“Kointegracja Pythona” Kod odpowiedzi

Kointegracja Pythona

import matplotlib.pyplot as plt
import yfinance as yf
import pandas as pd
import datetime as dt
import statsmodels.tsa.stattools as ts
from scipy.stats import linregress


def download_data(stock, start, end):
    stock_data = {}
    ticker = yf.download(stock, start, end)
    stock_data['Price'] = ticker['Adj Close']
    return pd.DataFrame(stock_data)


def plot_pairs(data1, data2):
    fig, (ax1, ax2) = plt.subplots(2)
    fig.suptitle('Pair Of Stocks')
    ax1.plot(data1)
    ax2.plot(data2)
    plt.show()


def scatter_plot(data1, data2):
    plt.scatter(data1.values, data2.values)
    plt.suptitle('Cointegration')
    plt.xlabel('XOM')
    plt.ylabel('CVX')
    plt.show()


if __name__ == '__main__':
    start_date = dt.datetime(2011, 4, 1)
    end_date = dt.datetime(2020, 1, 1)

    pair1 = download_data('XOM', start_date, end_date)
    pair2 = download_data('CVX', start_date, end_date)

    plot_pairs(pair1, pair2)
    scatter_plot(pair1, pair2)

    # Linear Regression
    result = linregress(pair1.values[:, 0], pair2.values[:, 0])
    print(result)

    # Create the residual series
    residuals = pair1 - result.slope * pair2

    adf = ts.adfuller(residuals)
    print(adf)