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Generalized Mean-Reverting 4/2 Factor Model

Author

Listed:
  • Yuyang Cheng

    (Department of Statistical and Actuarial Sciences, Western University, London, ON N6A 3K7, Canada
    These authors contributed equally to this work.)

  • Marcos Escobar-Anel

    (Department of Statistical and Actuarial Sciences, Western University, London, ON N6A 3K7, Canada
    These authors contributed equally to this work.)

  • Zhenxian Gong

    (Department of Statistical and Actuarial Sciences, Western University, London, ON N6A 3K7, Canada
    These authors contributed equally to this work.)

Abstract

This paper proposes and investigates a multivariate 4/2 Factor Model. The name 4/2 comes from the superposition of a CIR term and a 3/2-model component. Our model goes multidimensional along the lines of a principal component and factor covariance decomposition. We find conditions for well-defined changes of measure and we also find two key characteristic functions in closed-form, which help with pricing and risk measure calculations. In a numerical example, we demonstrate the significant impact of the newly added 3/2 component (parameter b ) and the common factor ( a ), both with respect to changes on the implied volatility surface (up to 100%) and on two risk measures: value at risk and expected shortfall where an increase of up to 29% was detected.

Suggested Citation

  • Yuyang Cheng & Marcos Escobar-Anel & Zhenxian Gong, 2019. "Generalized Mean-Reverting 4/2 Factor Model," JRFM, MDPI, vol. 12(4), pages 1-21, October.
    • Handle: RePEc:gam:jjrfmx:v:12:y:2019:i:4:p:159-:d:274079
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    References listed on IDEAS

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    Cited by:

    1. Alessandro Gnoatto & Martino Grasselli & Eckhard Platen, 2022. "Calibration to FX triangles of the 4/2 model under the benchmark approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(1), pages 1-34, June.
    2. Lars Stentoft, 2020. "Computational Finance," JRFM, MDPI, vol. 13(7), pages 1-4, July.

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