Module backtrader.indicators.lrsi

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 . import PeriodN


__all__ = ['LaguerreRSI', 'LRSI', 'LaguerreFilter', 'LAGF']


class LaguerreRSI(PeriodN):
    '''
    Defined by John F. Ehlers in `Cybernetic Analysis for Stock and Futures`,
    2004, published by Wiley. `ISBN: 978-0-471-46307-8`

    The Laguerre RSI tries to implements a better RSI by providing a sort of
    *Time Warp without Time Travel* using a Laguerre filter. This provides for
    faster reactions to price changes

    ``gamma`` is meant to have values between ``0.2`` and ``0.8``, with the
    best balance found theoretically at the default of ``0.5``
    '''
    alias = ('LRSI',)
    lines = ('lrsi',)
    params = (
        ('gamma', 0.5),
        ('period', 6),
    )

    plotinfo = dict(
        plotymargin=0.15,
        plotyticks=[0.0, 0.2, 0.5, 0.8, 1.0]
    )

    l0, l1, l2, l3 = 0.0, 0.0, 0.0, 0.0

    def next(self):
        l0_1 = self.l0  # cache previous intermediate values
        l1_1 = self.l1
        l2_1 = self.l2

        g = self.p.gamma  # avoid more lookups
        self.l0 = l0 = (1.0 - g) * self.data + g * l0_1
        self.l1 = l1 = -g * l0 + l0_1 + g * l1_1
        self.l2 = l2 = -g * l1 + l1_1 + g * l2_1
        self.l3 = l3 = -g * l2 + l2_1 + g * self.l3

        cu = 0.0
        cd = 0.0
        if l0 >= l1:
            cu = l0 - l1
        else:
            cd = l1 - l0

        if l1 >= l2:
            cu += l1 - l2
        else:
            cd += l2 - l1

        if l2 >= l3:
            cu += l2 - l3
        else:
            cd += l3 - l2

        den = cu + cd
        self.lines.lrsi[0] = 1.0 if not den else cu / den


class LaguerreFilter(PeriodN):
    '''
    Defined by John F. Ehlers in `Cybernetic Analysis for Stock and Futures`,
    2004, published by Wiley. `ISBN: 978-0-471-46307-8`

    ``gamma`` is meant to have values between ``0.2`` and ``0.8``, with the
    best balance found theoretically at the default of ``0.5``
    '''
    alias = ('LAGF',)
    lines = ('lfilter',)
    params = (('gamma', 0.5),)
    plotinfo = dict(subplot=False)

    l0, l1, l2, l3 = 0.0, 0.0, 0.0, 0.0

    def next(self):
        l0_1 = self.l0  # cache previous intermediate values
        l1_1 = self.l1
        l2_1 = self.l2

        g = self.p.gamma  # avoid more lookups
        self.l0 = l0 = (1.0 - g) * self.data + g * l0_1
        self.l1 = l1 = -g * l0 + l0_1 + g * l1_1
        self.l2 = l2 = -g * l1 + l1_1 + g * l2_1
        self.l3 = l3 = -g * l2 + l2_1 + g * self.l3
        self.lines.lfilter[0] = (l0 + (2 * l1) + (2 * l2) + l3) / 6

Classes

class LAGF

Defined by John F. Ehlers in Cybernetic Analysis for Stock and Futures, 2004, published by Wiley. ISBN: 978-0-471-46307-8

gamma is meant to have values between 0.2 and 0.8, with the best balance found theoretically at the default of 0.5

Ancestors

Class variables

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

Inherited members

class LRSI

Defined by John F. Ehlers in Cybernetic Analysis for Stock and Futures, 2004, published by Wiley. ISBN: 978-0-471-46307-8

The Laguerre RSI tries to implements a better RSI by providing a sort of Time Warp without Time Travel using a Laguerre filter. This provides for faster reactions to price changes

gamma is meant to have values between 0.2 and 0.8, with the best balance found theoretically at the default of 0.5

