Markov Chains, Markov Process, Python, Discrete Time Markov, Probability.
components π_1t and π_2t of π_t= [ π_1t, π_2t] for t=1 through 10. #plot pi_1t = P(X_t = +1) versus t fig = plt.figure() fig.suptitle('Probability of closing higher than previous day\'s close') plt.plot(range(len(pi)), pi[:,0]) plt.show() #plot pi_2t = P(X_t = -1) versus t fig.suptitle('Probability