3. Custom indicator creation help.
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Custom indicator creation help.


  • Hey I'm working on my mean reversion strategy but in order for me to fully start I need to finish my indicator. So what I want is a Linear regression slope from TALib which ive created then I want standard 8 standard deviations with different distances from the slope (4 above and 4 below). This is what I've got so far;

    class LregressionSlope(bt.indicators):
    params = (
        ('period', 17),
    )

    def __init__(self):
        self.slope = bt.talib.LINEARREG_SLOPE(timeperiod=self.params.period)


class Cstdev(bt.indicators.StandardDeviation, LregressionSlope):
    lines = (
        ('upper_dev1', 1),
        ('upper_dev2', 2),
        ('upper_dev3', 3),
        ('upper_dev4', 4),
        ('lower_dev1', -1),
        ('lower_dev2', -2),
        ('lower_dev3', -3),
        ('lower_dev4', -4)
    )
    params = (
        ('period', 14),
        ('movav', 'LregressionSlope')
    )

    def __init__(self):
        self.upper_dev1 = bt.indicators.StandardDeviation(self.lines.data, self)
        self.upper_dev2 = bt.indicators.StandardDeviation()
        self.upper_dev3 = bt.indicators.StandardDeviation()
        self.upper_dev4 = bt.indicators.StandardDeviation()
        self.lower_dev1 = bt.indicators.StandardDeviation()
        self.lower_dev2 = bt.indicators.StandardDeviation()
        self.lower_dev3 = bt.indicators.StandardDeviation()
        self.lower_dev4 = bt.indicators.StandardDeviation()

    I want the stdev to inherit the 'LregressionSlope' as its movav and then build the deviations around that. Any way I can plot it individually as I have a trading background and im still a novice (if that) coder. Thanks for any help!

    Regards,

    cept0r

    0

  • Reading trough all the docs again and going trough the 'parttimelarry' videos again will post updated code later.

    0

  • Okay I'm working on just getting the LINEARREG_SLOPE to plot to begin with.
    I'm getting this output error:

    self.lines[i].array = array.array(str('d'), o)
TypeError: 'numpy.float64' object is not iterable

    When running this code:

    #  Imports
import backtrader as bt
from backtrader.talib import LINEARREG_SLOPE


class LregressionSlope(bt.talib.LINEARREG_SLOPE):
    lines = ('slope',)
    params = (
        ('timeperiod', 17),
    )

    def __init__(self):
        self.slope = bt.talib.LINEARREG_SLOPE(self.data, timeperiod=self.params.timeperiod)

    def __next__(self):
        pass```
    0

  • Here is my backtester setup:

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

import backtrader as bt
import pandas as pd
import datetime
from strat.examplestrat_04 import LregressionSlope

class CommInfoFractional(bt.CommissionInfo):
    def getsize(self, price, cash):
        """Returns fractional size for cash operation @price"""
        return self.p.leverage * (cash / price)


startcash = 1000000
cerebro = bt.Cerebro()
cerebro.addindicator(LregressionSlope)

#  Datafeed
btc = pd.read_csv('/home/dev/PycharmProjects/Backtesting/csvdata/BTCUSDT-1m-data.csv',
                  index_col='timestamp',
                  parse_dates=True
                  )

feed = bt.feeds.PandasData(
    dataname=btc,

    fromdate=datetime.datetime(2020, 1, 1),
    todate=datetime.datetime(2020, 1, 2),

    timeframe=bt.TimeFrame.Minutes,

)

cerebro.adddata(feed)
cerebro.broker.setcash(startcash)

cerebro.addsizer(bt.sizers.PercentSizer, percents=0.05)
cerebro.broker.addcommissioninfo(CommInfoFractional())
cerebro.broker.setcommission(commission=0.0025, leverage=50)

cerebro.run()

portvalue = cerebro.broker.getvalue()
pnl = portvalue - startcash

print('Final Portfolio Value: ${}'.format(round(portvalue, 2)))
print('P/L: ${}'.format(round(pnl, 2)))

cerebro.plot(style='candlestick')
    0

  • Using btalib instead and going trough the docs there..

