This study explores the benefits of incorporating fat-tailed innovations, asymmetric volatility response, and an … extended information set into crude oil return modeling and forecasting. To this end, we utilize standard volatility models … such as Generalized Autoregressive Conditional Heteroskedastic (GARCH), Generalized Autoregressive Score (GAS), and …

This paper investigates the forecasting performance of three popular variants of the non-linear GARCH models, namely VS-GARCH …, GJR-GARCH and Q-GARCH, with the symmetric GARCH(1,1) model as a benchmark. The application involves ten European stock … price indexes. Forecasts produced by each non-linear GARCH model and each index are evaluated using a common set of …

-form GARCH-in-mean model assigned to six globally leading financial markets. The obtained results support Keynes's theory - the …

volatility and economic activity assuming that both variables are driven by the same set of unobserved common factors and that … these factors affect volatility and economic activity with a time lag of at least a quarter. Under these assumptions, the … paper analytically shows that volatility is forward looking and that the output equation of a typical VAR estimated in the …

We use a factor model with stochastic volatility to decompose the time-varying variance of Macro economic and Financial … component plays an important role in driving the time-varying volatility of nominal and financial variables. The cross …-country co-movement in volatility of real and financial variables has increased over time with the common component becoming more …