Ancestors

Class variables

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

Inherited members

class LaguerreFilter

Defined by John F. Ehlers in Cybernetic Analysis for Stock and Futures, 2004, published by Wiley. ISBN: 978-0-471-46307-8

gamma is meant to have values between 0.2 and 0.8, with the best balance found theoretically at the default of 0.5

Expand source code 
class LaguerreFilter(PeriodN):
    '''
    Defined by John F. Ehlers in `Cybernetic Analysis for Stock and Futures`,
    2004, published by Wiley. `ISBN: 978-0-471-46307-8`

    ``gamma`` is meant to have values between ``0.2`` and ``0.8``, with the
    best balance found theoretically at the default of ``0.5``
    '''
    alias = ('LAGF',)
    lines = ('lfilter',)
    params = (('gamma', 0.5),)
    plotinfo = dict(subplot=False)

    l0, l1, l2, l3 = 0.0, 0.0, 0.0, 0.0

    def next(self):
        l0_1 = self.l0  # cache previous intermediate values
        l1_1 = self.l1
        l2_1 = self.l2

        g = self.p.gamma  # avoid more lookups
        self.l0 = l0 = (1.0 - g) * self.data + g * l0_1
        self.l1 = l1 = -g * l0 + l0_1 + g * l1_1
        self.l2 = l2 = -g * l1 + l1_1 + g * l2_1
        self.l3 = l3 = -g * l2 + l2_1 + g * self.l3
        self.lines.lfilter[0] = (l0 + (2 * l1) + (2 * l2) + l3) / 6

Ancestors

Subclasses

Class variables

var alias
var aliased
var frompackages
var l0
var l1
var l2
var l3
var linealias
var packages
var params
var plotinfo
var plotlines

Inherited members

class LaguerreRSI

Defined by John F. Ehlers in Cybernetic Analysis for Stock and Futures, 2004, published by Wiley. ISBN: 978-0-471-46307-8

The Laguerre RSI tries to implements a better RSI by providing a sort of Time Warp without Time Travel using a Laguerre filter. This provides for faster reactions to price changes

gamma is meant to have values between 0.2 and 0.8, with the best balance found theoretically at the default of 0.5

Expand source code 
class LaguerreRSI(PeriodN):
    '''
    Defined by John F. Ehlers in `Cybernetic Analysis for Stock and Futures`,
    2004, published by Wiley. `ISBN: 978-0-471-46307-8`

    The Laguerre RSI tries to implements a better RSI by providing a sort of
    *Time Warp without Time Travel* using a Laguerre filter. This provides for
    faster reactions to price changes

    ``gamma`` is meant to have values between ``0.2`` and ``0.8``, with the
    best balance found theoretically at the default of ``0.5``
    '''
    alias = ('LRSI',)
    lines = ('lrsi',)
    params = (
        ('gamma', 0.5),
        ('period', 6),
    )

    plotinfo = dict(
        plotymargin=0.15,
        plotyticks=[0.0, 0.2, 0.5, 0.8, 1.0]
    )

    l0, l1, l2, l3 = 0.0, 0.0, 0.0, 0.0

    def next(self):
        l0_1 = self.l0  # cache previous intermediate values
        l1_1 = self.l1
        l2_1 = self.l2

        g = self.p.gamma  # avoid more lookups
        self.l0 = l0 = (1.0 - g) * self.data + g * l0_1
        self.l1 = l1 = -g * l0 + l0_1 + g * l1_1
        self.l2 = l2 = -g * l1 + l1_1 + g * l2_1
        self.l3 = l3 = -g * l2 + l2_1 + g * self.l3

        cu = 0.0
        cd = 0.0
        if l0 >= l1:
            cu = l0 - l1
        else:
            cd = l1 - l0

        if l1 >= l2:
            cu += l1 - l2
        else:
            cd += l2 - l1

        if l2 >= l3:
            cu += l2 - l3
        else:
            cd += l3 - l2

        den = cu + cd
        self.lines.lrsi[0] = 1.0 if not den else cu / den

Ancestors

Subclasses

Class variables

var alias
var aliased
var frompackages
var l0
var l1
var l2
var l3
var linealias
var packages
var params
var plotinfo
var plotlines

Inherited members