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

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dc.contributor.author Chakrabarti, Prasenjit.
dc.contributor.author Guhathakurata, Kousik.
dc.date.accessioned 2020-02-04T05:35:46Z
dc.date.available 2020-02-04T05:35:46Z
dc.date.issued 2019-09
dc.identifier.citation Chakrabarti, P., & Guhathakurata, K. (2019). Which is the right option for the Indian market: Gaussian, normal inverse Gaussian, or Tsallis?. IIMB Management Review, 31(3), 238-249. en_US
dc.identifier.issn 0970-3896
dc.identifier.uri http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/608
dc.description.abstract 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. en_US
dc.language.iso en en_US
dc.publisher IIMB Management Review en_US
dc.subject Geometric brownian motion en_US
dc.subject Normal inverse Gaussian distribution en_US
dc.subject Tsallis distribution en_US
dc.subject Stock index en_US
dc.subject IIM Ranchi en_US
dc.title Which is the right option for Indian market: Gaussian, normal inverse Gaussian, or Tsallis? en_US
dc.type Article en_US
dc.volume 31 en_US
dc.issue 3 en_US


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