Learning for infinitely divisible GARCH models in option pricing
Fumin Zhu, Michele Leonardo Bianchi, Young Shin Kim, Frank J. Fabozzi and Hengyu Wu
| Year of publication: |
2021
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|---|---|
| Authors: | Zhu, Fumin ; Bianchi, Michele Leonardo ; Kim, Young Shin ; Fabozzi, Frank J. ; Wu, Hengyu |
| Published in: |
Studies in nonlinear dynamics and econometrics : SNDE ; quarterly publ. electronically on the internet. - Berlin : De Gruyter, ISSN 1558-3708, ZDB-ID 1385261-9. - Vol. 25.2021, 3, p. 35-62
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| Subject: | Lévy-GARCH models | Markov chain Monte Carlo | option pricing | particle filtering | sequentialBayesian learning | Optionspreistheorie | Option pricing theory | Markov-Kette | Markov chain | Monte-Carlo-Simulation | Monte Carlo simulation | ARCH-Modell | ARCH model | Lernprozess | Learning process |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1515/snde-2019-0088 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://ebvufind01.dmz1.zbw.eu/10012594154