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Adaptive Filtering for Stochastic Volatility by Using Exact Sampling
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- Aihara, Shin Ichi (author)
- Tokyo University of Science, Japan
-
- Bagchi, Arunabha (author)
- University of Twente, Enschede, Netherlands
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- Saha, Saikat (author)
- Linköpings universitet,Reglerteknik,Tekniska högskolan,Sensor Fusion
- (creator_code:org_t)
- SciTePress - Science and and Technology Publications, 2013
- 2013
- English.
- In: 10th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2013). - : SciTePress - Science and and Technology Publications. - 9789898565709 ; , s. 326-335
- Conference paper (peer-reviewed)
Abstract
Subject headings
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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.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
Keyword
- Particle Filter
- Stochastic Volatility
- Parameter Identification
- Adaptive Filter
Publication and Content Type
- ref (subject category)
- kon (subject category)
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