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Title
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Towards a Δ-Gamma Sato multivariate model
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Author
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Abstract
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| The increased trading in multi-name financial products has paved the way for the use of multivariate models that are at once computationally tractable and flexible enough to mimic the stylized facts of asset log-returns and of their dependence structure. In this paper we propose a new multivariate Lévy model, the so-called Δ-Gamma model, where the log-price gains and losses are modeled by separate multivariate Gamma processes, each containing a common and an idiosyncratic component. Furthermore, we extend this multivariate model to the Sato setting, allowing for a moment term structure that is more in line with empirical evidence. We calibrate the two models on single-name option price surfaces and market implied correlations and we show how the Δ-Gamma Sato model outperforms its Lévy counterpart, especially during periods of market turmoil. The numerical study also reveals the advantages of these new types of multivariate models, compared to a multivariate VG model. |
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Language
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English
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Source (journal)
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Review of derivatives research. - Boston, Mass.
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Publication
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Boston, Mass.
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2020
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ISSN
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1380-6645
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DOI
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10.1007/S11147-019-09155-Y
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Volume/pages
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23
:1
(2020)
, p. 1-39
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ISI
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000522207200001
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Full text (Publisher's DOI)
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Full text (open access)
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Full text (publisher's version - intranet only)
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