def scat_plot():
dates = pd.date_range('2009-01-01', '2012-12-31')
symbols = ['SPY', 'XOM', 'GLD']
df = get_data(symbols, dates)
daily_returns = compute_daily_returns(df)
daily_returns.plot(kind='scatter', x='SPY', y='XOM')
beta_XOM, alpha_XOM = np.polyfit(daily_returns['SPY'],
daily_returns['XOM'], 1)
plt.plot(daily_returns['SPY'],
beta_XOM * daily_returns['SPY'] + alpha_XOM,
'-',
color='r')
plt.show()
daily_returns.plot(kind='scatter', x='SPY', y='GLD')
beta_GLD, alpha_GLD = np.polyfit(daily_returns['SPY'],
daily_returns['GLD'], 1)
plt.plot(daily_returns['SPY'],
beta_GLD * daily_returns['SPY'] + alpha_GLD,
'-',
color='r')
plt.show()
print daily_returns.corr(method='pearson')
def scat_plot():
dates = pd.date_range('2009-01-01', '2012-12-31')
symbols = ['SPY', 'XOM', 'GLD']
df = get_data(symbols, dates)
daily_returns = compute_daily_returns(df)
daily_returns.plot(kind='scatter', x='SPY', y='XOM')
beta_XOM, alpha_XOM = np.polyfit(daily_returns['SPY'], daily_returns['XOM'], 1)
plt.plot(daily_returns['SPY'], beta_XOM*daily_returns['SPY'] + alpha_XOM, '-', color='r')
plt.show()
daily_returns.plot(kind='scatter', x='SPY', y='GLD')
beta_GLD, alpha_GLD = np.polyfit(daily_returns['SPY'], daily_returns['GLD'], 1)
plt.plot(daily_returns['SPY'], beta_GLD*daily_returns['SPY'] + alpha_GLD, '-', color='r')
plt.show()
print daily_returns.corr(method='pearson')
def hist_plot():
dates = pd.date_range('2009-01-01', '2012-12-31')
symbols = ['SPY', 'XOM']
df = get_data(symbols, dates)
daily_returns = compute_daily_returns(df)
daily_returns['SPY'].hist(bins=20, label='SPY')
daily_returns['XOM'].hist(bins=20, label='XOM')
#mean = daily_returns['SPY'].mean()
#print 'mean = ', mean
#std = daily_returns['SPY'].std()
#print 'std = ', std
#plt.axvline(mean, color='w', linestyle='dashed', linewidth=2)
#plt.axvline(std, color='r', linestyle='dashed', linewidth=2)
#plt.axvline(-std, color='r', linestyle='dashed', linewidth=2)
plt.legend(loc='upper right')
plt.show()
print daily_returns.kurtosis()
def hist_plot():
dates = pd.date_range('2009-01-01', '2012-12-31')
symbols = ['SPY', 'XOM']
df = get_data(symbols, dates)
daily_returns = compute_daily_returns(df)
daily_returns['SPY'].hist(bins=20, label='SPY')
daily_returns['XOM'].hist(bins=20, label='XOM')
#mean = daily_returns['SPY'].mean()
#print 'mean = ', mean
#std = daily_returns['SPY'].std()
#print 'std = ', std
#plt.axvline(mean, color='w', linestyle='dashed', linewidth=2)
#plt.axvline(std, color='r', linestyle='dashed', linewidth=2)
#plt.axvline(-std, color='r', linestyle='dashed', linewidth=2)
plt.legend(loc='upper right')
plt.show()
print daily_returns.kurtosis()
