Bayesian Nonparametric Forecast Pooling

40 Pages Posted: 13 Jul 2020

See all articles by Xin Jin

Xin Jin

Shanghai University of Finance and Economics - School of Economics

John M. Maheu

McMaster University - Michael G. DeGroote School of Business; RCEA

Qiao Yang

ShanghaiTech University - School of Entrepreneurship and Management

Date Written: July 11, 2020

Abstract

This paper introduces a new approach to forecast pooling methods based on a nonparametric prior for the weight vector combining predictive densities. The first approach places a Dirichlet process prior on the weight vector and generalizes the static linear pool. The second approach uses a hierarchical Dirichlet process prior to allow the weight vector to follow an infinite hidden Markov chain. This generalizes dynamic prediction pools to the nonparametric setting. We discuss efficient posterior simulation based on MCMC methods. Detailed applications to short-term interest rates, realized covariance matrices and asset pricing models show the nonparametric pool forecasts well.

Keywords: Prediction pools, Dirichlet process, Beam sampling, Infinite Markov switching, density forecast, short-term interest rates, realized covariance matrices

JEL Classification: C53, C32, C11, Q43

Suggested Citation

Jin, Xin and Maheu, John M. and Yang, Qiao, Bayesian Nonparametric Forecast Pooling (July 11, 2020). ShanghaiTech SEM Working Paper No. 2020-008, Available at SSRN: https://ssrn.com/abstract=3649934 or http://dx.doi.org/10.2139/ssrn.3649934

Xin Jin

Shanghai University of Finance and Economics - School of Economics ( email )

777 Guoding Road
Shanghai, 200433
China

John M. Maheu

McMaster University - Michael G. DeGroote School of Business ( email )

1280 Main Street West
Hamilton, Ontario L8S 4M4
Canada

HOME PAGE: http://profs.degroote.mcmaster.ca/ads/maheujm/

RCEA

Via Patara, 3
Rimini (RN), RN 47900
Italy

HOME PAGE: http://www.rcfea.org/

Qiao Yang (Contact Author)

ShanghaiTech University - School of Entrepreneurship and Management ( email )

100 Haike Rd
Pudong Xinqu, Shanghai
China

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