Markov Chains, Markov Process, Python, Discrete Time Markov, Probability.
range [0, 2.0] delta = random.random() * 2 # generate a random number in the range [0.0, 1.0] r = random.random() # if r <= P(X_t = +1), increase the closing price by delta, # else decrease the closing price by delta if r <= pi_t[0]: closing_price = math.max(closing_price*(100+delta)/100,1.0) else: