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synced 2026-07-11 06:46:56 +08:00
fix account bug & update indicator_analysis & fix some comments
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@@ -7,7 +7,7 @@ import warnings
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import pandas as pd
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from pathlib import Path
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from pprint import pprint
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from ..contrib.evaluate import risk_analysis
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from ..contrib.evaluate import indicator_analysis, risk_analysis, indicator_analysis
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from ..data.dataset import DatasetH
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from ..data.dataset.handler import DataHandlerLP
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@@ -294,7 +294,9 @@ class PortAnaRecord(RecordTemp):
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artifact_path = "portfolio_analysis"
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def __init__(self, recorder, config, risk_analysis_freq, **kwargs):
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def __init__(
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self, recorder, config, risk_analysis_freq, indicator_analysis_freq, indicator_analysis_method=None, **kwargs
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):
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"""
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config["strategy"] : dict
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define the strategy class as well as the kwargs.
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@@ -304,6 +306,10 @@ class PortAnaRecord(RecordTemp):
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define the backtest kwargs.
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risk_analysis_freq : str|List[str]
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risk analysis freq of report
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indicator_analysis_freq : str|List[str]
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indicator analysis freq of report
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indicator_analysis_method : str, optional, default by None
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the candidated values include 'mean', 'amount_weighted', 'value_weighted'
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"""
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super().__init__(recorder=recorder, **kwargs)
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@@ -312,10 +318,17 @@ class PortAnaRecord(RecordTemp):
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self.backtest_config = config["backtest"]
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if isinstance(risk_analysis_freq, str):
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risk_analysis_freq = [risk_analysis_freq]
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if isinstance(indicator_analysis_freq, str):
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indicator_analysis_freq = [indicator_analysis_freq]
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self.risk_analysis_freq = [
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"{0}{1}".format(*parse_freq(_analysis_freq)) for _analysis_freq in risk_analysis_freq
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]
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self.report_freq = self._get_report_freq(self.executor_config)
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self.indicator_analysis_freq = [
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"{0}{1}".format(*parse_freq(_analysis_freq)) for _analysis_freq in indicator_analysis_freq
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]
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self.indicator_analysis_method = indicator_analysis_method
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self.all_freq = self._get_report_freq(self.executor_config)
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def _get_report_freq(self, executor_config):
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ret_freq = []
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@@ -328,21 +341,26 @@ class PortAnaRecord(RecordTemp):
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def generate(self, **kwargs):
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# custom strategy and get backtest
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report_dict = normal_backtest(
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report_dict, indicator_dict = normal_backtest(
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executor=self.executor_config, strategy=self.strategy_config, **self.backtest_config
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)
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for report_freq, (report_normal, positions_normal) in report_dict.items():
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for _freq, (report_normal, positions_normal) in report_dict.items():
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self.recorder.save_objects(
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**{f"report_normal_{report_freq}.pkl": report_normal}, artifact_path=PortAnaRecord.get_path()
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**{f"report_normal_{_freq}.pkl": report_normal}, artifact_path=PortAnaRecord.get_path()
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)
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self.recorder.save_objects(
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**{f"positions_normal_{report_freq}.pkl": positions_normal}, artifact_path=PortAnaRecord.get_path()
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**{f"positions_normal_{_freq}.pkl": positions_normal}, artifact_path=PortAnaRecord.get_path()
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)
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for _freq, indicators_normal in indicator_dict.items():
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self.recorder.save_objects(
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**{f"indicators_normal_{_freq}.pkl": indicators_normal}, artifact_path=PortAnaRecord.get_path()
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)
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for _analysis_freq in self.risk_analysis_freq:
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if _analysis_freq not in report_dict:
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warnings.warn(
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f"the freq {_analysis_freq} report is not found, please set the corresponding env with `generate_report==True`"
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f"the freq {_analysis_freq} report is not found, please set the corresponding env with `generate_report=True`"
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)
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else:
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report_normal, _ = report_dict.get(_analysis_freq)
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@@ -353,25 +371,46 @@ class PortAnaRecord(RecordTemp):
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analysis["excess_return_with_cost"] = risk_analysis(
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report_normal["return"] - report_normal["bench"] - report_normal["cost"], freq=_analysis_freq
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)
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analysis_df = pd.concat(analysis) # type: pd.DataFrame
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# log metrics
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self.recorder.log_metrics(**flatten_dict(analysis_df["risk"].unstack().T.to_dict()))
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analysis_dict = flatten_dict(analysis_df["risk"].unstack().T.to_dict())
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self.recorder.log_metrics(**{f"{_analysis_freq}.{k}": v for k, v in analysis_dict.items()})
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# save results
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self.recorder.save_objects(
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**{f"port_analysis_{report_freq}.pkl": analysis_df}, artifact_path=PortAnaRecord.get_path()
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**{f"port_analysis_{_analysis_freq}.pkl": analysis_df}, artifact_path=PortAnaRecord.get_path()
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)
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logger.info(
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f"Portfolio analysis record 'port_analysis_{report_freq}.pkl' has been saved as the artifact of the Experiment {self.recorder.experiment_id}"
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f"Portfolio analysis record 'port_analysis_{_analysis_freq}.pkl' has been saved as the artifact of the Experiment {self.recorder.experiment_id}"
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)
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# print out results
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pprint("The following are analysis results of the excess return without cost.")
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pprint(f"The following are analysis results of benchmark return({_analysis_freq}).")
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pprint(risk_analysis(report_normal["bench"], freq=_analysis_freq))
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pprint(f"The following are analysis results of the excess return without cost({_analysis_freq}).")
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pprint(analysis["excess_return_without_cost"])
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pprint("The following are analysis results of the excess return with cost.")
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pprint(f"The following are analysis results of the excess return with cost({_analysis_freq}).")
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pprint(analysis["excess_return_with_cost"])
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for _analysis_freq in self.indicator_analysis_freq:
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indicators_normal = indicator_dict.get(_analysis_freq)
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if self.indicator_analysis_method is None:
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analysis_df = indicator_analysis(indicators_normal)
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else:
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analysis_df = indicator_analysis(indicators_normal, method=self.indicator_analysis_method)
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# log metrics
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analysis_dict = analysis_df["value"].to_dict()
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self.recorder.log_metrics(**{f"{_analysis_freq}.{k}": v for k, v in analysis_dict.items()})
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# save results
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self.recorder.save_objects(
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**{f"indicator_analysis_{_analysis_freq}.pkl": analysis_df}, artifact_path=PortAnaRecord.get_path()
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)
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pprint(f"The following are analysis results of indicators({_analysis_freq}).")
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pprint(analysis_df)
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def list(self):
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list_path = []
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for _freq in self.report_freq:
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for _freq in self.all_freq:
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list_path.extend(
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[
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PortAnaRecord.get_path(f"report_normal_{_freq}.pkl"),
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@@ -380,7 +419,7 @@ class PortAnaRecord(RecordTemp):
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)
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for _analysis_freq in self.risk_analysis_freq:
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if _analysis_freq in self.report_freq:
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if _analysis_freq in self.all_freq:
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list_path.append(PortAnaRecord.get_path(f"port_analysis_{_analysis_freq}.pkl"))
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else:
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warnings.warn(f"{_analysis_freq} is not found")
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