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Simulation based calibration using extended balanced augmented empirical likelihood

Nguyen, Minh Khoa and Phelps, Steve and Ng, Wing Lon (2014) 'Simulation based calibration using extended balanced augmented empirical likelihood.' Statistics and Computing, 25 (6). pp. 1093-1112. ISSN 0960-3174

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Abstract

This paper introduces an extension of the balanced augmented empirical likelihood (eBAEL) method for calibrating simulation models. We illustrate the efficiency of our method in two simulation studies, where we calibrate moments of different distributions and parameters of a geometric Brownian motion process, comparing our approach against other simulation based methods. In these benchmark experiments we observe converging mean squared errors of the empirical likelihood approach. In fact, the results demonstrate that the eBAEL approach is able to provide the best mean squared errors for calibration and in particular is the most robust calibration method, particularly in the presence of noise.

Item Type: Article
Uncontrolled Keywords: Simulation based calibration; Empirical likelihood; Balance adjusted empirical likelihood; Unbiased estimation equation
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HG Finance
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of > Centre for Computational Finance and Economic Agents
Depositing User: Jim Jamieson
Date Deposited: 23 Jul 2015 14:48
Last Modified: 16 Oct 2015 13:24
URI: http://repository.essex.ac.uk/id/eprint/14438

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