Stock Market, Time Series Analysis, Time Series Forecasting, Python, Monte Carlo.
different stocks and the GBM function has an additional Covariance term as input. def create_covar(dfreturns): try: returns=[] arrOfReturns=[] columns = list(dfreturns) for column in columns: returns=dfreturns[column].values.tolist() arrOfReturns.append(returns) Cov = np.cov(np.array(arrOfReturns))