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Impulse Control of Interest Rates

Author

Listed:
  • Daniel Mitchell

    (Engineering Systems and Design, Singapore University of Technology and Design, Singapore 138682)

  • Haolin Feng

    (Lingnan College, Sun Yat-Sen University, Guangzhou, China 510275)

  • Kumar Muthuraman

    (McCombs School of Business, University of Texas, Austin, Texas 78712)

Abstract

This paper examines the effect that a central bank's interventions have on longer term interest rate securities by examining a stochastic short rate process that can be controlled by the central bank. Rather than investigate the motivations for the intervention, we assume that the bank is able to quantify its preferences and tolerances for various rates. We allow for a very general class of stochastic processes for the short rate, and most of the popular models in literature fall within this class. Interventions are best modeled as impulse controls, which are very difficult to handle, even computationally, except in very special cases. Allowing interventions to be modeled by impulse controls, we develop a computational method and provide relevant convergence results. We also derive error bounds for intermediate iterations. Using this method, we solve for the central bank's optimal control policy and also study the effect of this on longer term interest rate securities using a change of measure. The method developed here can easily be applied to a very wide range of impulse control problems beyond the realm of interest rate models.

Suggested Citation

  • Daniel Mitchell & Haolin Feng & Kumar Muthuraman, 2014. "Impulse Control of Interest Rates," Operations Research, INFORMS, vol. 62(3), pages 602-615, June.
    • Handle: RePEc:inm:oropre:v:62:y:2014:i:3:p:602-615
    DOI: 10.1287/opre.2014.1270
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    References listed on IDEAS

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    Cited by:

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    5. Li, Haitao & Ye, Xiaoxia & Yu, Fan, 2020. "Unifying Gaussian dynamic term structure models from a Heath–Jarrow–Morton perspective," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1153-1167.
    6. Korn, Ralf & Melnyk, Yaroslav & Seifried, Frank Thomas, 2017. "Stochastic impulse control with regime-switching dynamics," European Journal of Operational Research, Elsevier, vol. 260(3), pages 1024-1042.
    7. Matteo Basei, 2018. "Optimal price management in retail energy markets: an impulse control problem with asymptotic estimates," Papers 1803.08166, arXiv.org, revised Mar 2019.
    8. Jinbiao Wu, 2019. "Optimal exchange rates management using stochastic impulse control for geometric Lévy processes," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(2), pages 257-280, April.

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