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Filtering for Stochastic Volatility by Using Exact Sampling and Application to Term Structure Modeling
Tokyo University of Science Suwa, Japan.
University of Twente, Netherlands.
Linköping University, Department of Electrical Engineering. Linköping University, Faculty of Science & Engineering.
2015 (English)In: INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, Springer Science Business Media , 2015, Vol. 325, 329-348 p.Conference paper (Refereed)
Abstract [en]

The Bates stochastic volatility model is widely used in the finance problem and the sequential parameter estimation problem becomes important. By using the exact simulation technique, a particle filter for estimating stochastic volatility is constructed. The system parameters are sequentially estimated with the aid of parallel filtering algorithm with the new resampling procedure. The proposed filtering procedure is also applied to the modeling of the term structure dynamics. Simulation studies for checking the feasibility of the developed scheme are demonstrated.

Place, publisher, year, edition, pages
Springer Science Business Media , 2015. Vol. 325, 329-348 p.
Keyword [en]
Particle filter; Stochastic volatility; Parameter identification; Adaptive filter
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:liu:diva-120757DOI: 10.1007/978-3-319-10891-9_19ISI: 000358611400019ISBN: 978-3-319-10891-9; 978-3-319-10890-2OAI: diva2:848157
10th International Conference on Informatics in Control, Automation and Robotics (ICINCO)
Available from: 2015-08-24 Created: 2015-08-24 Last updated: 2015-08-24

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Saha, Saikat
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Department of Electrical EngineeringFaculty of Science & Engineering
Electrical Engineering, Electronic Engineering, Information Engineering

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ReferencesLink to record
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