Calibration for Weak Variance-Alpha-Gamma Processes

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dc.contributor.authorBuchmann, Boris
dc.contributor.authorLu, Kevin
dc.contributor.authorMadan, Dilip B.
dc.date.accessioned2021-06-09T04:25:06Z
dc.date.issued2018-08-23
dc.description.abstractThe weak variance-alpha-gamma process is a multivariate Lévy process constructed by weakly subordinating Brownian motion, possibly with correlated components with an alpha-gamma subordinator. It generalises the variance-alpha-gamma process of Semeraro constructed by traditional subordination. We compare three calibration methods for the weak variance-alpha-gamma process, method of moments, maximum likelihood estimation (MLE) and digital moment estimation (DME). We derive a condition for Fourier invertibility needed to apply MLE and show in our simulations that MLE produces a better fit when this condition holds, while DME produces a better fit when it is violated. We also find that the weak variance-alpha-gamma process exhibits a wider range of dependence and produces a significantly better fit than the variance-alpha-gamma process on a S&P500-FTSE100 data set, and that DME produces the best fit in this situation.en_AU
dc.description.sponsorshipB. Buchmann's research was supported by ARC grant DP160104737. K. Lu's research was supported by an Australian Government Research Training Program Scholarship.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.citationBuchmann, B., Lu, K.W. & Madan, D.B. Calibration for Weak Variance-Alpha-Gamma Processes. Methodol Comput Appl Probab 21, 1151–1164 (2019). https://doi.org/10.1007/s11009-018-9655-yen_AU
dc.identifier.issn1387-5841en_AU
dc.identifier.urihttp://hdl.handle.net/1885/236910
dc.language.isoen_AUen_AU
dc.provenancehttps://v2.sherpa.ac.uk/id/publication/11802..."Author accepted manuscript can be made open access on institutional repository after 12 month embargo" from SHERPA/RoMEO site (as at 17.6.2021).
dc.publisherKluwer Academic Publishersen_AU
dc.relationhttp://purl.org/au-research/grants/arc/DP160104737en_AU
dc.rights© 2018 Springer Science+Business Media, LLC, part of Springer Natureen_AU
dc.sourceMethodology and Computing in Applied Probabilityen_AU
dc.subjectBrownian motionen_AU
dc.subjectGamma processen_AU
dc.subjectLevy processen_AU
dc.subjectSubordinationen_AU
dc.subjectVariance-Gammaen_AU
dc.subjectVariance-Alpha-Gammaen_AU
dc.subjectSelf-Decomposabilityen_AU
dc.subjectLog-Returnen_AU
dc.subjectMethod of momentsen_AU
dc.subjectMaximum likelihood estimationen_AU
dc.subjectDigital moment estimationen_AU
dc.titleCalibration for Weak Variance-Alpha-Gamma Processesen_AU
dc.typeJournal articleen_AU
dcterms.accessRightsOpen Access
local.bibliographicCitation.issue4en_AU
local.bibliographicCitation.lastpage1164en_AU
local.bibliographicCitation.startpage1151en_AU
local.contributor.affiliationBuchmann, Boris, Research School of Finance, Actuarial Studies and Statistics, ANUen_AU
local.contributor.affiliationLu, Kevin, Mathematical Sciences Institute, ANUen_AU
local.contributor.affiliationMadan, Dilip B., University of Marylanden_AU
local.contributor.authoremailu4164354@anu.edu.auen_AU
local.contributor.authoruidBuchmann, Boris, u4164354en_AU
local.contributor.authoruidLu, Kevin, u5119413en_AU
local.identifier.absfor010404 - Probability Theoryen_AU
local.identifier.ariespublicationu1027566xPUB119en_AU
local.identifier.citationvolume21en_AU
local.identifier.doi10.1007/s11009-018-9655-yen_AU
local.identifier.uidSubmittedByu5031974en_AU
local.publisher.urlhttps://link.springer.com/en_AU
local.type.statusAccepted Versionen_AU

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