Bayesian Factor Selection in Dynamic Term Structure Models

Márcio Laurini

No 2011-02, IBMEC RJ Economics Discussion Papers from Economics Research Group, IBMEC Business School - Rio de Janeiro

Abstract: 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.

Keywords: Dynamic Term Structure Models; Model Selection; Reversible Jump MCMC (search for similar items in EconPapers)
JEL-codes: C11 C15 G12 (search for similar items in EconPapers)
Date: 2011-04-18
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-ore
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Journal Article: Bayesian Factor Selection in Dynamic Term Structure Models (2011)
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