# 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
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import pandas as pd
from matplotlib.dates import DateFormatter
from qf_lib.common.utils.dateutils.date_format import DateFormat
from qf_lib.common.utils.factorization.data_models.rolling_data_model import RollingDataModel
from qf_lib.plotting.charts.line_chart import LineChart
from qf_lib.plotting.decorators.axes_formatter_decorator import AxesFormatterDecorator
from qf_lib.plotting.decorators.data_element_decorator import DataElementDecorator
from qf_lib.plotting.decorators.legend_decorator import LegendDecorator
from qf_lib.plotting.decorators.title_decorator import TitleDecorator
[docs]class RollingDataPresenter:
"""
Class used for presenting the data stored in the RollingFactorizationDataModel.
"""
def __init__(self, rolling_model: RollingDataModel):
self.rolling_model = rolling_model
def general_info(self) -> str:
return 'Values are calculated based on {window_size:d} data samples rolling \n' \
'with {num_of_samples:d} sample(s) shift. \n' \
'Frequency of the data points is {frequency:s}. \n'.format(
window_size=self.rolling_model.window_size_,
num_of_samples=self.rolling_model.step_,
frequency=str(self.rolling_model.input_data.frequency)
)
def regression_coefficients_chart(self) -> LineChart:
rolling_coeffs = self.rolling_model.coefficients_df
line_chart = self._create_line_chart(rolling_values=rolling_coeffs, title='Rolling regression coefficients')
return line_chart
def t_statistics_chart(self) -> LineChart:
rolling_t_stats = self.rolling_model.t_stats_df
line_chart = self._create_line_chart(rolling_values=rolling_t_stats, title='Rolling t-statistics')
return line_chart
def p_values_chart(self) -> LineChart:
rolling_p_values = self.rolling_model.p_values_df
line_chart = self._create_line_chart(rolling_values=rolling_p_values, title='Rolling p-Value')
return line_chart
def r_squared_chart(self) -> LineChart:
rolling_r_squared = self.rolling_model.r_squared_tms
rolling_r_squared = rolling_r_squared.to_frame(name='R Squared Adjusted')
line_chart = self._create_line_chart(rolling_values=rolling_r_squared, title='R Squared')
return line_chart
def correlations_chart(self) -> LineChart:
# select correlations of different series with analysed timeseries
rolling_correlations = self.rolling_model.correlations_df
line_chart = self._create_line_chart(rolling_values=rolling_correlations, title='Correlation')
return line_chart
def risk_contribution_chart(self) -> LineChart:
rolling_risk_contribs = self.rolling_model.risk_contribs_df
line_chart = self._create_line_chart(rolling_values=rolling_risk_contribs, title='Risk Contribution')
return line_chart
def performance_attribution_chart(self) -> LineChart:
rolling_factors_performance_attributions = self.rolling_model.factors_performance_attributions_df
rolling_unexplained_perf_attribs = self.rolling_model.unexplained_performance_attributions_tms
rolling_unexplained_perf_attribs.name = 'Unexplained/Alpha'
rolling_perf_attribs = pd.concat([rolling_factors_performance_attributions, rolling_unexplained_perf_attribs],
axis=1)
line_chart = self._create_line_chart(rolling_values=rolling_perf_attribs, title='Performance Attribution')
return line_chart
def _create_line_chart(self, rolling_values, title):
line_chart = LineChart()
legend = LegendDecorator()
for column_name, values_tms in rolling_values.items():
coeff_tms_data_elem = DataElementDecorator(values_tms)
line_chart.add_decorator(coeff_tms_data_elem)
legend.add_entry(coeff_tms_data_elem, column_name)
full_title_str = "".join([title, ' {:d} samples rolling'.format(self.rolling_model.window_size_)])
line_chart.add_decorator(TitleDecorator(full_title_str))
line_chart.add_decorator(AxesFormatterDecorator(x_major=DateFormatter(fmt=str(DateFormat.YEAR_DOT_MONTH))))
line_chart.add_decorator(legend)
return line_chart