The article introduces a new method to model the volatility of financial returns using common and unique factors. The model is simple and efficient, able to handle complex data without becoming too complicated. By analyzing data from stocks in the S&P100, the researchers found that their model accurately captures both common trends and individual shocks in volatility. This approach could help investors better understand and predict market behavior.