Bayesian estimation and model selection for the weekly Colombian exchange rate

Norberto Rodríguez N. ()

Revista de Economía del Rosario, 2001, No 2059

Abstract: This document reviews and applies recently developed techniques for Bayesian estimation and model selection in the context of Time Series modelingfor Stochastic volatility. After the literature review on Generalized Conditional Autoregressive models, Stochastic Volatility models, and the relevant results on Markov chain monte Carlo methods (MCMC), an example applying such techniques is shown. The methodology is used with a series of Weekly Colombian - USA Exchange Rate on seven different models. The GARCH model, which uses Type-IV Pearson distribution, is favored for the selecting technique, Reversible Jump MCMC, over other models, including stochastic Volatility models with a student-t distribution.

Keywords: Estimation; markov chain Monte Carlo Methods MCMC; GARCH Models; Stochastic volatility; model selection (search for similar items in EconPapers)
JEL-codes: C11 C13 C15 C22 C52 (search for similar items in EconPapers)
Date: 2001
References: Add references at CitEc
Citations:

Downloads: (external link)
http://revistas.urosario.edu.co/index.php/economia/article/view/1003/902

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:col:000151:002059

Access Statistics for this article

More articles in Revista de Economía del Rosario from Universidad del Rosario Contact information at EDIRC.
Bibliographic data for series maintained by Facultad de Economía ().