Artikel
Use of adapted particle filters in SVJD models
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 un-adapted particle filter.
- Sprache
-
Englisch
- Erschienen in
-
Journal: European Financial and Accounting Journal ; ISSN: 1805-4846 ; Volume: 13 ; Year: 2018 ; Issue: 3 ; Pages: 5-20 ; Prague: University of Economics, Faculty of Finance and Accounting
- Klassifikation
-
Management
Bayesian Analysis: General
Semiparametric and Nonparametric Methods: General
Statistical Simulation Methods: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Thema
-
Particle Filters
Price Jumps
Stochastic Volatility
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Fičura, Milan
Witzany, Jiří
- Ereignis
-
Veröffentlichung
- (wer)
-
University of Economics, Faculty of Finance and Accounting
- (wo)
-
Prague
- (wann)
-
2018
- DOI
-
doi:10.18267/j.efaj.211
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:46 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Fičura, Milan
- Witzany, Jiří
- University of Economics, Faculty of Finance and Accounting
Entstanden
- 2018
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