Custom indicator creation help.

cept0r

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

cept0r

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

cept0r

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```

cept0r

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')

cept0r

Using btalib instead and going trough the docs there..

run-out

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

cept0r

@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.

cept0r

@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?

cept0r

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

cept0r

@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!