Re: Differing CCI Outputs bta-lib vs Backtrader.Indicators

Backtrader's CCI indicator has a bug, not computing the average absolute deviation in the right way. This results in different CCI values compared to CCI values in TradingView or compared tp the CCI values using TA-Lib (in backtrader).
The bug actually resides in the class MeanDeviation(Indicator), in the deviations.py file. MeanDeviation is used only by CCI.
attached is a cci.py that does not use MeanDeviation but implements the required logic directly. Another approach would be fixing MeanDeviation in deviations.py, but It would be less efficient.

Does anybody know how to feed the change into github and backtrader?

Thanks
Avy

#!/usr/bin/env python
# -*- coding: utf-8; py-indent-offset:4 -*-
###############################################################################
#
# Copyright (C) 2015-2020 Daniel Rodriguez
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.
#
# Implementation (of required average absolute deviation, or mean absolute deviation (MAD)) 
# corrected on 2021-01-19 By Avy Strominger
#
###############################################################################
from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import backtrader
from backtrader import Indicator, Max
from backtrader.indicators import    MovAv


class CommodityChannelIndex(Indicator):
    '''
    Introduced by Donald Lambert in 1980 to measure variations of the
    "typical price" (see below) from its mean to identify extremes and
    reversals

    Formula:
      - tp = typical_price = (high + low + close) / 3
      - tpmean = MovingAverage(tp, period)
      - deviation = tp - tpmean
      - meanabsdev = MeanAbsoluteDeviation(tp) (or average absolute deviation)
      - cci = deviation / (meanabsdev * factor)

    See:
      - https://en.wikipedia.org/wiki/Commodity_channel_index
    '''
    alias = ('CCI',)

    lines = ('cci',)

    params = (('period', 20),
              ('factor', 0.015),
              ('movav', MovAv.Simple),
              ('upperband', 100.0),
              ('lowerband', -100.0),)

    def _plotlabel(self):
        plabels = [self.p.period, self.p.factor]
        plabels += [self.p.movav] * self.p.notdefault('movav')
        return plabels

    def _plotinit(self):
        self.plotinfo.plotyhlines = [0.0, self.p.upperband, self.p.lowerband]

    def __init__(self):
        self.tp = (self.data.high + self.data.low + self.data.close) / 3.0
        self.tpmean = self.p.movav(self.tp, period=self.p.period)

    def next(self):
        AvgAbsDev = 0
        for i in range (int(-self.p.period+1), 1):
            AvgAbsDev = AvgAbsDev + abs(self.tp[i] - self.tpmean[0])
        AvgAbsDev = AvgAbsDev / self.p.period
        self.cci[0] = (self.tp[0] - self.tpmean[0]) / (self.p.factor * AvgAbsDev)

        super(CommodityChannelIndex, self).__init__()

Hello,
Sorry for the basic question. I want to remove the volume bars (or to move it to a separate chart). Saw that PlotScheme()
is supposed to do the work (has volpushup option that has to made False). However, I couldn't find how to use it in conjunction with cerebro.plot().
Any help will be appreciated.
Thanks
Avy

Thanks. Forgot to mention - I'm using PyCharm.
The funny thing it that the code breaks only when there is no single completed transaction (i.e. no self.buy() and self.sell() in the strategy). Adding even a single transaction that is getting executed 'cures' the problem. This is a 'poor man's workaround' I'm now using....
Avy

Hello,
I'm trying just to plot the candles, and get bombed by a "ValueError: Maximum allowed size exceeded" out of cerebro.plot().
same code with strategy that actually byes and sells plots just fine!

my code:

from datetime import datetime
import backtrader as bt

class testStrategy(bt.Strategy):

    def log(self, txt, dt=None):
        ''' Logging function for this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close

    def next(self):
        # Simply log the closing price of the series from the reference
        self.log('Close, %.2f' % self.dataclose[0])


cerebro = bt.Cerebro()  # create a "Cerebro" engine instance

# Create a data feed
data = bt.feeds.YahooFinanceData(dataname='MSFT',
                                 fromdate=datetime(2011, 1, 1),
                                 todate=datetime(2011, 1, 31))

cerebro.adddata(data)  # Add the data feed

cerebro.addstrategy(testStrategy)  # Add the trading strategy
cerebro.run()  # run it all
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.plot(style='candlestick', barup='green', bardown='red')  # and plot it with a single command

Any help/idea what I'm doing wring?
Thanks
Avy