Asymptotic behavior of maximum likelihood estimators for a jump-type Heston model - Archive ouverte HAL Access content directly
Journal Articles Journal of Statistical Planning and Inference Year : 2019

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

Matyas Barczy
• Function : Author
Mohamed Ben Alaya
• Function : Author
Ahmed Kebaier
• Function : Author
• PersonId : 897096
Gyula Pap
• Function : Author

#### 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.

### Dates and versions

hal-02332410 , version 1 (24-10-2019)

### Identifiers

• HAL Id : hal-02332410 , version 1
• ARXIV :
• DOI :

### Cite

Matyas Barczy, Mohamed Ben Alaya, Ahmed Kebaier, Gyula Pap. Asymptotic behavior of maximum likelihood estimators for a jump-type Heston model. Journal of Statistical Planning and Inference, 2019, 198, pp.139-164. ⟨10.1016/j.jspi.2018.02.002⟩. ⟨hal-02332410⟩

### Export

BibTeX TEI Dublin Core DC Terms EndNote Datacite

48 View