concentrate on modeling the conditional mean. However, financial time series exhibit certain stylized features such as volatility … to address this issue and to gain insights on the volatility patterns of CDS spreads, bond yield spreads and stock prices …. A generalized autoregressive conditional heteroscedasticity (GARCH) model is applied to the data of four large US banks …

A growing literature uses changes in residual volatility for identifying structural shocks in vector autoregressive … in applications in this context. This study reviews the different volatility models and points out their advantages and …

Changes in residual volatility in vector autoregressive (VAR) models can be used for identifying structural shocks in a … structural VAR analysis. Testable conditions are given for full identification for the case where the volatility changes can be … modelled by a multivariate GARCH process. Formal statistical tests are presented for identification and their small sample …

The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of … financial returns and port-folio risk. In this paper, we propose an adjustment of GARCH implied conditional value-at-risk and …, especially the Frank-GARCH models provide most conservative risk forecasts and out-perform all rival models. …

stability of aggregate lending. I find that banking sector integration decreases the aggregate volatility of lending due to …

investigation. Results from event study methodology as well as from conditional volatility models used here do no seem to point to …