In this paper, I study the equilibrium pricing of asset shares in the presence of dynamic private information. The market consists of a risk-neutral informed agent who observes the firm value, noise traders and competitive market makers who set share prices using the total order flow as a noisy...

We use the Cox process (or a doubly stochastic Poisson process) to model the claim arrival process for catastrophic events. The shot noise process is used for the claim intensity function within the Cox process. The Cox process with shot noise intensity is examined by piecewise deterministic...

Ensemble prediction systems aim to account for uncertainties of initial conditions and model error. Ensemble forecasting is sometimes viewed as a method of obtaining (objective) probabilistic forecasts. How is one to judge the quality of an ensemble at forecasting a system? The probability that...

This paper presents a Markov chain Monte Carlo algorithm for a class of multivariate diffusion models with unobserved paths. This class is of high practical interest as it includes most diffusion driven stochastic volatility models. The algorithm is based on a data augmentation scheme where the...

The parameters of a finite mixture model cannot be consistently estimated when the data come from an embedded distribution with fewer components than that being fitted, because the distribution is represented by a subset in the parameter space, and not by a single point. Feng & McCulloch (1996)...

For a simplified structural equation/IV regression model with one right-side endogenous variable, we obtain the exact conditional distribution function for Moreira's (2003) conditional likelihood ratio (CLR) test. This is then used to obtain the critical value function needed to implement the...

Different conditional independence specifications for ordinal categorical data are compared by calculating a posterior distribution over classes of graphical models. The approach is based on the multivariate ordinal probit model where the data are considered to have arisen as truncated...

In a recent paper González Manteiga and Vilar Fernández (1995) considered the problem of testing linearity of a regression under MA(infinity) structure of the errors using a weighted L2-distance between a parametric and a nonparametric fit. They established asymptotic normality of the...

The analysis of repeated surveys can be approached using model-based inference, utilising the methods of time series analysis. On a long run of repeated surveys it should then be possible to enhance the estimation of a survey parameter. However, many repeated surveys that are suited to this...

A compositional time series is defined as multivariate time series in which each of the series has values bounded betweenzero and one and the sum of the series equals one at each time point. Data with such characteristics are observed in repeatedsurveys when a survey variable has a multinomial...