Abstract. We study local asymptotic properties of likelihood ratios of certain Heston models. We distinguish three cases: subcritical, critical and supercritical models. For the drift parameters, local asymptotic normality is proved in the subcritical case, only local asymptotic quadraticity is shown in the critical case, while in the supercritical case not even local asymptotic quadraticity holds. For certain submodels, local asymptotic normality is proved in the critical case, and local asymptotic mixed normality is shown in the supercritical case. As a consequence, asymptotically optimal (randomized) tests are constructed in cases of local asymptotic normality. Moreover, local asymptotic minimax bound, and hence, asymptotic efficiency in the convolution theorem sense are concluded for the maximum likelihood estimators in cases of local asymptotic mixed normality.

DOI: 10.14232/actasm-016-506-x

AMS Subject Classification (1991): 60H10, 91G70, 60F05, 62F12

Keyword(s): Heston model, local asymptotic quadricity, local asymptotic mixed normality, local asymptotic normality, asymptotically optimal tests, local asymptotic minimax bound for estimators, asymptotic efficiency in the convolution theorem sense

Received February 1, 2016, and in final form August 17, 2016. (Registered under 6/2016.)