Flexible Modeling of Conditional Distributions Using Smooth Mixtures of Asymmetric Student T Densities

Riksbank Research Paper Series No. 64

Sveriges Riksbank Working Paper Series No. 233

24 Pages Posted: 4 Mar 2010 Last revised: 8 May 2010

See all articles by Feng Li

Feng Li

Central University of Finance and Economics (CUFE)

Mattias Villani

Sveriges Riksbank - Research Division; Stockholm University - Department of Statistics

Robert Kohn

University of New South Wales - School of Economics and School of Banking and Finance

Date Written: October 1, 2009

Abstract

A general model is proposed for flexibly estimating the density of a continuous response variable conditional on a possibly high-dimensional set of covariates. The model is a finite mixture of asymmetric student-t densities with covariate dependent mixture weights. The four parameters of the components, the mean, degrees of freedom, scale and skewness, are all modeled as functions of the covariates. Inference is Bayesian and the computation is carried out using Markov chain Monte Carlo simulation. To enable model parsimony, a variable selection prior is used in each set of covariates and among the covariates in the mixing weights. The model is used to analyse the distribution of daily stock market returns, and shown to more accurately forecast the distribution of returns than other widely used models for financial data.

Keywords: Bayesian Inference, Markov Chain Monte Carlo, Mixture of Experts, Variable Selection, Volatility Modeling

Suggested Citation

Li, Feng and Villani, Mattias and Kohn, Robert, Flexible Modeling of Conditional Distributions Using Smooth Mixtures of Asymmetric Student T Densities (October 1, 2009). Riksbank Research Paper Series No. 64. Available at SSRN: https://ssrn.com/abstract=1551195 or http://dx.doi.org/10.2139/ssrn.1551195

Feng Li (Contact Author)

Central University of Finance and Economics (CUFE) ( email )

39 South College Road
Haidian District
Beijing, Beijing 100081
China

HOME PAGE: http://feng.li/

Mattias Villani

Sveriges Riksbank - Research Division ( email )

S-103 37 Stockholm
Sweden

HOME PAGE: http://www.riksbank.com/research/villani

Stockholm University - Department of Statistics ( email )

Universitetsvägen 10
Stockholm, Stockholm SE-106 91
Sweden

HOME PAGE: http://www.riksbank.com/research/villani

Robert Kohn

University of New South Wales - School of Economics and School of Banking and Finance ( email )

Australian School of Business
Sydney NSW 2052, ACT 2600
Australia
+61 2 9385 2150 (Phone)

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