decompositions based on statistical vector autoregression (VAR) analysis, this study takes as a starting point a simple textbook … triangular format resembling the identification procedure of the VAR methodology. Applied to major bilateral exchange rate series …

developed by Vasicek in 1991 [1]. VAR is expressed as a sum of terms: the first contribution represents the value at risk of a …

uniqueness of a solution to the canonical (first-order) LRE model in finite-order VAR form and a quadratic matrix equation to …

shift from the 99% Value-at-Risk (VaR) to the 97.5% Expected Shortfall (ES) for internal models in market risk assessment …. Inspired by the above transition, we introduce a new distributional index, the probability equivalence level of VaR and ES … (PELVE), which identifies the balancing point for the equivalence between VaR and ES. PELVE enjoys many desirable theoretical …

We show that VAR calculation speedup of an order of magnitude can be obtained using Smart Monte Carlo with a …

models. I show that under certain conditions, if a solution exists and is unique, it can be cast in finite-order VAR form. I … also investigate the conditions for the VAR form to be stationary with a well-defined residual variance-covariance matrix … illustrates the practical use of the finite-order VAR representation. In particular, I argue that the identification of monetary …