3. More elegant way in strategy
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More elegant way in strategy

  • D

    Hi

    is there a way to improve the backorder strategy code? Especially the summation method used?

    i converted the indicator:
    https://www.prorealcode.com/prorealtime-indicators/reversal-point-indicator/

    to this code:

    class strategy(bt.Strategy):
    def __init__(self):
        self.sto = btind.Stochastic(period=8, period_dfast=3)

    def next(self):
        if (len(self.data) < 54):
            return

        c1 = self.data.close[-1] < self.data.open[-1] and self.data.close[0] > self.data.open[0]
        c2 = self.data.close[0] > self.data.open[-1]
        low3 = min(self.data.low.get(size=3))
        c3 = low3 < min(self.data.low.get(ago=-1, size=50)) or low3 < min(self.data.low.get(ago=-2, size=50)) or low3 < min(self.data.low.get(ago=-3, size=50))
        c4 = False
        for i in self.sto.get(size=3):
            if i < 20:
                c4 = True
                break
        long = c1 and c2 and c3 and c4

        c5 = self.data.close[-1] > self.data.open[-1] and self.data.close[0] < self.data.open[0]
        c6 = self.data.close[0] < self.data.open[-1]
        high3 = max(self.data.high.get(size=3))
        c7 = high3 > max(self.data.high.get(ago=-1, size=50)) or high3 > max(self.data.high.get(ago=-2, size=50)) or high3 > min(self.data.high.get(ago=-3, size=50))
        c8 = False
        for i in self.sto.get(size=3):
            if i > 80:
                c8 = True
                break
        short = c5 and c6 and c7 and c8

        if long:
            print("LONG", self.data[0])
        if short:
            print("SHORT", self.data[0])
    0
    B
     1 Reply
  • B
    administrators

    @dasch said in More elegant way in strategy:

     c1 = self.data.close[-1] < self.data.open[-1] and self.data.close[0] > self.data.open[0]

    You could pack those calculations in individual indicators. That's only a single line, but you could pack several in a single indicator, depending of the granularity or re-usability you may want for those calculations.

    0
  • D

    Updated it to this:

    '''
//PRC_Reversal point indicator | indicator
//09.04.2017
//Nicolas @ www.prorealcode.com
//Sharing ProRealTime knowledge
// https://www.prorealcode.com/topic/need-help-coding-the-following-reversal-indicator/
// https://www.prorealcode.com/prorealtime-indicators/reversal-point-indicator/

// LONG
//Red/Green candle (reversal)
//Bullish candle close above the open of the previous red candle
//Space to the left (the low of the last 3 candles lower than the low of the last 50 candles)
//default stochastic (8,3,3) was in the oversold area within the last 3 candles

// SHORT
//Green/Red candle (reversal)
//Bearish candle close below the close of the previous green candle
//Space to the left (the high of the last 3 candles higher than the high of the last 50 candles)
//default stochastic (8,3,3) was in the overbought area within the last 3 candles.
'''

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

# Import the backtrader platform
import backtrader as bt
import backtrader.indicators as btind

class ReversalPoint(bt.Indicator):
    lines = ('revpoint',)
    plotinfo = dict(
        # Add extra margins above and below the 1s and -1s
        plotymargin=0.15,

        # Plot a reference horizontal line at 1.0 and -1.0
        plothlines=[1.0, -1.0],

        # Simplify the y scale to 1.0 and -1.0
        plotyticks=[1.0, -1.0])

    # Plot the line "overunder" (the only one) with dash style
    # ls stands for linestyle and is directly passed to matplotlib
    plotlines = dict(revpoint=dict(ls='--'))
    params = dict(
        sto_period=8,
        sto_period_dfast=3,
        sto_oversold=20,
        sto_overbought=80,
        lperiod=50,
        speriod=3,
    )

    def __init__(self):
        self.sto = btind.Stochastic(period=self.p.sto_period, period_dfast=self.p.sto_period_dfast)
        
        self.addminperiod(self.p.lperiod + self.p.speriod)
        
        self.c1 = bt.And(self.data.close(-1) < self.data.open(-1), self.data.close(0) > self.data.open(0))
        self.c2 = self.data.close(0) > self.data.open(-1)
        self.c5 = bt.And(self.data.close(-1) > self.data.open(-1), self.data.close(0) < self.data.open(0))
        self.c6 = self.data.close(0) < self.data.open(-1)

    def next(self):
        sList = self.sto.get(size=self.p.speriod)
        sLow = min(self.data.low.get(size=self.p.speriod))
        lLow1 = min(self.data.low.get(ago=-1, size=self.p.lperiod))
        lLow2 = min(self.data.low.get(ago=-2, size=self.p.lperiod))
        lLow3 = min(self.data.low.get(ago=-3, size=self.p.lperiod))
        sHigh = max(self.data.high.get(size=self.p.speriod))
        lHigh1 = max(self.data.high.get(ago=-1, size=self.p.lperiod))
        lHigh2 = max(self.data.high.get(ago=-2, size=self.p.lperiod))
        lHigh3 = max(self.data.high.get(ago=-3, size=self.p.lperiod))
        
        c1 = self.c1
        c2 = self.c2
        c3 = sLow < lLow1 or sLow < lLow2 or sLow < lLow3
        c4 = len(list(filter(lambda x: (x < self.p.sto_oversold), sList))) > 0
        tLong = c1 and c2 and c3 and c4

        c5 = self.c5
        c6 = self.c6
        c7 = sHigh > lHigh1 or sHigh > lHigh2 or sHigh > lHigh3
        c8 = len(list(filter(lambda x: (x > self.p.sto_overbought), sList))) > 0
        tShort = c5 and c6 and c7 and c8

        if tLong:
            self.revpoint[0] = 1.0
        elif tShort:
            self.revpoint[0] = -1.0
        else:
            self.revpoint[0] = 0.0

    i also changed this calculation:

       c8 = False
        for i in self.sto.get(size=3):
            if i > 80:
                c8 = True
                break

    to this

            c8 = len(list(filter(lambda x: (x > self.p.sto_overbought), sList))) > 0
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