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Marcio Laurini
 
''Bayesian Factor Selection in Dynamic Term Structure Models''
( 2011, Vol. 31 No.3 )
 
 
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
JEL: C4 - Econometric and Statistical Methods: Special Topics
 
Manuscript Received : Apr 17 2011 Manuscript Accepted : Jul 25 2011

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