# 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.
from datetime import datetime
import matplotlib as plt
from qf_lib.common.utils.error_handling import ErrorHandling
from qf_lib.analysis.tearsheets.abstract_tearsheet import AbstractTearsheet
from qf_lib.containers.series.qf_series import QFSeries
from qf_lib.documents_utils.document_exporting.element.chart import ChartElement
from qf_lib.documents_utils.document_exporting.element.paragraph import ParagraphElement
from qf_lib.plotting.charts.cone_chart_oos import ConeChartOOS
from qf_lib.plotting.decorators.axes_position_decorator import AxesPositionDecorator
from qf_lib.settings import Settings
[docs]@ErrorHandling.class_error_logging()
class StrategyMonitoringDocument(AbstractTearsheet):
"""Creates PDF with strategy monitoring analysis.
Parameters
----------
settings: Settings
settings of the project
pdf_exporter: PDFExporter
tool that creates the pdf with the result
strategy_series: QFSeries
timeseries of the trading of the strategy
live_date: datetime
if set it is used to generate the cone chart
title: str
title of the document
"""
def __init__(self, settings: Settings, pdf_exporter, strategy_series: QFSeries, benchmark_series: QFSeries,
live_date: datetime = None, title: str = "Strategy Analysis"):
super().__init__(settings, pdf_exporter, strategy_series, live_date, title)
self.is_mean_return = None
self.is_sigma = None
self.excess_is_mean_return = None
self.excess_is_sigma = None
self.benchmark_series = benchmark_series
def build_document(self):
self._add_header()
self.document.add_element(ParagraphElement("\n\n"))
series_list = [self.strategy_series, self.benchmark_series]
self._add_perf_chart(series_list)
self.document.add_element(ParagraphElement("\n\n"))
self._add_relative_performance_chart(self.strategy_series, self.benchmark_series)
self.document.add_element(ParagraphElement("\n\n"))
self._add_excess_cone_chart()
self.document.add_element(ParagraphElement("\n\n"))
self._add_rolling_return_chart(series_list)
self.document.add_element(ParagraphElement("\n\n"))
self._add_rolling_vol_chart(series_list)
def set_in_sample_statistics(self, is_mean_return, is_sigma):
self.is_mean_return = is_mean_return
self.is_sigma = is_sigma
def set_in_sample_excess_statistics(self, excess_is_mean_return, excess_is_sigma):
self.excess_is_mean_return = excess_is_mean_return
self.excess_is_sigma = excess_is_sigma
def _add_excess_cone_chart(self):
diff = self.strategy_series.to_simple_returns().subtract(self.benchmark_series.to_simple_returns(),
fill_value=0)
diff = diff.iloc[-200:]
diff = diff.to_prices(1)
cone_chart = ConeChartOOS(diff,
is_mean_return=self.excess_is_mean_return,
is_sigma=self.excess_is_sigma,
title="Excess returns")
position_decorator = AxesPositionDecorator(*self.full_image_axis_position)
cone_chart.add_decorator(position_decorator)
chart_element = ChartElement(cone_chart, self.full_image_size, self.dpi, False)
self.document.add_element(chart_element)
def save(self, report_dir: str = "", file_name=None):
# Set the style for the report
plt.style.use(['tearsheet'])
filename = "%Y_%m_%d-%H%M {}.pdf".format(self.title)
filename = datetime.now().strftime(filename)
return self.pdf_exporter.generate([self.document], report_dir, filename)