Module backtrader.indicators.wma

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)

from ..utils.py3 import range

from . import MovingAverageBase, AverageWeighted


class WeightedMovingAverage(MovingAverageBase):
    '''
    A Moving Average which gives an arithmetic weighting to values with the
    newest having the more weight

    Formula:
      - weights = range(1, period + 1)
      - coef = 2 / (period * (period + 1))
      - movav = coef * Sum(weight[i] * data[period - i] for i in range(period))

    See also:
      - http://en.wikipedia.org/wiki/Moving_average#Weighted_moving_average
    '''
    alias = ('WMA', 'MovingAverageWeighted',)
    lines = ('wma',)

    def __init__(self):
        coef = 2.0 / (self.p.period * (self.p.period + 1.0))
        weights = tuple(float(x) for x in range(1, self.p.period + 1))

        # Before super to ensure mixins (right-hand side in subclassing)
        # can see the assignment operation and operate on the line
        self.lines[0] = AverageWeighted(
            self.data, period=self.p.period,
            coef=coef, weights=weights)

        super(WeightedMovingAverage, self).__init__()

Classes

class MovingAverageWeighted

A Moving Average which gives an arithmetic weighting to values with the newest having the more weight

Formula

  • weights = range(1, period + 1)
  • coef = 2 / (period * (period + 1))
  • movav = coef * Sum(weight[i] * data[period - i] for i in range(period))

See also: - http://en.wikipedia.org/wiki/Moving_average#Weighted_moving_average

Ancestors

Class variables

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

Inherited members

class WMA

A Moving Average which gives an arithmetic weighting to values with the newest having the more weight

Formula

  • weights = range(1, period + 1)
  • coef = 2 / (period * (period + 1))
  • movav = coef * Sum(weight[i] * data[period - i] for i in range(period))

See also: - http://en.wikipedia.org/wiki/Moving_average#Weighted_moving_average

Ancestors

Class variables

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

Inherited members

class WeightedMovingAverage

A Moving Average which gives an arithmetic weighting to values with the newest having the more weight

Formula

  • weights = range(1, period + 1)
  • coef = 2 / (period * (period + 1))
  • movav = coef * Sum(weight[i] * data[period - i] for i in range(period))

See also: - http://en.wikipedia.org/wiki/Moving_average#Weighted_moving_average

Expand source code 
class WeightedMovingAverage(MovingAverageBase):
    '''
    A Moving Average which gives an arithmetic weighting to values with the
    newest having the more weight

    Formula:
      - weights = range(1, period + 1)
      - coef = 2 / (period * (period + 1))
      - movav = coef * Sum(weight[i] * data[period - i] for i in range(period))

    See also:
      - http://en.wikipedia.org/wiki/Moving_average#Weighted_moving_average
    '''
    alias = ('WMA', 'MovingAverageWeighted',)
    lines = ('wma',)

    def __init__(self):
        coef = 2.0 / (self.p.period * (self.p.period + 1.0))
        weights = tuple(float(x) for x in range(1, self.p.period + 1))

        # Before super to ensure mixins (right-hand side in subclassing)
        # can see the assignment operation and operate on the line
        self.lines[0] = AverageWeighted(
            self.data, period=self.p.period,
            coef=coef, weights=weights)

        super(WeightedMovingAverage, self).__init__()

Ancestors

Subclasses

Class variables

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

Inherited members