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DC poleHodnotaJazyk
dc.contributor.authorPospíšil, Jan
dc.contributor.authorSobotka, Tomáš
dc.contributor.authorZiegler, Philippe
dc.date.accessioned2019-12-09T11:00:17Z-
dc.date.available2019-12-09T11:00:17Z-
dc.date.issued2019
dc.identifier.citationPOSPÍŠIL, J., SOBOTKA, T., ZIEGLER, P. Robustness and sensitivity analyses for stochastic volatility models under uncertain data structure. Empirical Economics, 2019, roč. 57, č. 6, s. 1935-1958. ISSN 0377-7332.en
dc.identifier.issn0377-7332
dc.identifier.uri2-s2.0-85052079492
dc.identifier.urihttp://hdl.handle.net/11025/36056
dc.format24 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherPhysica-Verlagen
dc.relation.ispartofseriesEmpirical Economicsen
dc.rights© Physica-Verlagen
dc.titleRobustness and sensitivity analyses for stochastic volatility models under uncertain data structureen
dc.typečlánekcs
dc.typepreprintcs
dc.typepostprintcs
dc.typearticleen
dc.typepreprinten
dc.typepostprinten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.type.versionacceptedVersionen
dc.type.versiondraften
dc.description.abstract-translatedIn this paper, we perform robustness and sensitivity analysis of several continuous-time stochastic volatility (SV) models with respect to the process of market calibration. The analyses should validate the hypothesis on importance of the jump part in the underlying model dynamics. Also an impact of the long memory parameter is measured for the approximative fractional SV model (FSV). For the first time, the robustness of calibrated models is measured using bootstrapping methods on market data and Monte Carlo filtering techniques. In contrast to several other sensitivity analysis approaches for SV models, the newly proposed methodology does not require independence of calibrated parameters - an assumption that is typically not satisfied in practice. Empirical study is performed on a data set of Apple Inc. equity options traded in four different days in April and May 2015. In particular, the results for Heston, Bates and approximative FSV models are provided.en
dc.subject.translatedrobustness analysisen
dc.subject.translatedsensitivity analysisen
dc.subject.translatedstochastic volatility modelsen
dc.subject.translatedbootstrappingen
dc.subject.translatedMonte Carlo filteringen
dc.identifier.doi10.1007/s00181-018-1535-3
dc.type.statusPeer-revieweden
dc.identifier.document-number494824300006
dc.identifier.obd43916434
dc.project.IDGA14-11559S/Analýza frakcionálních modelů stochastické volatility a jejich implementace v griducs
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