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Trading_strategies_RWH.py
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Trading_strategies_RWH.py
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import numpy as np
import pandas as pd
import yfinance as yf
import datetime as dt
from pylab import mpl, plt
plt.style.use("seaborn-v0_8-whitegrid")
mpl.rcParams['font.family'] = 'serif'
def load_raw_data(tickers, start_date, end_date):
raw = yf.download(tickers, start_date, end_date)['Adj Close']
raw = raw.reindex(columns=tickers)
raw = pd.DataFrame(raw)
raw.info()
return raw
def random_walk_hypothesis(raw, symbol):
data = pd.DataFrame(raw[symbol])
lags = 5
cols = []
for lag in range(1, lags + 1):
col = 'lag_{}'.format(lag)
data[col] = data[symbol].shift(lag)
cols.append(col)
print(data.head(7))
data.dropna(inplace=True)
reg = np.linalg.lstsq(data[cols], data[symbol], rcond=-1)
print(reg[0])
plt.figure(figsize=(10, 6))
plt.bar(cols, reg[0])
plt.show()
data['Perdiction'] = np.dot(data[cols], reg[0])
data[[symbol, 'Perdiction']].iloc[-75:].plot(figsize=(10, 6))
plt.show()
return data, reg
if __name__ == '__main__':
tickers = ['SPY', 'ALB']
start_date = '2020-01-01'
end_date = '2023-05-31'
raw_ = load_raw_data(tickers, start_date, end_date)
symbol = 'SPY'
data_, reg_ = random_walk_hypothesis(raw_, symbol)