A note on the asymptotic normality of the kernel deconvolution density estimator with logarithmic chi-square noise

Tools

Zu, Yang (2015) A note on the asymptotic normality of the kernel deconvolution density estimator with logarithmic chi-square noise. Econometrics, 3 (3). pp. 561-576. ISSN 2225-1146

Full text not available from this repository.

Official URL: http://www.mdpi.com/2225-1146/3/3/561

Abstract

This paper studies the asymptotic normality for the kernel deconvolution estimator when the noise distribution is logarithmic chi-square; both identical and independently distributed observations and strong mixing observations are considered. The dependent case of the result is applied to obtain the pointwise asymptotic distribution of the deconvolution volatility density estimator in discrete-time stochastic volatility models.

Item Type:	Article
RIS ID:	https://nottingham-repository.worktribe.com/output/756518
Keywords:	kernel deconvolution estimator; asymptotic normality; volatility density estimation
Schools/Departments:	University of Nottingham, UK > Faculty of Social Sciences > School of Economics
Identification Number:	10.3390/econometrics3030561
Depositing User:	Zu, Yang
Date Deposited:	13 Sep 2017 10:49
Last Modified:	04 May 2020 17:12
URI:	https://eprints.nottingham.ac.uk/id/eprint/45844

Actions (Archive Staff Only)

Edit View

LoginAdmin