In this paper, control variates are proposed to speed up Monte Carlo simulations to estimate expected error rates in multivariate classification.

Stochastic simulation with antithetic variates is used to evaluate the bias of deterministic simulation in nonlinear econometric models. Application to the Klein-Goldberger model exemplifies the potentiality of the method.

We propose using a Bayesian time-varying coefficient model estimated with Markov chain-Monte Carlo methods to measure contagion empirically. The proposed measure works in the joint presence of heteroskedasticity and omitted variables and does not require knowledge of the timing of the crisis. It...

(Re)insurance companies need to model their liabilities' portfolio to compute the risk-adjusted capital (RAC) needed to support their business. The RAC depends on both the distribution and the dependence functions that are applied among the risks in a portfolio. We investigate the impact of...

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation...

This paper discusses the estimation of models of the term structure of interest rates. After reviewing the term structure models, specifically the Nelson-Siegel Model and Affine Term- Structure Model, this paper estimates the terms structure of Treasury bond yields for the United States with...

This paper provides a selective overview of nonlinear exchange rate models recently proposed in the literature and assesses their contribution to understanding exchange rate behavior. Two key questions are examined. The first question is whether nonlinear autoregressive models of real exchange...

This paper presents some conventional and new measures of market, credit, and liquidity risks for government bonds. These measures are analyzed from the perspective of a sovereign's debt manager. In particular, it examines duration, convexity, M-square, skewness, kurtosis, and VaR statistics as...

A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating Bayesian parameters and filtering volatilities. Volatility persistence being close to one was...