Asymptotic behavior of maximum likelihood estimators for a jump-type Heston model

Matyas Barczy, Mohamed Ben Alaya, Ahmed Kebaier and Gyula Pap

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Abstract: We study asymptotic properties of maximum likelihood estimators of drift parameters for a jump-type Heston model based on continuous time observations, where the jump process can be any purely non-Gaussian L\'evy process of not necessarily bounded variation with a L\'evy measure concentrated on $(-1,\infty)$. We prove strong consistency and asymptotic normality for all admissible parameter values except one, where we show only weak consistency and mixed normal (but non-normal) asymptotic behavior. It turns out that the volatility of the price process is a measurable function of the price process. We also present some numerical illustrations to confirm our results.

Date: 2015-09, Revised 2018-05
New Economics Papers: this item is included in nep-ecm
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Published in Journal of Statistical Planning and Inference 198, (2019), 139-164

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1509.08869

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