Numerical analysis on quadratic hedging strategies for normal inverse Gaussian models

Takuji Arai, Yuto Imai, Ryo Nakashimax

Research output: Contribution to journalArticlepeer-review

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. [2], and Arai and Imai [1]. Here normal inverse Gaussian process is a framework of Lévy processes frequently appeared in financial literature. In addition, some numerical results are also introduced.

Original languageEnglish
JournalUnknown Journal
Publication statusPublished - 2018 Jan 17

Keywords

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

ASJC Scopus subject areas

  • General

Fingerprint Dive into the research topics of 'Numerical analysis on quadratic hedging strategies for normal inverse Gaussian models'. Together they form a unique fingerprint.

Cite this