Python, Monte Carlo Simulation, Trading, Probability, Investment.
print(year) market_return = np.random.normal(expected_returns, volatility) final_value = sip + (1+ market_return)* investment # print("\t{}".ljust(10).format(round(market_return, 4)), "\t{}".rjust(10).format(round(final_value, 4))) investment = final_value lst.append(final_value) df[i] = lst The