Pseudo Maximum Likelihood and Moments Estimators for Some Ergodic Diffusions

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

When \(\left (X_t\right )_{t\geq 0}\) is an ergodic process, the density function of Xt converges to some invariant density as t →∞. We will compute and study some asymptotic properties of pseudo moments estimators obtained from this invariant density, for a specific class of ergodic processes. In this class of processes we can find the Cox-Ingersoll & Ross or Dixit & Pindyck processes, among others. A comparative study of the proposed estimators with the usual estimators obtained from discrete approximations of the likelihood function will be carried out.
Original languageEnglish
Title of host publicationRecent Studies on Risk Analysis and Statistical Modeling
EditorsT. Oliveira, C. Kitsos, A. Oliveira, L. Grilo
Place of PublicationCham
PublisherSpringer International Publishing
Pages335-343
ISBN (Electronic)978-3-319-76605-8
ISBN (Print)978-3-319-76604-1
DOIs
Publication statusPublished - 23 Aug 2018

Publication series

NameContributions to Statistics
PublisherSpringer International Publishing
ISSN (Print)1431-1968

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  • Cite this

    Mota, P., & Esquível, M. L. (2018). Pseudo Maximum Likelihood and Moments Estimators for Some Ergodic Diffusions. In T. Oliveira, C. Kitsos, A. Oliveira, & L. Grilo (Eds.), Recent Studies on Risk Analysis and Statistical Modeling (pp. 335-343). (Contributions to Statistics). Springer International Publishing. https://doi.org/10.1007/978-3-319-76605-8_24