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Fractional Fast Fourier Transform on Pricing Cruel Oil Options under Lévy Process

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Cyber Security Intelligence and Analytics (CSIA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1147))

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Abstract

In order to calibrate the complicated derivatives trading and options pricing efficiency, fractional fast Fourier transform was used to investigate the options pricing efficiency under Lévy process. The results show that comparing with the traditional Black-Sholes pricing model, the calibration errors have been reduced under Lévy process with the application of fractional fast Fourier transform. It is concluded that using the global minimization algorithms to calibrate the parameters make the pricing model more accurate which reduce the risk of misevaluation on options.

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Acknowledgements

This research was supported by Social Science Fund of Fujian Province, China (Grant number: FJ2018B075), Fuzhou University of International Studies and Trade (Grant number: FWKQJ201904).

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Authors and Affiliations

  1. Fuzhou University of International Studies and Trade, No. 28, Yuhuan Road, Shouzhan New District, Changle, Fuzhou, Fujian, China

    Ming Fang & Chiu-Lan Chang

Authors
  1. Ming Fang
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  2. Chiu-Lan Chang
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Corresponding author

Correspondence to Chiu-Lan Chang .

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Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Zheng Xu

  2. Department of Software Engineering and Game Development, Kennesaw State University, Marietta, GA, USA

    Reza M. Parizi

  3. Manchester Metropolitan University, Stockport, UK

    Mohammad Hammoudeh

  4. School of Engineering and Sciences, Tecnologico de Monterrey, Puebla, Mexico

    Octavio Loyola-González

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Fang, M., Chang, CL. (2020). Fractional Fast Fourier Transform on Pricing Cruel Oil Options under Lévy Process. In: Xu, Z., Parizi, R., Hammoudeh, M., Loyola-González, O. (eds) Cyber Security Intelligence and Analytics. CSIA 2020. Advances in Intelligent Systems and Computing, vol 1147. Springer, Cham. https://doi.org/10.1007/978-3-030-43309-3_34

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