Module backtrader.observers.logreturns

Expand source code 
#!/usr/bin/env python
# -*- coding: utf-8; py-indent-offset:4 -*-
###############################################################################
#
# Copyright (C) 2015-2023 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/>.
#
###############################################################################
from __future__ import (absolute_import, division, print_function,
                        unicode_literals)


import backtrader as bt


__all__ = ['LogReturns', 'LogReturns2']


class LogReturns(bt.Observer):
    '''This observer stores the *log returns* of the strategy or a

    Params:

      - ``timeframe`` (default: ``None``)
        If ``None`` then the complete return over the entire backtested period
        will be reported

        Pass ``TimeFrame.NoTimeFrame`` to consider the entire dataset with no
        time constraints

      - ``compression`` (default: ``None``)

        Only used for sub-day timeframes to for example work on an hourly
        timeframe by specifying "TimeFrame.Minutes" and 60 as compression

      - ``fund`` (default: ``None``)

        If ``None`` the actual mode of the broker (fundmode - True/False) will
        be autodetected to decide if the returns are based on the total net
        asset value or on the fund value. See ``set_fundmode`` in the broker
        documentation

        Set it to ``True`` or ``False`` for a specific behavior

    Remember that at any moment of a ``run`` the current values can be checked
    by looking at the *lines* by name at index ``0``.

    '''
    _stclock = True

    lines = ('logret1',)
    plotinfo = dict(plot=True, subplot=True)

    params = (
        ('timeframe', None),
        ('compression', None),
        ('fund', None),
    )

    def _plotlabel(self):
        return [bt.TimeFrame.getname(self.p.timeframe, self.p.compression),
                str(self.p.compression or 1)]

    def __init__(self):
        self.logret1 = self._owner._addanalyzer_slave(
            bt.analyzers.LogReturnsRolling,
            data=self.data0, **self.p._getkwargs())

    def next(self):
        self.lines.logret1[0] = self.logret1.rets[self.logret1.dtkey]


class LogReturns2(LogReturns):
    '''Extends the observer LogReturns to show two instruments'''
    lines = ('logret2',)

    def __init__(self):
        super(LogReturns2, self).__init__()

        self.logret2 = self._owner._addanalyzer_slave(
            bt.analyzers.LogReturnsRolling,
            data=self.data1, **self.p._getkwargs())

    def next(self):
        super(LogReturns2, self).next()
        self.lines.logret2[0] = self.logret2.rets[self.logret2.dtkey]

Classes

class LogReturns

This observer stores the log returns of the strategy or a

Params

  • timeframe (default: None) If None then the complete return over the entire backtested period will be reported

Pass TimeFrame.NoTimeFrame to consider the entire dataset with no time constraints

  • compression (default: None)

Only used for sub-day timeframes to for example work on an hourly timeframe by specifying "TimeFrame.Minutes" and 60 as compression

  • fund (default: None)

If None the actual mode of the broker (fundmode - True/False) will be autodetected to decide if the returns are based on the total net asset value or on the fund value. See set_fundmode in the broker documentation

Set it to True or False for a specific behavior

Remember that at any moment of a run the current values can be checked by looking at the lines by name at index 0.

Expand source code 
class LogReturns(bt.Observer):
    '''This observer stores the *log returns* of the strategy or a

    Params:

      - ``timeframe`` (default: ``None``)
        If ``None`` then the complete return over the entire backtested period
        will be reported

        Pass ``TimeFrame.NoTimeFrame`` to consider the entire dataset with no
        time constraints

      - ``compression`` (default: ``None``)

        Only used for sub-day timeframes to for example work on an hourly
        timeframe by specifying "TimeFrame.Minutes" and 60 as compression

      - ``fund`` (default: ``None``)

        If ``None`` the actual mode of the broker (fundmode - True/False) will
        be autodetected to decide if the returns are based on the total net
        asset value or on the fund value. See ``set_fundmode`` in the broker
        documentation

        Set it to ``True`` or ``False`` for a specific behavior

    Remember that at any moment of a ``run`` the current values can be checked
    by looking at the *lines* by name at index ``0``.

    '''
    _stclock = True

    lines = ('logret1',)
    plotinfo = dict(plot=True, subplot=True)

    params = (
        ('timeframe', None),
        ('compression', None),
        ('fund', None),
    )

    def _plotlabel(self):
        return [bt.TimeFrame.getname(self.p.timeframe, self.p.compression),
                str(self.p.compression or 1)]

    def __init__(self):
        self.logret1 = self._owner._addanalyzer_slave(
            bt.analyzers.LogReturnsRolling,
            data=self.data0, **self.p._getkwargs())

    def next(self):
        self.lines.logret1[0] = self.logret1.rets[self.logret1.dtkey]

Ancestors

Subclasses

Class variables

var alias
var aliased
var frompackages
var linealias
var packages
var params
var plotinfo
var plotlines

Inherited members

class LogReturns2

Extends the observer LogReturns to show two instruments

Expand source code 
class LogReturns2(LogReturns):
    '''Extends the observer LogReturns to show two instruments'''
    lines = ('logret2',)

    def __init__(self):
        super(LogReturns2, self).__init__()

        self.logret2 = self._owner._addanalyzer_slave(
            bt.analyzers.LogReturnsRolling,
            data=self.data1, **self.p._getkwargs())

    def next(self):
        super(LogReturns2, self).next()
        self.lines.logret2[0] = self.logret2.rets[self.logret2.dtkey]

Ancestors

Class variables

var alias
var aliased
var frompackages
var linealias
var packages
var params
var plotinfo
var plotlines

Inherited members