = output_prediction<output_prediction[1] and output_prediction[1]>output_prediction[2] ?true:false

plot(showPrediction and showPredictionCurve?output_prediction:na,title='Prediction Curve', color=f_color(7), editable=0)
//prediction bull
plot(showPrediction?showPredictionPivots?output_prediction>output_prediction[1] and output_prediction[1]<output_prediction[2]?showPredictionCurve?output_prediction:output_signal:na:na:na,
  title='Prediction Bullish',color=f_color(8), style=plot.style_circles, linewidth=2, editable=0)
//prediction bear
plot(showPrediction?showPredictionPivots?output_prediction<output_prediction[1] and output_prediction[1]>output_prediction[2]?showPredictionCurve?output_prediction:output_signal:na:na:na,
  title='Prediction Bearish', color=f_color(9), style=plot.style_circles, linewidth=2, editable=0)

// User Aggreement -------------------------------------------------------------

plotshape(userAgreement==false?0:na,title='Welcome', text='Welcome to Orion Algo! Please double click me to enable signals',textcolor=color.black,color=color.white,offset=0,size=size.huge,style=shape.labeldown,location=location.absolute, transp=0, show_last=1, editable=0)
plotshape(userAgreement==false?0:na,title='Welcome', text='Welcome to Orion Algo! Please double click me to enable signals',textcolor=color.black,color=color.white,offset=-100,size=size.huge,style=shape.labeldown,location=location.absolute, transp=0, show_last=1, editable=0)

// Alerts ----------------------------------------------------------------------

alertcondition(plFound,title='1. Bullish (Big Dot)', message='Bullish Signal (Big Dot)')
alertcondition(phFound,title='2. Bearish (Big Dot)', message='Bearish Signal (Big Dot)')
alertcondition(prediction_bullish,title='3. Prediction Bullish (Small Dot)', message='Prediction Bullish Signal (Small Dot)')
alertcondition(prediction_bearish,title='4. Prediction Bearish (Small Dot)', message='Prediction Bearish Signal (Small Dot)')





// Strategy --------------------------------------------------------------------
i_strategy = input(defval='dca long', title='strategy', options=['simple','dca long'])
i_pyramid = input(10, 'pyramid orders')

// Simple Strat
if (i_strategy == 'simple')
    longCondition = crossover(output_signal, output_signal[1])
    if (longCondition)
        strategy.entry("My Long Entry Id", strategy.long)
    
    shortCondition = crossunder(output_signal, output_signal[1])
    if (shortCondition)
        strategy.entry("My Short Entry Id", strategy.short)

// DCA Strat
i_percent_exit = input(2.0,'percent exit in profit')/100
i_percent_drop = input(2.0,'percent drop before each entry')/100

var entryPrice = 0.0
var exitPrice = 0.0


var inTrade = false
var tradeCount = 0
var moneyInTrade = 0.0

if(output_signal > output_signal[1] and output_signal[1]<=output_signal[2] and i_strategy=='dca long')
//if (true)    
    if (inTrade==false)
        strategy.entry('Long',long=true)
        entryPrice:=close
        moneyInTrade:=close
        exitPrice:=entryPrice + (entryPrice*(i_percent_exit))
        inTrade:=true
        tradeCount := 1
        
    if (inTrade==true and close <= (entryPrice-(entryPrice*(i_percent_drop) )))
        //calculate DCA //math is incorrect!!!
        if (tradeCount <= i_pyramid)
            tradeCount := tradeCount+1
            entryPrice:=close
            moneyInTrade := moneyInTrade+close
            exitPrice2 = moneyInTrade / tradeCount
            exitPrice := exitPrice2 + (exitPrice2 *(i_percent_exit)) 
           
            strategy.entry('Long',long=true)
            

if(close >= exitPrice and inTrade==true and output_signal <= output_signal[1] and output_signal[1]>=output_signal[2] and i_strategy=='dca long')
    inTrade:=false
   
    strategy.close('Long')
    
    


// Dashboard -------------------------------------------------------------------


//deltav
deltav = slope