Bond portfolio optimization using dynamic factor models

João F. Caldeira*, Guilherme V. Moura, André A.P. Santos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

A general class of dynamic factor models is used to obtain optimal bond portfolios, and to develop a duration-constrained mean-variance optimization, which can be used to improve bond indexing. An empirical application involving two large data sets of U.S. Treasuries shows that the proposed portfolio policy outperforms a set of yield curve strategies used in bond desks. Additionally, we propose a dynamic rule to switch among alternative bond investment strategies, and find that the benefits of such dynamic rule are even more pronounced when the set of available policies is augmented with the proposed mean-variance portfolios.

Original languageEnglish
Pages (from-to)128-158
Number of pages31
JournalJournal of Empirical Finance
Volume37
Early online date24 Mar 2016
DOIs
Publication statusPublished - 1 Jun 2016

Keywords

  • bond indexing
  • C53
  • dynamic policy selection
  • E43
  • G17
  • Kalman filter
  • out-of-sample evaluation
  • portfolio optimization
  • yield curve forecasts

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