In this paper, we extend the concept of mutual exclusivity proposed by Dhaene and Denuit (1999) to its tail counterpart and baptise this new dependency structure as tail mutual exclusivity. Probability levels are first specified for each component of the random vector. Under this dependency...

The computation of various risk metrics is essential to the quantitative risk management of variable annuity guaranteed benets. The current market practice of Monte Carlo simulation often requires intensive computations, which can be very costly for insurance companies to implement and take so...

We study risk and return properties of capital structure arbitrage strategies aiming to profit from temporal mispricing between equity and credit default swaps (CDSs) of companies. We find that capital structure arbitrage provides an attractive annualized return of 24.35% on invested capital....

We investigate the determinants of bid-ask spreads on corporate credit default swaps (CDSs). We find that proxies for dealer inventory costs such as variability of CDS premia and CDS trading volume explain as much as 80% of variation in CDS bid-ask spreads. We also analyze the influence of...

Highly non-elliptical posterior distributions may occur in several econometric models, in particular, when the likelihood information is allowed to dominate and data information is weak. We explain the issue of highly non-elliptical posteriors in a model for the effect of education on income...

We introduce a dynamic statistical model for Skellam distributed random variables. The Skellam distribution can be obtained by taking differences between two Poisson distributed random variables. We treat cases where observations are measured over time and where possible serial correlation is...

This discussion paper resulted in a publication in the <I>International Journal of Forecasting</I> (2010). Vol. 26(2), 231-247.<P> An efficient and accurate approach is proposed for forecasting Value at Risk [VaR] and Expected Shortfall [ES] measures in a Bayesian framework. This consists of a new...</p></i>

We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear non-Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when these proposal densities are used in an independent...

This paper resulted in a publication in the <I>Journal of Econometrics</I> (2014). Volume 180, pages 127-140.<P> An exact maximum likelihood method is developed for the estimation of parameters in a nonlinear non-Gaussian dynamic panel data model with unobserved random individual-specific and time-varying...</p></i>

Accepted for an article forthcoming in the <I>Review of Economics and Statics</I>. Volume 97, 2015.<P> We study whether and when parameter-driven time-varying parameter models lead to forecasting gains over observation-driven models. We consider dynamic count, intensity, duration, volatility and copula...</p></i>