    0

  • Let us know how you get on and if you still need help after you work through the docs. Good luck.

    0 3 Replies

  • @run-out
    All right I managed to solve it using 4 of these indicators:

    #  Imports
import backtrader as bt


class MeanReversionLong(bt.Strategy):
    lines = ('kama', 'mean'
             'top1', 'emamean'
             'bot1', 'emamean'
             'top2', 'emadev1'
             'bot2', 'emadev1'
             'top3', 'emadev2'
             'bot3', 'emadev2'
             'top4', 'emadev3'
             'bot4', 'emadev3')

    params = dict(period=30,
                  fast=2,
                  slow=30,
                  perc=2.5)

    def __init__(self):
        emamean = bt.indicators.AdaptiveMovingAverageEnvelope(period=9, fast=1, slow=7, perc=0.2, plotname='mean')
        emadev1 = bt.indicators.AdaptiveMovingAverageEnvelope(period=9, fast=1, slow=7, perc=0.4, plotname='dev1')
        emadev2 = bt.indicators.AdaptiveMovingAverageEnvelope(period=9, fast=1, slow=7, perc=0.8, plotname='dev2')
        emadev3 = bt.indicators.AdaptiveMovingAverageEnvelope(period=9, fast=1, slow=7, perc=1.2, plotname='dev3')

    But now I need to identify each "band" like I do it in my lines section, because when I plot it it only identifies the moving average which is the same for all indicators.

    0

  • @run-out
    AdaptiveMovingAverageEnvelope

    Alias:

    KAMAEnvelope, MovingAverageAdaptiveEnvelope

    AdaptiveMovingAverage and envelope bands separated “perc” from it

    Formula:

    kama (from AdaptiveMovingAverage)

top = kama * (1 + perc)

bot = kama * (1 - perc)

    See also:

    http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:moving_average_envelopes

    Lines:

    kama

top

bot

    Params:

    period (30)

fast (2)

slow (30)

perc (2.5)

        def __init__(self):

        emamean = bt.indicators.AdaptiveMovingAverageEnvelope(period=30, fast=1, slow=8, perc=0.2, plotname='mean')
        emadev1 = bt.indicators.AdaptiveMovingAverageEnvelope(period=30, fast=1.2, slow=8.2, perc=0.4, plotname='dev1')
        emadev2 = bt.indicators.AdaptiveMovingAverageEnvelope(period=30, fast=1.4, slow=8.5, perc=0.8, plotname='dev2')
        emadev3 = bt.indicators.AdaptiveMovingAverageEnvelope(period=30, fast=1.8, slow=8.9, perc=1.2, plotname='dev3')

        top1 = emamean()

    How do I create a unique identifier on each respective band ? or what is the calculation I need to provide inside "top1" for example.

    And also;
    Should I create an indicator or just develop within the strategy what is the best or rather easiest approach?

    0

  • Maybe I should calculate inside the lines or parameters.. hmm

    0

  • @run-out
    All right I'm kind of stuck on this calculation.. I changed my code but I can't seem to get the "top" code done right. No output errors but it won't plot.
    here is the code;

    from backtrader.indicators import AdaptiveMovingAverageEnvelope

amae = AdaptiveMovingAverageEnvelope


class Adaptive_ma1(amae):

    lines = ('kama',
             'top',
             'bot')

    params = dict(period=27,
                  fast=1.0,
                  slow=8,
                  perc=0.2)

    def __init__(self):
        self.l.kama = amae(period=self.p.period)
        self.l.top = self.l.kama * (1 + amae(perc=self.p.perc))
        #  self.l.bot = self.l.kama * (1 - ama(self.data, self.p.perc))

    def __next__(self):
        pass

    here is the plot:
    link text

    This is what I need to calculate:
    top = kama * (1 + perc)

    Thanks in advance!

    0
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