Bayesian Factor Selection in Dynamic Term Structure Models

This paper discusses Bayesian procedures for factor selection in dynamic term structure models through simulation methods based on Markov Chain Monte Carlo. The number of factors, besides influencing the fitting and prediction of observed yields, is also relevant to features such as the imposition of no-arbitrage conditions. We present a methodology for selecting the best specification in the Nelson-Siegel class of models using Reversible Jump MCMC.

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Year of publication:	2011
Authors:	Laurini, Marcio
Published in:	Economics Bulletin. - AccessEcon, ISSN 1545-2921. - Vol. 31.2011, 3, p. 2167-2176
Publisher:	AccessEcon
Subject:	Term Structure Models \| Model Selection \| MCMC \| Nelson-Siegel

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Extent:	application/pdf
Type of publication:	Article
Language:	English
Classification:	C4 - Econometric and Statistical Methods: Special Topics
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10009207368