Improved estimation of portfolio value‐at‐risk under copula models with mixed marginals

Portfolio value‐at‐risk (PVAR) is widely used in practice, but recent criticisms have focused on risks arising from biased PVAR estimates due to model specification errors and other problems. The PVAR estimation method proposed in this article combines generalized Pareto distribution tails with the empirical density function to model the marginal distributions for each asset in the portfolio, and a copula model is used to form a joint distribution from the fitted marginals. The copula–mixed distribution (CMX) approach converges in probability to the true marginal return distribution but is based on weaker assumptions that may be appropriate for the returns data found in practice. CMX is used to estimate the joint distribution of log returns for the Taiwan Stock Exchange (TSE) index and the associated futures contracts on SGX and TAIFEX. The PVAR estimates for various hedge portfolios are computed from the fitted CMX model, and backtesting diagnostics indicate that CMX outperforms the alternative PVAR estimators. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:997–1018, 2006     

Fixed Exchange Rates and Disinflation in Emerging Markets: How Large Is the Effect?

We examine developing countries which have institutional quality ratings for the effects of exchange rate rigidity on inflation. The level of institutional development exerts no effect on the impact of currency regimes. However, the interaction of institutional quality and exchange rates has, in the most plausible specifications, a negative impact on inflation. This suggests that fixed exchange rates exert at most a contingent effect on inflation, and indicates that countries in Eastern Europe and Latin America contemplating currency pegs would be better off improving institutional quality prior to adopting the euro or dollar and expecting a large subsequent disinflationary effect. JEL no.  F31, O11