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']])