advanced-algorithmic-trading

298
label=’Avg Test MSE’
)
ax.legend(loc=0)
ax.set_xlabel(’Degree of Polynomial Fit’)
ax.set_ylabel(’Mean Squared Error’)
fig.set_facecolor(’white’)
plt.show()
def plot_test_error_curves_kf(kf_dict, folds, degrees):
fig, ax = plt.subplots()
ds = range(1, degrees+1)
for i in range(1, folds+1):
ax.plot(
ds,
kf_dict["fold_%s" % i],
lw=2,
label=’Test MSE - Fold %s’ % i
)
ax.plot(
ds,
kf_dict["avg"],
linestyle=’--’,
color="black",
lw=3,
label=’Avg Test MSE’
)
ax.legend(loc=0)
ax.set_xlabel(’Degree of Polynomial Fit’)
ax.set_ylabel(’Mean Squared Error’)
fig.set_facecolor(’white’)
plt.show()
if __name__ == "__main__":
symbol = "AMZN"
start_date = datetime.datetime(2004, 1, 1)
end_date = datetime.datetime(2016, 10, 27)
lags = create_lagged_series(
symbol, start_date, end_date, lags=10
)
# Use ten prior days of returns as predictor
# values, with "Today" as the response