Module backtrader.indicators.zlind

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 backtrader.utils.py3 import MAXINT


from . import MovingAverageBase, MovAv


class ZeroLagIndicator(MovingAverageBase):
    '''By John Ehlers and Ric Way

    The zero-lag indicator (ZLIndicator) is a variation of the EMA
    which modifies the EMA by trying to minimize the error (distance price -
    error correction) and thus reduce the lag

    Formula:
      - EMA(data, period)

      - For each iteration calculate a best-error-correction of the ema (see
        the paper and/or the code) iterating over ``-bestgain`` ->
        ``+bestgain`` for the error correction factor (both incl.)

      - The default moving average is EMA, but can be changed with the
        parameter ``_movav``

        .. note:: the passed moving average must calculate alpha (and 1 -
                  alpha) and make them available as attributes ``alpha`` and
                  ``alpha1`` in the instance

    See also:
      - http://www.mesasoftware.com/papers/ZeroLag.pdf

    '''
    alias = ('ZLIndicator', 'ZLInd', 'EC', 'ErrorCorrecting',)
    lines = ('ec',)
    params = (
        ('gainlimit', 50),
        ('_movav', MovAv.EMA),
    )

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

    def __init__(self):
        self.ema = MovAv.EMA(period=self.p.period)
        self.limits = [-self.p.gainlimit, self.p.gainlimit + 1]

        # To make mixins work - super at the end for cooperative inheritance
        super(ZeroLagIndicator, self).__init__()

    def next(self):
        leasterror = MAXINT  # 1000000 in original code
        bestec = ema = self.ema[0]  # seed value 1st time for ec
        price = self.data[0]
        ec1 = self.lines.ec[-1]
        alpha, alpha1 = self.ema.alpha, self.ema.alpha1

        for value1 in range(*self.limits):
            gain = value1 / 10
            ec = alpha * (ema + gain * (price - ec1)) + alpha1 * ec1
            error = abs(price - ec)
            if error < leasterror:
                leasterror = error
                bestec = ec

        self.lines.ec[0] = bestec

Classes

class EC

By John Ehlers and Ric Way

The zero-lag indicator (ZLIndicator) is a variation of the EMA which modifies the EMA by trying to minimize the error (distance price - error correction) and thus reduce the lag

Formula

  • EMA(data, period)

  • For each iteration calculate a best-error-correction of the ema (see the paper and/or the code) iterating over -bestgain -> +bestgain for the error correction factor (both incl.)

  • The default moving average is EMA, but can be changed with the parameter _movav

!!! note "Note: the passed moving average must calculate alpha (and 1 -" alpha) and make them available as attributes alpha and alpha1 in the instance

See also: - http://www.mesasoftware.com/papers/ZeroLag.pdf

Ancestors

Class variables

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

Inherited members

class ErrorCorrecting

By John Ehlers and Ric Way

The zero-lag indicator (ZLIndicator) is a variation of the EMA which modifies the EMA by trying to minimize the error (distance price - error correction) and thus reduce the lag

Formula

  • EMA(data, period)

  • For each iteration calculate a best-error-correction of the ema (see the paper and/or the code) iterating over -bestgain -> +bestgain for the error correction factor (both incl.)

  • The default moving average is EMA, but can be changed with the parameter _movav

!!! note "Note: the passed moving average must calculate alpha (and 1 -" alpha) and make them available as attributes alpha and alpha1 in the instance

See also: - http://www.mesasoftware.com/papers/ZeroLag.pdf

Ancestors

Class variables

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

Inherited members

class ZLInd

By John Ehlers and Ric Way

The zero-lag indicator (ZLIndicator) is a variation of the EMA which modifies the EMA by trying to minimize the error (distance price - error correction) and thus reduce the lag

Formula

  • EMA(data, period)

  • For each iteration calculate a best-error-correction of the ema (see the paper and/or the code) iterating over -bestgain -> +bestgain for the error correction factor (both incl.)

  • The default moving average is EMA, but can be changed with the parameter _movav

!!! note "Note: the passed moving average must calculate alpha (and 1 -" alpha) and make them available as attributes alpha and alpha1 in the instance

See also: - http://www.mesasoftware.com/papers/ZeroLag.pdf

Ancestors

Class variables

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

Inherited members

class ZLIndicator

By John Ehlers and Ric Way

The zero-lag indicator (ZLIndicator) is a variation of the EMA which modifies the EMA by trying to minimize the error (distance price - error correction) and thus reduce the lag

Formula

  • EMA(data, period)

  • For each iteration calculate a best-error-correction of the ema (see the paper and/or the code) iterating over -bestgain -> +bestgain for the error correction factor (both incl.)

  • The default moving average is EMA, but can be changed with the parameter _movav

!!! note "Note: the passed moving average must calculate alpha (and 1 -" alpha) and make them available as attributes alpha and alpha1 in the instance

See also: - http://www.mesasoftware.com/papers/ZeroLag.pdf

Ancestors

Class variables

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

Inherited members

class ZeroLagIndicator

By John Ehlers and Ric Way

The zero-lag indicator (ZLIndicator) is a variation of the EMA which modifies the EMA by trying to minimize the error (distance price - error correction) and thus reduce the lag

Formula

  • EMA(data, period)

  • For each iteration calculate a best-error-correction of the ema (see the paper and/or the code) iterating over -bestgain -> +bestgain for the error correction factor (both incl.)

  • The default moving average is EMA, but can be changed with the parameter _movav

!!! note "Note: the passed moving average must calculate alpha (and 1 -" alpha) and make them available as attributes alpha and alpha1 in the instance

See also: - http://www.mesasoftware.com/papers/ZeroLag.pdf

Expand source code 
class ZeroLagIndicator(MovingAverageBase):
    '''By John Ehlers and Ric Way

    The zero-lag indicator (ZLIndicator) is a variation of the EMA
    which modifies the EMA by trying to minimize the error (distance price -
    error correction) and thus reduce the lag

    Formula:
      - EMA(data, period)

      - For each iteration calculate a best-error-correction of the ema (see
        the paper and/or the code) iterating over ``-bestgain`` ->
        ``+bestgain`` for the error correction factor (both incl.)

      - The default moving average is EMA, but can be changed with the
        parameter ``_movav``

        .. note:: the passed moving average must calculate alpha (and 1 -
                  alpha) and make them available as attributes ``alpha`` and
                  ``alpha1`` in the instance

    See also:
      - http://www.mesasoftware.com/papers/ZeroLag.pdf

    '''
    alias = ('ZLIndicator', 'ZLInd', 'EC', 'ErrorCorrecting',)
    lines = ('ec',)
    params = (
        ('gainlimit', 50),
        ('_movav', MovAv.EMA),
    )

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

    def __init__(self):
        self.ema = MovAv.EMA(period=self.p.period)
        self.limits = [-self.p.gainlimit, self.p.gainlimit + 1]

        # To make mixins work - super at the end for cooperative inheritance
        super(ZeroLagIndicator, self).__init__()

    def next(self):
        leasterror = MAXINT  # 1000000 in original code
        bestec = ema = self.ema[0]  # seed value 1st time for ec
        price = self.data[0]
        ec1 = self.lines.ec[-1]
        alpha, alpha1 = self.ema.alpha, self.ema.alpha1

        for value1 in range(*self.limits):
            gain = value1 / 10
            ec = alpha * (ema + gain * (price - ec1)) + alpha1 * ec1
            error = abs(price - ec)
            if error < leasterror:
                leasterror = error
                bestec = ec

        self.lines.ec[0] = bestec

Ancestors

Subclasses

Class variables

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

Inherited members