On a consistent state-space bond markets model for pricing long-maturity bonds

Dennis Ikpe, Yethu Sithole and Samuel Asante Gyamerah
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Dennis Ikpe: Department of Statistics and Probability, Michigan State University, USA†African Institute for Mathematical Sciences, South Africa
Yethu Sithole: ��Department of Mathematical Sciences, University of South Africa, South Africa
Samuel Asante Gyamerah: �Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Ghana¶Laboratory for Interdisciplinary Statistical Analysis – Kwame Nkrumah University of Science and Technology (KNUST-LISA), Kumasi-Ghana

International Journal of Financial Engineering (IJFE), 2022, vol. 09, issue 04, 1-30

Abstract: In most financial markets, prices for long-maturity derivatives are not readily available due to illiquidity. This reality is particularly common in bond markets, as it is very challenging to model prices consistently—for medium-to-long-term bonds under a single specification of the underlying interest rate process. We develop a bond market state-space model that incorporates uncertainty in the underlying interest rate process parameters. Our state-space representation, coupled with the complementary Kalman filtering, provides a modeling configuration that permits for liquidity risk management and pricing that is designed in a consistent fashion for both medium- and long-term bonds. As an example, we constructed a state-space bond market modeling system formulated on the two-factor Vasicek interest rate model. Wherein, the interest rate model is subject to noise for medium-to-long-term bond maturities and follows an unobservable process. We demonstrate our Kalman filter algorithm using the observed United States (US) 10 year bond yield data.

Keywords: Infinite horizon; partial observation; uncertainty; illiquidity; state-space representation; price consistency; bond market; Kalman filter (search for similar items in EconPapers)
JEL-codes: G12 G22 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S2424786322500244

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