qis.generate_strategy_benchmark_factsheet_plt

qis.generate_strategy_benchmark_factsheet_plt(multi_portfolio_data, strategy_idx=0, benchmark_idx=1, time_period=None, perf_params=PerfParams(freq='W-WED', freq_vol='W-WED', freq_skewness='ME', freq_drawdown='D', freq_reg='W-WED', freq_excess_return='W-WED', return_type=<ReturnTypes.LOG: 'Log'>, sharpe_convention=<SharpeConvention.PA: 1>, rates_data=None), regime_classifier=<qis.perfstats.regime_classifier.BenchmarkReturnsQuantilesRegime object>, backtest_name=None, add_benchmarks_to_navs=False, add_brinson_attribution=True, add_exposures_pnl_attribution=False, add_strategy_factsheet=False, add_grouped_exposures=False, add_grouped_cum_pnl=False, add_tracking_error_table=False, add_exposures_comp=False, is_grouped=True, figsize=(8.3, 11.7), fontsize=5, heatmap_fontsize=4, add_joint_instrument_history_report=False, **kwargs)[source]

factsheet comparing one strategy against one benchmark, as a list of A4 figures.

The two-portfolio case, where the difference between them is the subject: the first page is the strategy on its own and the second is the comparison, with Brinson attribution decomposing the active return into allocation, selection and interaction. That decomposition is why this is a separate report from generate_multi_portfolio_factsheet(), which compares strategies that share no common weights.

Parameters:

  • multi_portfolio_data (MultiPortfolioData) – the portfolios, strategy and benchmark among them

  • strategy_idx (int) – position of the strategy within multi_portfolio_data

  • benchmark_idx (int) – position of the benchmark within multi_portfolio_data

  • time_period (TimePeriod) – reporting window. None uses the full common history

  • perf_params (PerfParams) – annualisation, frequency and rate conventions for the statistics

  • regime_classifier (BenchmarkReturnsQuantilesRegime) – how benchmark returns are mapped to regimes

  • backtest_name (str) – title of the report

  • add_benchmarks_to_navs (bool) – include the benchmarks as additional lines in the performance panels

  • add_brinson_attribution (bool) – add the allocation / selection / interaction decomposition

  • add_exposures_pnl_attribution (bool) – add the exposure and P&L attribution pages

  • add_strategy_factsheet (bool) – append the full single-strategy factsheet

  • add_grouped_exposures (bool) – report exposures by group in that appended factsheet

  • add_grouped_cum_pnl (bool) – report cumulative P&L by group in that appended factsheet

  • add_tracking_error_table (bool) – add the tracking-error table

  • add_exposures_comp (bool) – add the strategy-versus-benchmark exposure comparison

  • is_grouped (bool | None) – report annual returns by asset class rather than by instrument. None decides by the universe size, grouping once there are more than ten instruments

  • figsize (Tuple[float, float]) – page size in inches; the default is A4 portrait

  • fontsize (int) – base font size

  • heatmap_fontsize (int) – font size inside the heatmap panels, smaller because the cells are dense

  • add_joint_instrument_history_report (bool) – add the per-instrument history page

Returns:

the pages, in order, ready for save_figs_to_pdf()

Return type:

List[Figure]