Search: id:"swepub:oai:DiVA.org:liu-103985" >
Adaptive Filtering ...
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Aihara, Shin IchiTokyo University of Science, Japan
(author)
Adaptive Filtering for Stochastic Volatility by Using Exact Sampling
- Article/chapterEnglish2013
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SciTePress - Science and and Technology Publications,2013
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LIBRIS-ID:oai:DiVA.org:liu-103985
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https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-103985URI
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https://doi.org/10.5220/0004454703260335DOI
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:kon swepub-publicationtype
Notes
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We study the sequential identification problem for Bates stochastic volatility model, which is widely used as the model of a stock in finance. By using the exact simulation method, a particle filter for estimating stochastic volatility is constructed. The systems parameters are sequentially estimated with the aid of parallel filtering algorithm. To improve the estimation performance for unknown parameters, the new resampling procedure is proposed. Simulation studies for checking the feasibility of the developed scheme are demonstrated.
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Bagchi, ArunabhaUniversity of Twente, Enschede, Netherlands
(author)
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Saha, SaikatLinköpings universitet,Reglerteknik,Tekniska högskolan,Sensor Fusion(Swepub:liu)saisa77
(author)
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Tokyo University of Science, JapanUniversity of Twente, Enschede, Netherlands
(creator_code:org_t)
Related titles
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In:10th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2013): SciTePress - Science and and Technology Publications, s. 326-3359789898565709
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