Stand-alone marketing models are well-suited to deal with different behavioral features such as variation in transaction frequency (customer heterogeneity with latent classes), recency and attrition (“buy ‘till you die” models), and more general changes in customer transaction rates...

Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a...

This book presents in detail methodologies for the Bayesian estimation of single-regime and regime-switching GARCH models. These models are widespread and essential tools in financial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique....

In this paper we propose a novel self-exciting jump diffusion model for oil price dynamics based on a Hawkes-type jump-diffusion process. In particular, the jump intensity is stochastic and path dependent, implying that the occurrence of a jump will increase the probability of observing a new...

We examine the role of global and domestic shocks in driving macroeconomic fluctuations for Ghana. We are able to study the impact of exogenous shocks including productivity, credit supply, and commodity price shocks. We identify the shocks with a combination of sign and recursive restrictions...

We build on Fackler and King (1990) and propose a general calibration model for implied risk neutral densities. Our model allows for the joint calibration of a set of densities at different maturities and dates. The model is a Bayesian dynamic beta Markov random field which allows for possible...

This paper studies the properties of the Bayesian approach to estimation and comparison of dynamic equilibrium economies. Both tasks can be performed even if the models are nonnested, misspecified, and nonlinear. First, we show that Bayesian methods have a classical interpretation:...

Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood. This...

This chapter proposes an up-to-date review of estimation strategies available for the Bayesian inference of GARCH-type models. The emphasis is put on a novel efficient procedure named AdMitIS. The methodology automatically constructs a mixture of Student-t distributions as an approximation to...