Standard VAR and Bayesian VAR models are proven to be reliable tools for modeling and forecasting, yet they are still linear and they do not consider time-variation in parameters. VAR modeling is subject to the Lucas critique and fails to take into account the inherent nonlinearities of the...

We consider a time-varying parameter vector autoregressive model with stochastic volatility and mixture innovations to study the empirical relevance of the Lucas critique for the postwar U.S. economy. The model allows blocks of parameters to change at endogenously estimated points of time....

Purpose – The aim of this paper is to measure and evaluate the relationship between returns-volatility and trading volume and returns and volatility of financial market indexes using time-varying copulas. Design/methodology/approach – The time dynamic dependence parameter is allowed to...

In this paper we turn our attention to comparing the policy function obtained by Beck and Wieland (J Econ Dyn Control 26:1359–1377, <CitationRef CitationID="CR6">2002</CitationRef>) to the one obtained with adaptive control methods. It is an integral part of the optimal learning method used by Beck and Wieland to obtain a policy...</citationref>

We propose a novel Bayesian model combination approach where the combination weights depend on the past forecasting performance of the individual models entering the combina- tion through a utility-based objective function. We use this approach in the context of stock return predictability and...

Purpose – The aim of this paper is to measure and evaluate the relationship between returns-volatility and trading volume and returns and volatility of financial market indexes using time-varying copulas. Design/methodology/approach – The time dynamic dependence parameter is allowed to...

This chapter of the Handbook of Computational Economics is mostly about research on active learning and is confined to discussion of learning in dynamic models in which the system equations are linear, the criterion function is quadratic, and the additive noise terms are Gaussian. Though there...