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Use of Adapted Particle Filters in SVJD Models

Milan Ficura () and Jiří Witzany ()

European Financial and Accounting Journal, 2018, vol. 2018, issue 3, 5-20

Abstract: Particle Filter algorithms for filtering latent states (volatility and jumps) of Stochastic-Volatility Jump-Diffusion (SVJD) models are being explained. Three versions of the SIR particle filter with adapted proposal distributions to the jump occurrences, jump sizes, and both are derived and their performance is compared in a simulation study to the un-adapted particle filter. The filter adapted to both the jump occurrences and jump sizes achieves the best performance, followed in their respective order by the filter adapted only to the jump occurrences and the filter adapted only to the jump sizes. All adapted particle filters outperformed the unadapted particle filter.

Keywords: Particle Filters; Stochastic Volatility; Price Jumps (search for similar items in EconPapers)
JEL-codes: C11 C14 C15 C22 G1 (search for similar items in EconPapers)
Date: 2018
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DOI: 10.18267/j.efaj.211

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