CAPM_Single stock

import statsmodels.api as sm
import pandas as pd
import pandas_datareader as web
import matplotlib.pyplot as plt
%matplotlib inline

start = pd.to_datetime('2010-01-04')
end = pd.to_datetime('2020-04-16')

spy_etf = web.DataReader('SPY', 'yahoo', start, end)

spy_etf.info()

spy_etf.head()

aapl = web.DataReader('AAPL', 'yahoo', start, end)

aapl.head()

aapl['Close'].plot(label = 'AAPL',
                   figsize = (12, 8))
spy_etf['Close'].plot(label = 'SPY Index')
plt.legend()

aapl['Cumulative'] = aapl['Close'] / aapl['Close'].iloc[0]
spy_etf['Cumulative'] = spy_etf['Close'] / spy_etf['Close'].iloc[0]

aapl['Cumulative'].plot(label = 'AAPL',
                        figsize = (10,8))
spy_etf['Cumulative'].plot(label = 'SPY Index')
plt.legend()
plt.title('Cumulative Return')

aapl['Daily Return'] = aapl['Close'].pct_change(1)
spy_etf['Daily Return'] = spy_etf['Close'].pct_change(1)

fig = plt.figure(figsize = (12, 8))
plt.scatter(aapl['Daily Return'], spy_etf['Daily Return'],alpha = 0.3)

aapl['Daily Return'].hist(bins = 100, figsize = (12, 8))

spy_etf['Daily Return'].hist(bins = 100, figsize = (12, 8))

X = sm.add_constant(spy_etf['Daily Return'].iloc[1:])
reg1 = sm.OLS(aapl['Daily Return'].iloc[1:], X, missing='drop')
results = reg1.fit()
print(results.summary())