This article presents a new filter for state-space models based on Bellman's dynamic programming principle applied to the posterior mode. The proposed Bellman filter generalises the Kalman filter including its extended and iterated versions, while remaining equally inexpensive computationally....

This short paper is a comment on ``Testing for Nonlinear Structure and Chaos in Economic Time Series'' by Catherine Kyrtsou and Apostolos Serletis. We summarize their main results and discuss some of their conclusions concerning the role of outliers and noisy chaos. In particular, we include...

This paper features an analysis of the effectiveness of a range of portfolio diversfication strategies as applied to a set of 17 years of monthly hedge fund index returns on a set of ten market indices representing 13 major hedge fund categories, as compiled by the EDHEC Risk Institute. The...

We explore how optimal emission abatement trajectories are affected by dynamic characteristics of greenhouse-gas emitting systems, such as inertia, induced innovation, and pathdependency, by formulating a compact and analytically tractable model with stylized damage assumptions to derive the...

This paper describes a forecasting exercise of close-to-open returns on major global stock indices, based on price patterns from foreign markets that have become available overnight. As the close-to-open gap is a scalar response variable to a functional variable, it is natural to focus on...

In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are ineffective, but that this problem can be removed by...