Machine Learning, Forecasting, Trading, Forex Trading, Predictive Analytics.
dataset_normalizado.pct_change()) Thus we obtain the time series of daily returns. We fill NaNs with 0 using fillna() to remove any missing values. Now we have the computed daily returns that can be used to train forecasting models. dataset_taxa_retorno = np.log(1 +