mirror of
https://github.com/webclinic017/drift.git
synced 2026-07-28 03:08:01 +00:00
Mark Aron Szulyovszky
57 lines
2.1 KiB
Python
57 lines
2.1 KiB
Python
#%%
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import pandas as pd
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import os
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import numpy as np
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#%%
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def load_files(path: str, add_features: bool, log_returns: bool) -> pd.DataFrame:
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dfs = [__load_df(os.path.join(path,f), f.split('.')[0], add_features, log_returns) for f in os.listdir(path) if os.path.isfile(os.path.join(path,f))]
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dfs = pd.concat(dfs, axis=1).fillna(0.)
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dfs.index = pd.DatetimeIndex(dfs.index)
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if add_features:
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dfs['day_month'] = dfs.index.day
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dfs['day_week'] = dfs.index.dayofweek
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dfs['month'] = dfs.index.month
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return dfs.drop(index=dfs.index[0], axis=0)
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def __load_df(path: str, prefix: str, add_features: bool, log_returns: bool) -> pd.DataFrame:
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df = pd.read_csv(path, header=0, index_col=0).fillna(0)
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if log_returns:
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df['returns'] = np.log(df['close']).diff(1)
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else:
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df['returns'] = df['close'].pct_change()
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if add_features:
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# volatility (10, 20, 30 days)
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df['vol_10'] = df['returns'].rolling(10).std()*(252**0.5)
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df['vol_20'] = df['returns'].rolling(20).std()*(252**0.5)
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df['vol_30'] = df['returns'].rolling(30).std()*(252**0.5)
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df['vol_60'] = df['returns'].rolling(30).std()*(252**0.5)
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# momentum (10, 20, 30, 60, 90 days)
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if log_returns:
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df['mom_10'] = np.log(df['close']).diff(10)
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df['mom_20'] = np.log(df['close']).diff(20)
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df['mom_30'] = np.log(df['close']).diff(30)
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df['mom_60'] = np.log(df['close']).diff(60)
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df['mom_90'] = np.log(df['close']).diff(90)
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else:
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df['mom_10'] = df['close'].pct_change(10)
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df['mom_20'] = df['close'].pct_change(20)
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df['mom_30'] = df['close'].pct_change(30)
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df['mom_60'] = df['close'].pct_change(60)
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df['mom_90'] = df['close'].pct_change(90)
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df = df.drop(columns=['open', 'high', 'low', 'close'])
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df.columns = [prefix + "_" + c for c in df.columns]
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return df
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# %%
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def create_target_cum_forward_returns(df: pd.DataFrame, source_column: str, period: int) -> pd.DataFrame:
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df['target'] = df[source_column].diff(period).shift(-period)
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return df |