We derive a framework for asymptotically valid inference in stable vector autoregressive (VAR) models with conditional … heteroskedasticity of unknown form. We prove a joint central limit theorem for the VAR slope parameter and innovation covariance … parameter estimators and address bootstrap inference as well. Our results are important for correct inference on VAR statistics …

In this note we present an updated algorithm to estimate the VAR with stochastic volatility proposed in Mumtaz (2018 …

the risk better than Value-at-Risk especially. While VaR is a measure of end-of-horizon risk, MaxVaR captures the interim … horizon. For a 30-day maturity option, we find that MaxVaR can be 40% higher than VaR at a 5% significance level. It … highlights the importance of MaxVaR as a risk measure and shows that the risk is vastly underestimated when VaR is used as the …

following econometric techniques OLS, VAR, TAR, GMM and VECM. The results showed a positive and significant, but weak …

This paper introduces a VAR with stochastic volatility in mean where the residuals of the volatility equations and the …

While a lot of research concentrates on the respective merits of VaR and TCE, which are the two most classic risk … quantiles of this indicator to the quantiles of VaR in a simple Pareto framework, and then in a generalized Pareto framework. We …