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  • 标题:Optimal estimation of the supremum and occupation times of a self-similar Lévy process
  • 本地全文:下载
  • 作者:Jevgenijs Ivanovs ; Mark Podolskij
  • 期刊名称:Electronic Journal of Statistics
  • 印刷版ISSN:1935-7524
  • 出版年度:2022
  • 卷号:16
  • 期号:1
  • 页码:892-934
  • DOI:10.1214/21-EJS1928
  • 语种:English
  • 出版社:Institute of Mathematical Statistics
  • 摘要:In this paper we present new theoretical results on optimal estimation of certain random quantities based on high frequency observations of a Lévy process. More specifically, we investigate the asymptotic theory for the conditional mean and conditional median estimators of the supremum/infimum of a linear Brownian motion and a strictly stable Lévy process. Another contribution of our article is the conditional mean estimation of the local time and the occupation time of a linear Brownian motion. We demonstrate that the new estimators are considerably more efficient compared to the classical estimators studied in e.g. [6, 14, 29, 30, 38]. Furthermore, we discuss pre-estimation of the parameters of the underlying models, which is required for practical implementation of the proposed statistics.
  • 关键词:60F05;60G18;60G51;62G15;62G20;62M05;Conditioning to stay positive;Lévy processes;Local time;occupation time;optimal estimation;self-similarity;supremum;weak limit theorems
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