SVI estimation of the implied volatility by Kalman filter.

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 th...

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Bibliographic Details
Main Authors: Burnos, Sergey, Ngow, ChaSing
Format: Others
Language:English
Published: Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) 2010
Subjects:
Kalman filter
SVI model
implied volatility
Mathematical statistics
Matematisk statistik
Applied mathematics
Tillämpad matematik
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-13949
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spelling ndltd-UPSALLA1-oai-DiVA.org-hh-139492013-01-08T13:28:00ZSVI estimation of the implied volatility by Kalman filter.engBurnos, SergeyNgow, ChaSingHögskolan 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)2010Kalman filterSVI modelimplied volatilityMathematical statisticsMatematisk statistikApplied mathematicsTillämpad matematikTo 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. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-13949application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic Kalman filter
SVI model
implied volatility
Mathematical statistics
Matematisk statistik
Applied mathematics
Tillämpad matematik
spellingShingle Kalman filter
SVI model
implied volatility
Mathematical statistics
Matematisk statistik
Applied mathematics
Tillämpad matematik
Burnos, Sergey
Ngow, ChaSing
SVI estimation of the implied volatility by Kalman filter.
description 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.
author Burnos, Sergey
Ngow, ChaSing
author_facet Burnos, Sergey
Ngow, ChaSing
author_sort Burnos, Sergey
title SVI estimation of the implied volatility by Kalman filter.
title_short SVI estimation of the implied volatility by Kalman filter.
title_full SVI estimation of the implied volatility by Kalman filter.
title_fullStr SVI estimation of the implied volatility by Kalman filter.
title_full_unstemmed SVI estimation of the implied volatility by Kalman filter.
title_sort svi estimation of the implied volatility by kalman filter.
publisher Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE)
publishDate 2010
url http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-13949
work_keys_str_mv AT burnossergey sviestimationoftheimpliedvolatilitybykalmanfilter
AT ngowchasing sviestimationoftheimpliedvolatilitybykalmanfilter
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