Bayesian Factor Selection in Dynamic Term Structure Models

Márcio Laurini

Economics Bulletin, 2011, vol. 31, issue 3, 2167-2176

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: Term Structure Models; Model Selection; MCMC; Nelson-Siegel (search for similar items in EconPapers)
JEL-codes: C4 (search for similar items in EconPapers)
Date: 2011-07-25
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Related works:
Working Paper: Bayesian Factor Selection in Dynamic Term Structure Models (2011)
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