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77 lines
2.9 KiB
Python
77 lines
2.9 KiB
Python
# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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# pylint: skip-file
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import logging
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from ...log import get_module_logger
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from ..evaluate import risk_analysis
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from ...data import D
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class User:
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def __init__(self, account, strategy, model, verbose=False):
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"""
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A user in online system, which contains account, strategy and model three module.
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Parameter
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account : Account()
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strategy :
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a strategy instance
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model :
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a model instance
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report_save_path : string
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the path to save report. Will not save report if None
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verbose : bool
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Whether to print the info during the process
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"""
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self.logger = get_module_logger("User", level=logging.INFO)
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self.account = account
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self.strategy = strategy
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self.model = model
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self.verbose = verbose
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def init_state(self, date):
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"""
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init state when each trading date begin
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Parameter
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date : pd.Timestamp
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"""
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self.account.init_state(today=date)
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self.strategy.init_state(trade_date=date, model=self.model, account=self.account)
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return
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def get_latest_trading_date(self):
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"""
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return the latest trading date for user {user_id}
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Parameter
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user_id : string
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:return
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date : string (e.g '2018-10-08')
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"""
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if not self.account.last_trade_date:
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return None
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return str(self.account.last_trade_date.date())
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def showReport(self, benchmark="SH000905"):
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"""
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show the newly report (mean, std, information_ratio, annualized_return)
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Parameter
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benchmark : string
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bench that to be compared, 'SH000905' for csi500
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"""
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bench = D.features([benchmark], ["$change"], disk_cache=True).loc[benchmark, "$change"]
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portfolio_metrics = self.account.portfolio_metrics.generate_portfolio_metrics_dataframe()
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portfolio_metrics["bench"] = bench
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analysis_result = {"pred": {}, "excess_return_without_cost": {}, "excess_return_with_cost": {}}
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r = (portfolio_metrics["return"] - portfolio_metrics["bench"]).dropna()
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analysis_result["excess_return_without_cost"][0] = risk_analysis(r)
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r = (portfolio_metrics["return"] - portfolio_metrics["bench"] - portfolio_metrics["cost"]).dropna()
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analysis_result["excess_return_with_cost"][0] = risk_analysis(r)
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self.logger.info("Result of porfolio:")
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self.logger.info("excess_return_without_cost:")
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self.logger.info(analysis_result["excess_return_without_cost"][0])
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self.logger.info("excess_return_with_cost:")
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self.logger.info(analysis_result["excess_return_with_cost"][0])
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return portfolio_metrics
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