HIGHLIGHTS
SUMMARY
Literature Review To deal with the empirically observable "volatility clustering" effect in financial returns, the GARCH (Bollerslev 1986) class models and the SV model (Taylor 1982) are widely used in the modeling of volatility. The volatility forecasting performance of these models is compared with that of the daily return-based GARCH model, the rangebased ECARR model (Chou 2005), and the CRM model to disclose the gains from applying the PM framework-based interval regression models. Empirical evidence shows that the interval regression models significantly improve the volatility prediction accuracy compared to the point-data . . .
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