Bond portfolio optimization using dynamic factor models

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 portfoli...

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Bibliographic Details
Published inJournal of empirical finance Vol. 37; pp. 128 - 158
Main Authors Caldeira, João F., Moura, Guilherme V., Santos, André A.P.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.06.2016
Subjects
Bond indexing
Dynamic policy selection
Kalman filter
Out-of-sample evaluation
Portfolio optimization
Yield curve forecasts
Portfolio optimization
C53
Dynamic policy selection
E43
Kalman filter
Out-of-sample evaluation
Bond indexing
G17
Yield curve forecasts
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Summary: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. •We present a simple way to map yields to expected returns of bonds and their covariance matrix.•We compare mean-variance bond portfolios to traditional bond desk strategies.•We propose a duration-constrained optimized portfolio.•Optimized bond portfolios using U.S.-Treasuries exhibit attractive risk-return profiles.
ISSN:0927-5398
1879-1727
DOI:10.1016/j.jempfin.2016.03.004