InitialRiskStatsFactory¶
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class
qf_lib.backtesting.fast_alpha_model_tester.initial_risk_stats.
InitialRiskStatsFactory
(max_accepted_dd: float, target_return: float)[source]¶ Bases:
object
Methods
make_stats
(initial_risks, scenarios_list)Creates a pandas.DataFrame showing how many strategies failed (reached certain draw down level) and how many of them succeeded (that is: reached the target return and not failed on the way).
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make_stats
(initial_risks: Sequence[float], scenarios_list: Sequence[qf_lib.containers.dataframe.qf_dataframe.QFDataFrame]) → qf_lib.containers.dataframe.qf_dataframe.QFDataFrame[source]¶ Creates a pandas.DataFrame showing how many strategies failed (reached certain draw down level) and how many of them succeeded (that is: reached the target return and not failed on the way).
- Parameters
initial_risks (Sequence[float]) – list of initial_risk parameters where initial_risk is a float number
scenarios_list (Sequence[pandas.DataFrame]) – list with scenarios (QFDataFrame) where each DataFrame corresponds to one initial_risk value Each DataFrame has columns corresponding to different scenarios and its indexed by Trades’ ordinal number. Its values are returns of Trades.
- Returns
DataFrame indexed with initial_risk values and with columns FAILED (fraction of scenarios that failed) and SUCCEEDED (fraction of scenarios that met the objective and didn’t fail on the way)
- Return type
pandas.DataFrame
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