Sploe = 2: means that SPY move up 1, ABC move up 2
Correlation: how close those dots close to the line.
def scatter(df): plot_data(df, title="Data frame", yLabel="Time")
plt.show() dr = compute_daily_return(df)
plot_data(dr, title="Daily returns", yLabel="Daily returns") dr['GOOG'].hist(bins=20, label="GOOG")
dr['SPY'].hist(bins=20, label="SPY")
plt.legend(loc='upper right') # Scatterplot SPY vs GOOG
dr.plot(kind='scatter', x = 'SPY', y = 'GOOG')
spy = dr['SPY'][:-1] # remove nan value
goog = dr['GOOG'][:-1] # remove nan value
beta_goog, alpha_goog = np.polyfit(spy, goog, 1)
# beta_goog= 1.23719057977
# alpha_goog= -0.000283995818653
plt.plot(dr['SPY'], beta_goog*dr['SPY']+alpha_goog, '-', color='r')
plt.show() print("Correlation", dr.corr(method='pearson')) # Get kurtosis
print("kurtosis=", dr.kurtosis())if __name__ == '__main__':
df=test_run()
scatter(df[['SPY', 'GOOG']])