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59 lines
1.6 KiB
Python
59 lines
1.6 KiB
Python
"""波动率类因子。"""
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from __future__ import annotations
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import numpy as np
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import pandas as pd
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from easy_tdx.factor.base import Factor, register_factor
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@register_factor
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class Volatility20D(Factor):
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name = "volatility_20d"
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category = "volatility"
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description = "20 日波动率（20 日收益率标准差）"
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inputs = ("close",)
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def compute(self, df: pd.DataFrame) -> pd.Series:
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ret = df["close"].pct_change()
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return ret.rolling(20).std()
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@register_factor
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class ATR14D(Factor):
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name = "atr_14d"
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category = "volatility"
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description = "14 日平均真实波幅（ATR）"
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inputs = ("high", "low", "close")
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def compute(self, df: pd.DataFrame) -> pd.Series:
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high = df["high"].to_numpy(dtype=np.float64)
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low = df["low"].to_numpy(dtype=np.float64)
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close = df["close"].to_numpy(dtype=np.float64)
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tr = np.empty(len(df), dtype=np.float64)
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tr[0] = np.nan
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tr[1:] = np.maximum(
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high[1:] - low[1:],
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np.maximum(
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np.abs(high[1:] - close[:-1]),
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np.abs(low[1:] - close[:-1]),
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),
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)
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return pd.Series(tr, index=df.index).rolling(14).mean()
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@register_factor
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class TurnoverRate(Factor):
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name = "turnover_rate"
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category = "volatility"
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description = "换手率代理（当日成交额 / 20 日均成交额）"
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inputs = ("amount",)
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def compute(self, df: pd.DataFrame) -> pd.Series:
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amt = df["amount"]
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ma20 = amt.rolling(20).mean()
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return amt / ma20.replace(0, np.nan)
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