# Copyright 2016-present CERN – European Organization for Nuclear Research
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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# limitations under the License.
from typing import Union, Sequence
from qf_lib.common.utils.confidence_interval.analytical_cone_base import AnalyticalConeBase
from qf_lib.plotting.charts.chart import Chart
from qf_lib.plotting.decorators.chart_decorator import ChartDecorator
[docs]class ConeProcessDecorator(ChartDecorator):
"""
Puts cone on top of the timeseries starting from given date.
Parameters
----------
mean: float
mean return of the process. expressed in the frequency of samples (not annualised)
std: float
std of returns of the process. expressed in the frequency of samples (not annualised)
steps: int
length of the cone that we are creating
starting_value: float
corresponds to the starting price of the instrument
cone_stds: Sequence[Union[float, int]], float, int
defines the size of the cones in standard deviations
colors_alpha: float
sets the level of transparency of the cone
key: str
see ChartDecorator.key.__init__#key
"""
def __init__(self, mean: float, std: float, steps: int, starting_value=1,
cone_stds: Union[Sequence[Union[float, int]], float, int] = (1, 2),
colors_alpha: float = 0.25, key: str = None):
super().__init__(key)
self._mean = mean
self._std = std
self._steps = steps
self._starting_value = starting_value
if isinstance(cone_stds, (float, int)):
cone_stds = [cone_stds]
assert cone_stds, "cone_stds can't be empty"
self._cone_stds = cone_stds
self._colors_alpha = colors_alpha
[docs] def decorate(self, chart) -> None:
cone = AnalyticalConeBase()
ax = chart.axes
colors = Chart.get_axes_colors()
for cone_std in self._cone_stds:
if cone_std == 0:
# special case for mean return line (which is not a cone, but a line) == 0
mean_tms = cone.calculate_simple_cone_for_process(self._mean, self._std, 0, self._steps,
self._starting_value)
ax.plot(mean_tms, color=colors[1])
else:
upper_bound_tms = cone.calculate_simple_cone_for_process(
self._mean, self._std, cone_std, self._steps, self._starting_value)
lower_bound_tms = cone.calculate_simple_cone_for_process(
self._mean, self._std, -cone_std, self._steps, self._starting_value)
ax.fill_between(upper_bound_tms.index, upper_bound_tms, lower_bound_tms, alpha=self._colors_alpha)