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

Abstract

This paper is concerned with the parameter estimation problem for discrete observed Chan-Karoli-Longstaff-Saunders model driven by small Levy 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 e → 0 and n → ∞ simultaneously. The simulation is made to verify the effectiveness of the estimators.