Machine Learning, Forecasting, Trading, Forex Trading, Predictive Analytics.
returns with dataset_taxa_retorno.std(). Then we generate random values from a standard normal distribution with stats.norm.ppf(np.random.rand()) These random Z values represent random shocks in daily returns. To simulate future returns, we apply: returns = exp(drift + standard_dev * Z) Where: