In this paper we propose an on-line Bayesian filtering and smoothing method for time series models with heavy-tailed alpha-stable noise, with a particular focus on TVAR models. alpha-stable processes have been shown in the past to be a good model for many naturally occurring noise sources. We...

Following the Loss Distribution Approach (LDA), this article develops two procedures for the simulation of an annual loss distribution for the modeling of operational risk. First, we provide an overview of the typical compound-process LDA used widely in operational risk modeling, before...

Following the Loss Distributional Approach (LDA), this article develops two procedures for simulation of an annual loss distribution for modeling of Operational Risk. First, we provide an overview of the typical compound-process LDA used widely in Operational Risk modeling, before expanding upon...

Likelihood based estimation of the parameters of state space models can be carried out via a particle filter.  In this paper we show how to make valid inference on such parameters when the model is incorrect.  In particular we develop a simulation strategy for computing sandwich covariance...

We examine a general multi-factor model for commodity spot prices and futures valuation. We extend the multi-factor long-short model in Schwartz and Smith (2000) and Yan (2002) in two important aspects: firstly we allow for both the long and short term dynamic factors to be mean reverting...

Likelihood based estimation of the parameters of state space models can be carried out via a particle filter. In this paper we show how to make valid inference on such parameters when the model is incorrect. In particular we develop a simulation strategy for computing sandwich covariance...