SVI estimation of the implied volatility by Kalman filter.
2010 (English)Independent thesis Advanced level (degree of Master (One Year)), 15 credits / 22,5 HE credits
Student thesis
Abstract [en]
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.
Place, publisher, year, edition, pages
2010. , p. 58
Keywords [en]
Kalman filter, SVI model, implied volatility
National Category
Probability Theory and Statistics Computational Mathematics
Identifiers
URN: urn:nbn:se:hh:diva-13949OAI: oai:DiVA.org:hh-13949DiVA, id: diva2:373504
Presentation
2010-06-04, Haldasalen, Halmstad University, Halmstad, 12:30 (English)
Uppsok
Physics, Chemistry, Mathematics
Supervisors
Examiners
2010-12-022010-11-302010-12-02Bibliographically approved