Title: Parameter estimation for Chan-Karoli-Longstaff-Saunders model driven by small Lévy noises from discrete observations

Authors: Chao Wei

Addresses: School of Mathematics and Statistics, Anyang Normal University, Anyang 455000, China

Abstract: This paper is concerned with the parameter estimation problem for discrete observed Chan-Karoli-Longstaff-Saunders model driven by small Lévy noises. The explicit formula of the least squares estimators are obtained and the estimation error is given. By using Cauchy-Schwarz inequality, Gronwall's inequality, Markov inequality and dominated convergence, the consistency of the least squares estimators are proved when a small dispersion coefficient ε → 0 and n → ∞ simultaneously. The simulation is made to verify the effectiveness of the estimators.

Keywords: Chan-Karoli-Longstaff-Saunders model; parameter estimation; small dispersion coefficient; simulation; Markov inequality; dominated convergence; Gronwall's inequality.

DOI: 10.1504/IJDSDE.2020.109109

International Journal of Dynamical Systems and Differential Equations, 2020 Vol.10 No.4, pp.373 - 382

Received: 06 Mar 2018
Accepted: 01 Dec 2018
Published online: 20 Aug 2020 *

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