The article introduces a new method to estimate and predict the volatility of multiple time series data. The researchers use a special type of mathematical model to describe how the volatility changes over time, incorporating different distributions to capture uncertainty. They apply this method to real-world data on metal prices and find that it works well for financial data, improving upon existing models.