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Lookback option pricing using the Fourier transform B-spline method

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  • Gareth G. Haslip
  • Vladimir K. Kaishev

Abstract

We derive a new, efficient closed-form formula approximating the price of discrete lookback options, whose underlying asset price is driven by an exponential semimartingale process, which includes ( jump) diffusions, L�vy models, affine processes and other models. The derivation of our pricing formula is based on inverting the Fourier transform using B-spline approximation theory. We give an error bound for our formula and establish its fast rate of convergence to the true price. Our method provides lookback option prices across the quantum of strike prices with greater efficiency than for a single strike price under existing methods. We provide an alternative proof to the Spitzer formula for the characteristic function of the maximum of a discretely observed stochastic process, which yields a numerically efficient algorithm based on convolutions. This is an important result which could have a wide range of applications in which the Spitzer formula is utilized. We illustrate the numerical efficiency of our algorithm by applying it in pricing fixed and floating discrete lookback options under Brownian motion, jump diffusion models, and the variance gamma process.

Suggested Citation

  • Gareth G. Haslip & Vladimir K. Kaishev, 2014. "Lookback option pricing using the Fourier transform B-spline method," Quantitative Finance, Taylor & Francis Journals, vol. 14(5), pages 789-803, May.
    • Handle: RePEc:taf:quantf:v:14:y:2014:i:5:p:789-803
    DOI: 10.1080/14697688.2014.882010
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    References listed on IDEAS

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    1. Alan L. Lewis, 2001. "A Simple Option Formula for General Jump-Diffusion and other Exponential Levy Processes," Related articles explevy, Finance Press.
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    Cited by:

    1. Gao, Yin & Jia, Lifen, 2021. "Pricing formulas of barrier-lookback option in uncertain financial markets," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    2. C. E. Phelan & D. Marazzina & G. Germano, 2020. "Pricing methods for α-quantile and perpetual early exercise options based on Spitzer identities," Quantitative Finance, Taylor & Francis Journals, vol. 20(6), pages 899-918, June.
    3. Hatem Ben‐Ameur & Rim Chérif & Bruno Rémillard, 2020. "Dynamic programming for valuing American options under a variance‐gamma process," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(10), pages 1548-1561, October.
    4. Svetlana Boyarchenko & Sergei Levendorskiu{i}, 2022. "Efficient inverse $Z$-transform and pricing barrier and lookback options with discrete monitoring," Papers 2207.02858, arXiv.org, revised Jul 2022.
    5. Svetlana Boyarchenko & Sergei Levendorskii, 2023. "Alternative models for FX, arbitrage opportunities and efficient pricing of double barrier options in L\'evy models," Papers 2312.03915, arXiv.org.
    6. Deswal, Komal & Kumar, Devendra, 2022. "Rannacher time-marching with orthogonal spline collocation method for retrieving the discontinuous behavior of hedging parameters," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    7. Svetlana Boyarchenko & Sergei Levendorskiu{i}, 2022. "Efficient evaluation of double-barrier options and joint cpdf of a L\'evy process and its two extrema," Papers 2211.07765, arXiv.org.

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