Module backtrader.analyzers.calmar

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
from . import TimeDrawDown


__all__ = ['Calmar']


class Calmar(bt.TimeFrameAnalyzerBase):
    '''This analyzer calculates the CalmarRatio
    timeframe which can be different from the one used in the underlying data
    Params:

      - ``timeframe`` (default: ``None``)
        If ``None`` the ``timeframe`` of the 1st data in the system will be
        used

        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

        If ``None`` then the compression of the 1st data of the system will be
        used
      - *None*

      - ``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

    See also:

      - https://en.wikipedia.org/wiki/Calmar_ratio

    Methods:
      - ``get_analysis``

        Returns a OrderedDict with a key for the time period and the
        corresponding rolling Calmar ratio

    Attributes:
      - ``calmar`` the latest calculated calmar ratio
    '''

    packages = ('collections', 'math',)

    params = (
        ('timeframe', bt.TimeFrame.Months),  # default in calmar
        ('period', 36),
        ('fund', None),
    )

    def __init__(self):
        self._maxdd = TimeDrawDown(timeframe=self.p.timeframe,
                                   compression=self.p.compression)

    def start(self):
        self._mdd = float('-inf')
        self._values = collections.deque([float('Nan')] * self.p.period,
                                         maxlen=self.p.period)
        if self.p.fund is None:
            self._fundmode = self.strategy.broker.fundmode
        else:
            self._fundmode = self.p.fund

        if not self._fundmode:
            self._values.append(self.strategy.broker.getvalue())
        else:
            self._values.append(self.strategy.broker.fundvalue)

    def on_dt_over(self):
        self._mdd = max(self._mdd, self._maxdd.maxdd)
        if not self._fundmode:
            self._values.append(self.strategy.broker.getvalue())
        else:
            self._values.append(self.strategy.broker.fundvalue)
        rann = math.log(self._values[-1] / self._values[0]) / len(self._values)
        self.calmar = calmar = rann / (self._mdd or float('Inf'))

        self.rets[self.dtkey] = calmar

    def stop(self):
        self.on_dt_over()  # update last values

Classes

class Calmar

This analyzer calculates the CalmarRatio timeframe which can be different from the one used in the underlying data

Params

  • timeframe (default: None) If None the timeframe of the 1st data in the system will be used

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

If None then the compression of the 1st data of the system will be used - None

  • 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

See also:

Methods

  • get_analysis

Returns a OrderedDict with a key for the time period and the corresponding rolling Calmar ratio

Attributes

  • calmar the latest calculated calmar ratio
Expand source code 
class Calmar(bt.TimeFrameAnalyzerBase):
    '''This analyzer calculates the CalmarRatio
    timeframe which can be different from the one used in the underlying data
    Params:

      - ``timeframe`` (default: ``None``)
        If ``None`` the ``timeframe`` of the 1st data in the system will be
        used

        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

        If ``None`` then the compression of the 1st data of the system will be
        used
      - *None*

      - ``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

    See also:

      - https://en.wikipedia.org/wiki/Calmar_ratio

    Methods:
      - ``get_analysis``

        Returns a OrderedDict with a key for the time period and the
        corresponding rolling Calmar ratio

    Attributes:
      - ``calmar`` the latest calculated calmar ratio
    '''

    packages = ('collections', 'math',)

    params = (
        ('timeframe', bt.TimeFrame.Months),  # default in calmar
        ('period', 36),
        ('fund', None),
    )

    def __init__(self):
        self._maxdd = TimeDrawDown(timeframe=self.p.timeframe,
                                   compression=self.p.compression)

    def start(self):
        self._mdd = float('-inf')
        self._values = collections.deque([float('Nan')] * self.p.period,
                                         maxlen=self.p.period)
        if self.p.fund is None:
            self._fundmode = self.strategy.broker.fundmode
        else:
            self._fundmode = self.p.fund

        if not self._fundmode:
            self._values.append(self.strategy.broker.getvalue())
        else:
            self._values.append(self.strategy.broker.fundvalue)

    def on_dt_over(self):
        self._mdd = max(self._mdd, self._maxdd.maxdd)
        if not self._fundmode:
            self._values.append(self.strategy.broker.getvalue())
        else:
            self._values.append(self.strategy.broker.fundvalue)
        rann = math.log(self._values[-1] / self._values[0]) / len(self._values)
        self.calmar = calmar = rann / (self._mdd or float('Inf'))

        self.rets[self.dtkey] = calmar

    def stop(self):
        self.on_dt_over()  # update last values

Ancestors

Class variables

var frompackages
var packages
var params

Methods

def on_dt_over(self)
Expand source code 
def on_dt_over(self):
    self._mdd = max(self._mdd, self._maxdd.maxdd)
    if not self._fundmode:
        self._values.append(self.strategy.broker.getvalue())
    else:
        self._values.append(self.strategy.broker.fundvalue)
    rann = math.log(self._values[-1] / self._values[0]) / len(self._values)
    self.calmar = calmar = rann / (self._mdd or float('Inf'))

    self.rets[self.dtkey] = calmar

Inherited members