# 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
from qf_lib.analysis.rolling_analysis.rolling_analysis import RollingAnalysisFactory
from qf_lib.analysis.tearsheets.abstract_tearsheet import AbstractTearsheet
from qf_lib.common.enums.grid_proportion import GridProportion
from qf_lib.common.enums.plotting_mode import PlottingMode
from qf_lib.containers.series.qf_series import QFSeries
from qf_lib.documents_utils.document_exporting.element.grid import GridElement
from qf_lib.documents_utils.document_exporting.element.new_page import NewPageElement
from qf_lib.documents_utils.document_exporting.element.paragraph import ParagraphElement
from qf_lib.documents_utils.document_exporting.element.table import Table
from qf_lib.plotting.charts.regression_chart import RegressionChart
from qf_lib.plotting.charts.returns_heatmap_chart import ReturnsHeatmapChart
from qf_lib.plotting.helpers.create_returns_bar_chart import create_returns_bar_chart
from qf_lib.plotting.helpers.create_returns_distribution import create_returns_distribution
from qf_lib.settings import Settings
[docs]class TearsheetComparative(AbstractTearsheet):
"""Creates a PDF report, which additionally contains a benchamrk.
Can be used with or without the benchmark
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
benchmark_series: QFSeries
timeseries of the benchmark
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.benchmark_series = benchmark_series
def build_document(self):
series_list = [self.strategy_series, self.benchmark_series]
# First Page
self._add_header()
self._add_perf_chart(series_list)
self._add_relative_performance_chart(self.strategy_series, self.benchmark_series)
self._add_statistics_table(series_list)
# Next Page
self.document.add_element(NewPageElement())
self._add_header()
self.document.add_element(ParagraphElement("\n"))
self._add_returns_statistics_charts(self.strategy_series)
self._add_returns_statistics_charts(self.benchmark_series)
self.document.add_element(ParagraphElement("\n"))
self.document.add_element(ParagraphElement("\n"))
self._add_ret_distribution_and_similarity()
# Next Page
self.document.add_element(NewPageElement())
self._add_header()
self.document.add_element(ParagraphElement("\n"))
self.document.add_element(ParagraphElement("\n"))
self._add_rolling_return_chart(series_list)
self.document.add_element(ParagraphElement("\n"))
self.document.add_element(ParagraphElement("\n"))
self._add_rolling_vol_chart(series_list)
def _add_returns_statistics_charts(self, series):
grid = self._get_new_grid()
# Monthly returns heatmap
heatmap_chart = ReturnsHeatmapChart(series, title="Monthly Returns - {}".format(series.name))
grid.add_chart(heatmap_chart)
# Annual returns bar chart
annual_ret_chart = create_returns_bar_chart(series, title="Annual Returns - {}".format(series.name))
grid.add_chart(annual_ret_chart)
self.document.add_element(grid)
def _add_ret_distribution_and_similarity(self):
grid = GridElement(mode=PlottingMode.PDF,
figsize=self.half_image_size, dpi=self.dpi)
# Distribution of Monthly Returns
chart = create_returns_distribution(self.strategy_series)
grid.add_chart(chart)
# Regression chart
chart = RegressionChart(self.benchmark_series, self.strategy_series)
grid.add_chart(chart)
# Distribution of Monthly Returns
chart = create_returns_distribution(self.benchmark_series)
grid.add_chart(chart)
# Regression chart
chart = RegressionChart(self.strategy_series, self.benchmark_series)
grid.add_chart(chart)
self.document.add_element(grid)
def _add_rolling_table(self):
dtos = RollingAnalysisFactory.calculate_analysis(self.strategy_series, self.benchmark_series)
column_names = [
Table.ColumnCell("Rolling Return Period", css_class="left-align"),
"Strategy Average",
"Strategy Worst",
Table.ColumnCell("Strategy Best", css_class="right-align"),
"Benchmark Average",
"Benchmark Worst",
Table.ColumnCell("Benchmark Best", css_class="right-align"),
Table.ColumnCell("% Strategy outperform Benchmark")]
result = Table(column_names, grid_proportion=GridProportion.Sixteen, css_class="table rolling-table")
for dto in dtos:
result.add_row([Table.Cell(dto.period, css_class="right-align"),
Table.Cell(dto.strategy_average, "{:.2%}"),
Table.Cell(dto.strategy_worst, "{:.2%}"),
Table.Cell(dto.strategy_best, "{:.2%}"),
Table.Cell(dto.benchmark_average, "{:.2%}"),
Table.Cell(dto.benchmark_worst, "{:.2%}"),
Table.Cell(dto.benchmark_best, "{:.2%}"),
Table.Cell(dto.percentage_difference, "{:.2%}")])
self.document.add_element(result)