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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 models. These models are widespread and essential tools in financial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique....

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

Incorporating Higher Moments into Value at Risk Estimation

Polanski, Arnold; Stoja, Evarist - 2020

Value-at-Risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a new simple approach to estimation of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting...

Persistent link: https://www.econbiz.de/10014213990

The Gibbs Sampler with Particle Efficient Importance Sampling for State-Space Models

Grothe, Oliver - 2017

Monte Carlo (MC) approximation of the standard Gibbs procedure which uses sequential MC (SMC) importance sampling inside the … generic and easily implementable SMC approach known as Particle Efficient Importance Sampling (PEIS). By using SMC importance … sampling densities which are approximately fully globally adapted to the targeted density of the states, PEIS can substantially …

Persistent link: https://www.econbiz.de/10012970355

On the practice of Bayesian inference in basic economic time series models using Gibbs sampling

Pooter, Michiel de; Segers, Rene; Dijk, Herman K. van - 2006

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling … algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the …

Persistent link: https://www.econbiz.de/10011349180

Efficient Bayesian Estimation and Combination of GARCH-Type Models

Ardia, David; Hoogerheide, Lennart F. - 2017

used in importance sampling for model estimation, model selection and model combination. The procedure is fully automatic …

Persistent link: https://www.econbiz.de/10014198683

Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations

Ardia, David; Hoogerheide, Lennart F. - 2019

time-consuming and difficult task of tuning a sampling algorithm. The usage of the package is shown in an empirical …

Persistent link: https://www.econbiz.de/10014203852

Bayesian estimation of the GARCH(1,1) model with student-t innovations

Ardia, David; Hoogerheide, Lennart F. - 2010

the tedious task of tuning a MCMC sampling algorithm. The usage of the package is shown in an empirical application to …

Persistent link: https://www.econbiz.de/10011380176

A Bayesian Method of Change-Point Estimation with Recurrent Regimes : Application to GARCH Models

Bauwens, Luc - 2017

We present an estimation and forecasting method, based on a differential evolution MCMC method, for inference in GARCH models subjected to an unknown number of structural breaks at unknown dates. We treat break dates as parameters and determine the number of breaks by computing the marginal...

Persistent link: https://www.econbiz.de/10012956780

Bayesian Inference on GARCH Models Using the Gibbs Sampler

Bauwens, Luc; Lubrano, Michel - 1999

compared with importance sampling and the Metropolis-Hastings algorithm. It is applied to estimate an asymmetric Student …

Persistent link: https://www.econbiz.de/10014197191

Fitting a distribution to survey data for the half-life of deviations from PPP

Fisher, Mark - 2015

This note presents a nonparametric Bayesian approach to fitting a distribution to the survey data provided in Kilian and Zha (2002) regarding the prior for the half-life of deviations from purchasing power parity (PPP). A point mass at infinity is included. The unknown density is represented as...

Persistent link: https://www.econbiz.de/10011403123