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SVI estimation of the implied volatility by Kalman filter.

To understand and model the dynamics of the implied volatility smile is essential for trading, pricing and risk management portfolio. We suggest a  linear Kalman filter for updating of the Stochastic Volatility Inspired (SVI) model of the volatility. From a risk management perspective we generate the 1-day ahead forecast of profit and loss (P\&L) of option portfolios. We compare the estimation of the implied volatility using the SVI model with the cubic polynomial model. We find that the SVI Kalman filter has outperformed the  others.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hh-13949
Date January 2010
CreatorsBurnos, Sergey, Ngow, ChaSing
PublisherHögskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Högskolan i Halmstad, Tillämpad matematik och fysik (MPE-lab), Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Högskolan i Halmstad, Tillämpad matematik och fysik (MPE-lab)
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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