- specifically, volatility clustering effectively captured by a GARCH model - this approach achieves global identification of shocks … while allowing for volatility spillovers across them. Findings reveal that increased variance in aggregate demand shocks …

In this paper, we investigate the dynamic response of stock market volatility to changes in monetary policy. Using a … vector autoregressive model, our findings reveal a significant and asymmetric response of stock returns and volatility to … monetary policy shocks. Although the increase in the volatility risk premium, futures-trading volume, and leverage appear to …

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 …

Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed … divergent when volatility clusters idiosyncratically.It is illustrated that this property is important for empirical …

This paper introduces a novel model to analyse the impact of macroeconomic shocks on volatility spillovers within key … market volatility, our study distinguishes between internal financial volatility spillovers and external shocks arising from … source of volatility spillovers, with Crude Oil being the principal spillover recipient. However, the Stock market's role in …

multivariate GARCH volatility speci cation is based on Tsiaplias and Chua (2009) and accommodates both direct and indirect … volatility spillovers. The impulse response function generalises Elder (2003) by considering the addition of common transmission … relevant for variables that exhibit direct and indirect volatility spillovers, such as exchange rates (Tsiaplias and Chua …