Most time series models used in econometrics and empirical finance are estimated withmaximum likelihood methods, in particular when interest centers on density and Value{at{Risk (VaR) prediction. The standard maximum likelihood principle implicitly placesequal weight on each of the observations...

We consider time series models in which the conditional mean of the response variable given thepast depends on latent covariates. We assume that the covariates can be estimated consistentlyand use an iterative nonparametric kernel smoothing procedure for estimating the conditional meanfunction....

Tse (1998) proposes a model which combines the fractionally integrated GARCH formulationof Baillie, Bollerslev and Mikkelsen (1996) with the asymmetric power ARCH specification of Ding,Granger and Engle (1993). This paper analyzes the applicability of a multivariate constant...

While stochastic volatility models improve on the option pricing error when compared to theBlack-Scholes-Merton model, mispricings remain. This paper uses mixed normalheteroskedasticity models to price options. Our model allows for significant negative skewnessand time varying higher order...

We propose an empirical approach to determine the various economic sourcesdriving the US yield curve. We allow the conditional dynamics of the yield at differ-ent maturities to change in reaction to past information coming from several relevantpredictor variables. We consider both endogenous,...