PInescript: converting strategy into study

Question

I am trying to convert to this strategy into a study to generate signals - link

However, the study does not show exact same entry points as the strategy.

After making a few modifications to that strategy into the study I made this

//@version=4
study("MACD Strategy", overlay=true)

// FUNCTIONS

Ema(src,p) =>
    ema = 0.
    sf = 2/(p+1)
    ema := nz(ema[1] + sf*(src - ema[1]),src)

Sma(src,p) => a = cum(src), (a - a[max(p,0)])/max(p,0)

Atr(p) =>
    atr = 0.
    Tr = max(high - low, max(abs(high - close[1]), abs(low - close[1])))
    atr := nz(atr[1] + (Tr - atr[1])/p,Tr)

/// TREND
ribbon_period = input(34, "Period", step=1)

leadLine1 = ema(close, ribbon_period)
leadLine2 = sma(close, ribbon_period)

p3 = plot(leadLine1, color= #53b987, title="EMA", transp = 50, linewidth = 1)
p4 = plot(leadLine2, color= #eb4d5c, title="SMA", transp = 50, linewidth = 1)
fill(p3, p4, transp = 60, color = leadLine1 > leadLine2 ? #53b987 : #eb4d5c)


// MACD
fast_length = input(title="Fast Length", type=input.integer, defval=3)
slow_length = input(title="Slow Length", type=input.integer, defval=5)
src = input(title="Source", type=input.source, defval=close)
signal_length = input(title="Signal Smoothing", type=input.integer, minval = 1, maxval = 50, defval = 2)
sma_source = input(title="Simple MA(Oscillator)", type=input.bool, defval=false)
sma_signal = input(title="Simple MA(Signal Line)", type=input.bool, defval=true)

// Plot colors
col_grow_above = #26A69A
col_grow_below = #FFCDD2
col_fall_above = #B2DFDB
col_fall_below = #EF5350
col_macd = #0094ff
col_signal = #ff6a00

// Calculating
fast_ma = sma_source ? Sma(src, fast_length) : Ema(src, fast_length)
slow_ma = sma_source ? Sma(src, slow_length) : Ema(src, slow_length)
macd = fast_ma - slow_ma
signal = sma_signal ? Sma(macd, signal_length) : Ema(macd, signal_length)
hist = macd - signal

//plot(hist, title="Histogram", style=plot.style_columns, color=(hist>=0 ? (hist[1] < hist ? col_grow_above : col_fall_above) : (hist[1] < hist ? col_grow_below : col_fall_below) ), transp=0 )


// TAKE PROFIT AND STOP LOSS
long_tp1_inp = input(1, title='Long Take Profit 1 %', step=0.1)/100
long_tp1_qty = input(10, title="Long Take Profit 1 Qty", step=1)

long_tp2_inp = input(5, title='Long Take Profit 2%', step=0.1)/100
long_tp2_qty = input(50, title="Long Take Profit 2 Qty", step=1)



// Stop Loss
multiplier = input(2.2, "SL Mutiplier", minval=1, step=0.1)
ATR_period=input(17,"ATR period", minval=1, step=1)

// Strategy
entry_long=crossover(macd,signal) and leadLine2 < leadLine1
entry_price_long=valuewhen(entry_long,close,0)
SL_floating_long = entry_price_long - multiplier*Atr(ATR_period)
exit_long= close < SL_floating_long 

//if(entry_long)
//    label.new(bar_index, na,text="Long", color=color.red,style=label.style_arrowup, yloc=yloc.belowbar)

plotshape(entry_long, style=shape.triangleup,location=location.belowbar, color=color.green)

However, this gives wrong and extra signals compared to the strategy. I am not able to understand why, because the logic of the code remains the same I am just plotting instead of using strategy.long . It should give me the same signals right?

Answer 1

The strategy delegates some of its entry/exit logic to the broker emulator in these line:

if testPeriod()
    strategy.entry("long", strategy.long, comment="Long", when=entry_long)
    strategy.exit("TP1","long", qty_percent=long_tp1_qty, limit=long_take_level_1)//, trail_points=entry_price_long * long_trailing / syminfo.mintick, trail_offset=entry_price_long * long_trailing / syminfo.mintick)
    strategy.exit("TP2", qty_percent=long_tp2_qty, limit=long_take_level_2) //, trail_points=entry_price_long * long_trailing / syminfo.mintick, trail_offset=entry_price_long * long_trailing / syminfo.mintick)
    strategy.close("long", when=exit_long, comment="exit long" )

In order to reproduce that logic in a study, you will need to understand what it's doing and then replicate it using your own code.