We study asymptotic properties of maximum likelihood estimators of drift parameters for a jump-type Heston model based on continuous time observations  . 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  . We also present some numerical illustrations to confirm our results.
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.
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, 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)
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. It turns out that the volatility of the price process is a measurable function of the price process