HMM_for_Regime_Detection.py

X_train = train[["date", "return", "range", "close"]].set_index("date")
X_test = test[["date", "return", "range", "close"]].set_index("date")

model = mix.GaussianMixture(n_components=3, 
                            covariance_type="full", 
                            n_init=100, 
                            random_state=7).fit(X_train)

# Predict the optimal sequence of internal hidden state
hidden_states = model.predict(X_test)

print("Means and vars of each hidden state")
for i in range(model.n_components):
    print("{0}th hidden state".format(i))
    print("mean = ", model.means_[i])
    print("var = ", np.diag(model.covariances_[i]))
    print()