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RL backtest pipeline on 5-min data (#1417)
* Workflow runnable * CI * Slight changes to make the workflow runnable. The changes of handler/provider should be reverted before merging. * Train experiment successful * Refine handler & provider * test passed * Ready to test on server * Minor * Test passed * TWAP training * Add PPOReward * Add a FIXME * Refine PPO reward according to PR comments * Minor * Resolve PR comments * CI issues * CI issues * CI issues
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@@ -1,6 +1,7 @@
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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from __future__ import annotations
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import pathlib
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from collections import OrderedDict
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@@ -86,7 +87,7 @@ class PortfolioMetrics:
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self.benches: dict = OrderedDict()
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self.latest_pm_time: Optional[pd.TimeStamp] = None
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def init_bench(self, freq: str = None, benchmark_config: dict = None) -> None:
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def init_bench(self, freq: str | None = None, benchmark_config: dict | None = None) -> None:
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if freq is not None:
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self.freq = freq
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self.benchmark_config = benchmark_config
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@@ -149,15 +150,15 @@ class PortfolioMetrics:
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self,
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trade_start_time: Union[str, pd.Timestamp] = None,
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trade_end_time: Union[str, pd.Timestamp] = None,
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account_value: float = None,
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cash: float = None,
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return_rate: float = None,
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total_turnover: float = None,
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turnover_rate: float = None,
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total_cost: float = None,
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cost_rate: float = None,
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stock_value: float = None,
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bench_value: float = None,
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account_value: float | None = None,
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cash: float | None = None,
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return_rate: float | None = None,
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total_turnover: float | None = None,
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turnover_rate: float | None = None,
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total_cost: float | None = None,
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cost_rate: float | None = None,
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stock_value: float | None = None,
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bench_value: float | None = None,
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) -> None:
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# check data
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if None in [
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