Module backtrader.analyzers.leverage
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
class GrossLeverage(bt.Analyzer):
'''This analyzer calculates the Gross Leverage of the current strategy
on a timeframe basis
Params:
- ``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
Methods:
- get_analysis
Returns a dictionary with returns as values and the datetime points for
each return as keys
'''
params = (
('fund', None),
)
def start(self):
if self.p.fund is None:
self._fundmode = self.strategy.broker.fundmode
else:
self._fundmode = self.p.fund
def notify_fund(self, cash, value, fundvalue, shares):
self._cash = cash
if not self._fundmode:
self._value = value
else:
self._value = fundvalue
def next(self):
# Updates the leverage for "dtkey" (see base class) for each cycle
# 0.0 if 100% in cash, 1.0 if no short selling and fully invested
lev = (self._value - self._cash) / self._value
self.rets[self.data0.datetime.datetime()] = lev
Classes
class GrossLeverage (*args, **kwargs)
-
This analyzer calculates the Gross Leverage of the current strategy on a timeframe basis
Params
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. Seeset_fundmode
in the broker documentationSet it to
True
orFalse
for a specific behaviorMethods
- get_analysis
Returns a dictionary with returns as values and the datetime points for each return as keys
Expand source code
class GrossLeverage(bt.Analyzer): '''This analyzer calculates the Gross Leverage of the current strategy on a timeframe basis Params: - ``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 Methods: - get_analysis Returns a dictionary with returns as values and the datetime points for each return as keys ''' params = ( ('fund', None), ) def start(self): if self.p.fund is None: self._fundmode = self.strategy.broker.fundmode else: self._fundmode = self.p.fund def notify_fund(self, cash, value, fundvalue, shares): self._cash = cash if not self._fundmode: self._value = value else: self._value = fundvalue def next(self): # Updates the leverage for "dtkey" (see base class) for each cycle # 0.0 if 100% in cash, 1.0 if no short selling and fully invested lev = (self._value - self._cash) / self._value self.rets[self.data0.datetime.datetime()] = lev
Ancestors
Class variables
var frompackages
var packages
var params
Inherited members