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:	2011-04-18
Authors:	Laurini, Márcio
Institutions:	IBMEC Business School - Rio de Janeiro
Subject:	Dynamic Term Structure Models \| Model Selection \| Reversible Jump MCMC

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Extent:	application/pdf
Series:	IBMEC RJ Economics Discussion Papers.
Type of publication:	Book / Working Paper
Language:	English
Notes:	Number 2011-02
Classification:	C11 - Bayesian Analysis ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; G12 - Asset Pricing
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10009001791