Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox

Tinbergen Institute Discussion Paper 13-055/III

28 Pages Posted: 4 May 2015

See all articles by Roberto Casarin

Roberto Casarin

University Ca' Foscari of Venice - Department of Economics

Stefano Grassi

Aarhus University - CREATES

Francesco Ravazzolo

Free University of Bolzano

H. K. van Dijk

Tinbergen Institute; Econometric Institute

Multiple version iconThere are 3 versions of this paper

Date Written: April 9, 2013

Abstract

This paper presents the Matlab package DeCo (Density Combination) which is based on the paper by Billio et al. (2013) where a constructive Bayesian approach is presented for combining predictive densities originating from different models or other sources of information. The combination weights are time-varying and may depend on past predictive forecasting performances and other learning mechanisms. The core algorithm is the function DeCo which applies banks of parallel Sequential Monte Carlo algorithms to filter the time-varying combination weights. The DeCo procedure has been implemented both for standard CPU computing and for Graphical Process Unit (GPU) parallel computing. For the GPU implementation we use the Matlab parallel computing toolbox and show how to use General Purposes GPU computing almost effortless. This GPU implementation comes with a speed up of the execution time up to seventy times compared to a standard CPU Matlab implementation on a multicore CPU. We show the use of the package and the computational gain of the GPU version, through some simulation experiments and empirical applications.

Keywords: Density Forecast Combination, Sequential Monte Carlo, Parallel Computing, GPU, Matlab

JEL Classification: C11, C15, C53, E37

Suggested Citation

Casarin, Roberto and Grassi, Stefano and Ravazzolo, Francesco and van Dijk, Herman K., Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox (April 9, 2013). Tinbergen Institute Discussion Paper 13-055/III. Available at SSRN: https://ssrn.com/abstract=2247332 or http://dx.doi.org/10.2139/ssrn.2247332

Roberto Casarin (Contact Author)

University Ca' Foscari of Venice - Department of Economics ( email )

San Giobbe 873/b
Venice, 30121
Italy
+39 030.298.91.49 (Phone)
+39 030.298.88.37 (Fax)

HOME PAGE: http://venus.unive.it/r.casarin/

Stefano Grassi

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Francesco Ravazzolo

Free University of Bolzano ( email )

Bolzano
Italy

Herman K. Van Dijk

Tinbergen Institute ( email )

Gustav Mahlerplein 117
Burg. Oudlaan 50
Amsterdam/Rotterdam, 1082 MS
Netherlands
+31104088955 (Phone)
+31104089031 (Fax)

HOME PAGE: http://people.few.eur.nl/hkvandijk/

Econometric Institute ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands
+31 10 4088955 (Phone)
+31 10 4527746 (Fax)

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