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Financial Risk Management with Bayesian Estimation of GARCH Models : Theory and Applications

Ardia, David - 2009

This book presents in detail methodologies for the Bayesian estimation of single-regime and regime-switching GARCH … estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach offers an … the Bayesian paradigm for inference. The next three chapters describe the estimation of the GARCH model with Normal …

Persistent link: https://www.econbiz.de/10013156202

Nowcasting made easier : a toolbox for economists

Linzenich, Jan; Meunier, Baptiste - 2024

We provide a versatile nowcasting toolbox that supports three model classes (dynamic factor models, large Bayesian VAR …

Persistent link: https://www.econbiz.de/10015179785

"Children of the HMM" : modeling longitudinal customer behavior at Hulu.com

Schwartz, Eric M.; Bradlow, Eric T.; Fader, Peter; … - 2011

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...

Persistent link: https://www.econbiz.de/10009356633

Bayesian forecasts combination to improve the Romanian inflation predictions based on econometric models

Bratu, Mihaela - In: UTMS journal of economics / University of Tourism and … 5 (2014) 2, pp. 131-140

There are many types of econometric models used in predicting the inflation rate, but in this study we used a Bayesian … compared to other types of econometric models like VAR, Bayesian VAR, simultaneous equations model, dynamic model, log …-linear model. The Bayesian combinations that used experts' predictions as priors, when the shrinkage parameter tends to infinite …

Persistent link: https://www.econbiz.de/10010439151

BayVAR_R : Bayesian VAR Modeling in R

Quilis, Enrique M. - 2022

BayVAR_R is an R package designed to estimate and analyze Vec-tor Autoregressive (VAR) models from both a classical (UVAR) andBayesian (BVAR) perspective. The package includes functionalities forthe speci cation, estimation and diagnosis of such a models. It alsoprovides procedures for...

Persistent link: https://www.econbiz.de/10013309434

Bayesian dynamic variable selection in high dimensions

Koop, Gary - 2020

This paper proposes a variational Bayes algorithm for computationally efficient posterior and predictive inference in time-varying parameter (TVP) models. Within this context we specify a new dynamic variable/model selection strategy for TVP dynamic regression models in the presence of a large...

Persistent link: https://www.econbiz.de/10012851399

Genetic Algorithm Calibration of Seasonal BVAR Models

Quilis, Enrique M. - 2015

In this paper we explore the use of Genetic Algorithms (GA) to calibrate seasonal BVAR models. In this way, the mechanistic use of seasonal adjustment procedures is avoided, since seasonality becomes a structural, basic and explicit part of the BVAR model. At the same time, the use of GA allows...

Persistent link: https://www.econbiz.de/10014132203