Increments of Normal Inverse Gaussian Process as Logarithmic Returns of Stock Price

Oskars Rubenis, Andrejs Matvejevs

Abstract


Normal inverse Gaussian (NIG) distribution is quite a new distribution introduced in 1997. This is distribution, which describes evolution of NIG process. It appears that in many cases NIG distribution describes log-returns of stock prices with a high accuracy. Unlike normal distribution, it has higher kurtosis, which is necessary to fit many historical returns. This gives the opportunity to construct precise algorithms for hedging risks of options. The aim of the present research is to evaluate how well NIG distribution can reproduce stock price dynamics and to illuminate future fields of application.

Keywords:
Normal inverse Gaussian distribution; normal inverse Gaussian process; log-returns; maximum likelihood estimation

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DOI: 10.7250/itms-2018-0015

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