Affine Term Structure Models: Applications in Portfolio Optimization and Change Point Detection
Stelios Psarakis () and
Athanasios N. Yannacopoulos
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Konstantinos Bisiotis: Department of Statistics and Department of Accounting and Finance, Athens University of Economics and Business, Patission 76, 104 34 Athens, Greece
Stelios Psarakis: Department of Statistics and Laboratory of Statistical Methodology, Athens University of Economics and Business, Patission 76, 104 34 Athens, Greece
Athanasios N. Yannacopoulos: Stochastic Modeling and Applications Laboratory, Department of Statistics, Athens University of Economics and Business, Patission 76, 104 34 Athens, Greece
Mathematics, 2022, vol. 10, issue 21, 1-33
Affine term structure models are widely used for studying the relationship between yields on assets of different maturities. However, it can be a helpful tool for the construction of fixed-income portfolios. The monitoring of these bond portfolios is of great importance for the investor. The purpose of this work is twofold. Firstly, we construct and optimize fixed-income portfolios using Markowitz’s portfolio approach to a multifactor Gaussian affine term structure model (ATSM) under no-arbitrage conditions estimated with the minimum chi square estimation method. The fixed-income portfolios based on the term structure model are compared with some benchmark portfolio strategies, and our findings show that our proposed approach performs well under the risk–return tradeoff. Secondly, we propose control chart procedures for monitoring the optimal weights of government bond portfolios in order to detect possible changes. The results indicate that control chart procedures can be useful in the detection of changes in the optimal asset allocation of fixed income portfolios.
Keywords: affine models; bond portfolio; change points; control charts (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:21:p:4094-:d:961672
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