Which is the right option for Indian market: Gaussian, normal inverse Gaussian, or Tsallis?

Autor: Prasenjit Chakrabarti, Kousik Guhathakurata
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: IIMB Management Review, Vol 31, Iss 3, Pp 238-249 (2019)
Druh dokumentu: article
ISSN: 0970-3896
DOI: 10.1016/j.iimb.2019.03.011
Popis: This paper models Nifty spot prices using frameworks based on Gaussian distribution (geometric Brownian motion) and non-Gaussian distributions, viz. normal inverse Gaussian (NIG), and Tsallis distributions, to investigate which model best captures the underlying dynamics. The simulation results suggest that Tsallis outperforms the Gaussian model and NIG in predicting the Nifty spot prices. Amongst the non-Gaussian models, Tsallis better captures the behaviour of Nifty spot prices than NIG distribution. Based on our findings, we conclude that non-Gaussian option pricing frameworks to price Nifty options are likely to give better results over the traditional class of Gaussian models. Keywords: Geometric Brownian motion, Normal inverse Gaussian distribution, Tsallis distribution, Stock index
Databáze: Directory of Open Access Journals