Financial asset returns are known to be conditionally heteroskedastic and generally non-normally distributed, fat-tailed and often skewed. These features must be taken into account to produce accurate forecasts of Value-at-Risk (VaR). We provide a comprehensive look at the problem by considering...

Financial asset returns are known to be conditionally heteroskedastic and generally non-normally distributed, fat-tailed and often skewed. In order to account for both the skewness and the excess kurtosis in returns, we combine the BEKK model from the multivariate GARCH literature with different...

We develop a DSGE model incorporating a banking sector comprising 4 banks connected in a stylised network representing their interbank exposures. The micro-founded framework allows inter alia for endogenous bank defaults and bank capital requirements. In addition, we introduce a central bank who...

We develop a DSGE model incorporating a banking sector comprising 4 banks connected in a stylised network representing their interbank exposures. The micro-founded framework allows inter alia for endogenous bank defaults and bank capital requirements. In addition, we introduce a central bank who...

Novel model specifications that include a time-varying long run component in the dynamics of realized covariance matrices are proposed. The adopted modeling framework allows the secular component to enter the model structure either in an additive fashion or as a multiplicative factor, and to be...

The Multiplicative MIDAS Realized DCC (MMReDCC) model simultaneously accounts for short and long term dynamics in the conditional (co)volatilities of asset returns, in line with the empirical evidence suggesting that their level is changing over time as a function of economic conditions. Herein...