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Numerical Analysis on Quadratic Hedging Strategies for Normal Inverse Gaussian Models

  • Takuji AraiEmail author
  • Yuto Imai
  • Ryo Nakashima
Chapter
Part of the Advances in Mathematical Economics book series (MATHECON, volume 22)

Abstract

The authors aim to develop numerical schemes of the two representative quadratic hedging strategies: locally risk-minimizing and mean-variance hedging strategies, for models whose asset price process is given by the exponential of a normal inverse Gaussian process, using the results of Arai et al. (Int J Theor Appl Financ 19:1650008, 2016) and Arai and Imai (A closed-form representation of mean-variance hedging for additive processes via Malliavin calculus, preprint. Available at https://arxiv.org/abs/1702.07556). Here normal inverse Gaussian process is a framework of Lévy processes that frequently appeared in financial literature. In addition, some numerical results are also introduced.

Keywords

Local risk minimization Mean-variance hedging Normal inverse Gaussian process Fast Fourier transform 

Notes

Acknowledgements

This work was supported by JSPS KAKENHI Grant Numbers 15K04936 and 17K13764.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of EconomicsKeio UniversityTokyoJapan
  2. 2.Graduate School of ManagementTokyo Metropolitan UniversityTokyoJapan
  3. 3.Power Solutions Inc.TokyoJapan

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