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Accelerating FHS Option Pricing Under Linear GARCH

Author

Listed:
  • Haibin Xie

    (University of International Business and Economics)

  • Xinyu Wu

    (Anhui University of Finance and Economics)

  • Pengying Fan

    (Beijing Technology and Business University)

Abstract

We propose an analytical approximation technique to accelerate the filtered historical simulation (FHS) option pricing method. The analytical approximation technique has at least two advantages over the FHS method: first, it does not suffer from random sampling error as it needs no simulation; second, it is fast in calculating option price as it is analytical. Simulation results indicate our technique approximates the FHS method quite well, and empirical results show that our technique has very good option pricing performance.

Suggested Citation

  • Haibin Xie & Xinyu Wu & Pengying Fan, 2021. "Accelerating FHS Option Pricing Under Linear GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 395-411, August.
    • Handle: RePEc:kap:compec:v:58:y:2021:i:2:d:10.1007_s10614-020-10033-1
    DOI: 10.1007/s10614-020-10033-1
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    References listed on IDEAS

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