mirror of
https://github.com/webclinic017/drift.git
synced 2026-07-27 18:57:55 +00:00
Mark Aron Szulyovszky
111 lines
3.9 KiB
Python
111 lines
3.9 KiB
Python
#%%
|
|
import pandas as pd
|
|
import os
|
|
import numpy as np
|
|
from utils.technical_indicators import ROC, RSI, STOK, STOD
|
|
|
|
#%%
|
|
|
|
def load_files(path: str, add_features: bool, log_returns: bool, narrow_format: bool = False) -> pd.DataFrame:
|
|
files = [f for f in os.listdir(path) if os.path.isfile(os.path.join(path,f)) and not f.startswith('.')]
|
|
dfs = [__load_df(os.path.join(path,f), f.split('.')[0], add_features, log_returns, narrow_format) for f in files]
|
|
if narrow_format:
|
|
dfs = pd.concat(dfs, axis=0).fillna(0.)
|
|
else:
|
|
dfs = pd.concat(dfs, axis=1).fillna(0.)
|
|
|
|
dfs.index = pd.DatetimeIndex(dfs.index)
|
|
|
|
if add_features:
|
|
dfs['day_month'] = dfs.index.day
|
|
dfs['day_week'] = dfs.index.dayofweek
|
|
dfs['month'] = dfs.index.month
|
|
|
|
if narrow_format:
|
|
return dfs
|
|
else:
|
|
return dfs.drop(index=dfs.index[0], axis=0)
|
|
|
|
def __load_df(path: str, prefix: str, add_features: bool, log_returns: bool, narrow_format: bool = False) -> pd.DataFrame:
|
|
df = pd.read_csv(path, header=0, index_col=0).fillna(0)
|
|
|
|
if log_returns:
|
|
df['returns'] = np.log(df['close']).diff(1)
|
|
else:
|
|
df['returns'] = df['close'].pct_change()
|
|
|
|
if add_features:
|
|
# volatility (10, 20, 30 days)
|
|
df['vol_10'] = df['returns'].rolling(10).std()*(252**0.5)
|
|
df['vol_20'] = df['returns'].rolling(20).std()*(252**0.5)
|
|
df['vol_30'] = df['returns'].rolling(30).std()*(252**0.5)
|
|
df['vol_60'] = df['returns'].rolling(30).std()*(252**0.5)
|
|
|
|
# momentum (10, 20, 30, 60, 90 days)
|
|
if log_returns:
|
|
df['mom_10'] = np.log(df['close']).diff(10)
|
|
df['mom_20'] = np.log(df['close']).diff(20)
|
|
df['mom_30'] = np.log(df['close']).diff(30)
|
|
df['mom_60'] = np.log(df['close']).diff(60)
|
|
df['mom_90'] = np.log(df['close']).diff(90)
|
|
else:
|
|
df['mom_10'] = df['close'].pct_change(10)
|
|
df['mom_20'] = df['close'].pct_change(20)
|
|
df['mom_30'] = df['close'].pct_change(30)
|
|
df['mom_60'] = df['close'].pct_change(60)
|
|
df['mom_90'] = df['close'].pct_change(90)
|
|
|
|
|
|
df['roc_10'] = ROC(df['close'], 10)
|
|
df['roc_30'] = ROC(df['close'], 30)
|
|
|
|
df['rsi_10'] = RSI(df['close'], 10)
|
|
df['rsi_30'] = RSI(df['close'], 30)
|
|
df['rsi_100'] = RSI(df['close'], 30)
|
|
|
|
df['stok_10'] = STOK(df['close'], df['low'], df['high'], 10)
|
|
df['stod_10'] = STOD(df['close'], df['low'], df['high'], 10)
|
|
df['stok_30'] = STOK(df['close'], df['low'], df['high'], 30)
|
|
df['stod_30'] = STOD(df['close'], df['low'], df['high'], 30)
|
|
df['stok_200'] = STOK(df['close'], df['low'], df['high'], 200)
|
|
df['stod_200'] = STOD(df['close'], df['low'], df['high'], 200)
|
|
|
|
|
|
df = df.replace([np.inf, -np.inf], 0.)
|
|
df = df.drop(columns=['open', 'high', 'low', 'close'])
|
|
if narrow_format:
|
|
df["ticker"] = np.repeat(prefix, df.shape[0])
|
|
else:
|
|
df.columns = [prefix + "_" + c for c in df.columns]
|
|
return df
|
|
|
|
# %%
|
|
def create_target_cum_forward_returns(df: pd.DataFrame, source_column: str, period: int) -> pd.DataFrame:
|
|
df['target'] = df[source_column].diff(period).shift(-period)
|
|
df = df.iloc[:-period]
|
|
return df
|
|
|
|
|
|
#%%
|
|
def create_target_pos_neg_classes(df: pd.DataFrame, source_column: str, period: int) -> pd.DataFrame:
|
|
df['target'] = df[source_column].diff(period).shift(-period)
|
|
df['target'] = df['target'].map(lambda x: 0 if x <= 0.0 else 1)
|
|
df = df.iloc[:-period]
|
|
return df
|
|
|
|
def create_target_four_classes(df: pd.DataFrame, source_column: str, period: int) -> pd.DataFrame:
|
|
def __get_class(x):
|
|
treshold = 0.08
|
|
if x <= -treshold:
|
|
return 0
|
|
elif x > -treshold and x <= 0:
|
|
return 1
|
|
elif x > 0 and x <= treshold:
|
|
return 2
|
|
else:
|
|
return 3
|
|
|
|
df['target'] = df[source_column].diff(period).shift(-period)
|
|
df['target'] = df['target'].map(__get_class)
|
|
df = df.iloc[:-period]
|
|
return df |