Stock Market, Time Series Analysis, Time Series Forecasting, Python, Monte Carlo.
GBMsimulatorUniVar(So, mu, sigma, T, N): """ Parameters So: initial stocks' price mu: expected return sigma: volatility Cov: covariance matrix T: time period N: number of increments """ dim = np.size(So) t = np.linspace(0., T, int(N)) S = np.zeros([dim, int(N)]) S[:, 0] = So for i in range(1,