We propose a jackknife for reducing the order of the bias of maximum likelihood estimates of nonlinear dynamic fixed-effect panel models. In its simplest form, the half-panel jackknife, the estimatorisjust 2θˆ−θ1/2,where θˆ!istheMLEfromthefullpaneland θ1/2 istheaverageofthe two...

We investigate the existence of chart patterns in the Euro/Dollar intra-daily foreign exchange market. We use two identification methods of the different chart patterns: one built on close prices only, and one based on low and high prices. We look for twelve types of chart patterns and we study...

Copulas are extensively used for dependence modeling. In many cases the data does not reveal how the dependence can be modeled using a particular parametric copula. Nonparametric copulas do not share this problem since they are entirely data based. This paper proposes nonparametric estimation of...

The EGARCH is a popular model for discrete time volatility since it allows for asymmetric effects and naturally ensures positivity even when including exogenous variables. Estimation and inference is usually done via maximum likelihood. Although some progress has been made recently, a complete...

The GARCH and stochastic volatility (SV) models are two competing, well-known and often used models to explain the volatility of financial series. In this paper, we consider a closed form estimator for a stochastic volatility model and derive its asymptotic properties. We confirm our...

Benchmarking methods, and in particular Data Envelopment Analysis (DEA), have become well-established and informative tools for economic regulation. DEA is now routinely used by European regulators to set reasonable revenue caps for energy transmission and distribution system operators. The...

We consider a nonlinear vector model called the logistic vector smooth transition autoregressive model. The bivariate single-transition vector smooth transition regression model of Camacho (2004) is generalised to a multivariate and multitransition one. A modelling strategy consisting of...

We assess the predictive accuracy of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set 248 multivariate models that differ in their...

An important class of structural econometric models (nonlinear rational expectations,option pricing, auction models,...) characterize observable variables as highly nonlinear transformations of some latent variables. These transformations are one-to-one but they depend on the unknown...

In this paper, we survey some of the recent nonparapmetric estimation methods which were developed to price derivative contracts. We focus on equity options and staart with a so-called model-free approach which involves very little financial theory. Next we discuss nonparametric and...