Finite Gaussian Mixture Approximations to Analytically Intractable Density Kernels

Computational Economics, Vol. 53(3), 2019

24 Pages Posted: 4 Jul 2016 Last revised: 21 Mar 2019

See all articles by Natalia Khorunzhina

Natalia Khorunzhina

Copenhagen Business School - Faculty of Economics and Business Administration

Jean-Francois Richard

University of Pittsburgh - Department of Economics

Date Written: June 29, 2016

Abstract

The objective of the paper is that of constructing finite Gaussian mixture approximations to analytically intractable density kernels. The proposed method is adaptive in that terms are added one at the time and the mixture is fully re-optimized at each step using a distance measure that approximates the corresponding importance sampling variance. All functions of interest are evaluated under Gaussian quadrature rules. Examples include a sequential (filtering) evaluation of the likelihood function of a stochastic volatility model where all relevant densities (filtering, predictive and likelihood) are closely approximated by mixtures.

Keywords: Finite mixture, Distance measure, Gaussian quadrature, Importance sampling, Adaptive algorithm, Stochastic volatility, Density kernel

JEL Classification: C11, C63

Suggested Citation

Khorunzhina, Natalia and Richard, Jean-Francois, Finite Gaussian Mixture Approximations to Analytically Intractable Density Kernels (June 29, 2016). Computational Economics, Vol. 53(3), 2019, Available at SSRN: https://ssrn.com/abstract=2803514 or http://dx.doi.org/10.2139/ssrn.2803514

Natalia Khorunzhina (Contact Author)

Copenhagen Business School - Faculty of Economics and Business Administration ( email )

Frederiksberg, DK - 2000
Denmark

HOME PAGE: http://sf.cbs.dk/nk

Jean-Francois Richard

University of Pittsburgh - Department of Economics ( email )

4901 Wesley Posvar Hall
230 South Bouquet Street
Pittsburgh, PA 15260
United States
412-648-1750 (Phone)

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
40
Abstract Views
482
PlumX Metrics