Realized volatility in financial markets can be better predicted by considering the time-varying nature of volatility. By analyzing high-frequency data, researchers found that traditional models underestimated volatility due to non-Gaussian residuals and volatility clustering. Adjusting for these factors improved the accuracy of volatility forecasts for S&P500 index futures.