SNP: A Program for Nonparametric Time Series Analysis

Authors: A. Ronald Gallant and George Tauchen

A. Ronald Gallant
Fuqua School of Business
Duke University
Box 90120, W425
Durham NC 27708-0120

Phone: 919-660-7927 (Duke-Fuqua)

George Tauchen
Department of Economics
Box 90097
Duke University
Durham NC 27708-0097

Phone 1-919-660-1812
FAX 1-919-684-8974

 Keywords: nonparametric time series, nonlinear time series, hermite series


FORTRAN: Code and a User's Guide as a PostScript file are available anonymous ftp from in the folder pub/arg/snp or from the Carnegie-Mellon University e-mail server by sending the e-mail message "send snp from general" to The code is provided at no charge for research purposes without warranty of any kind, expressed or implied.  The PC version is available within the ms-snp and pc-snp subdirectories under pub/arg/snp.

C++: A recently developed C++ version with a User's Guide as a PostScript file is available from  in the folder /pub/arg/snp_cpp.  The same discloser applies.


Gallant, A. Ronald, and George Tauchen (1989),"Seminonparametric Estimation of Conditionally Constrained Heterogeneous Processes: Asset Pricing Applications," Econometrica 57, 1091--1120.

Gallant, A. Ronald, and George Tauchen (1992), A Nonparametric Approach to Nonlinear Time Series Analysis: Estimation and Simulation," in David Brillinger, Peter Caines, John Geweke, Emanuel Parzen, Murray Rosenblatt, and Murad S. Taqqu eds. New Directions in Time Series Analysis, Part II. New York: Springer-Verlag, 71-92.


SNP is a method of nonparametric time series analysis. The method employs a Hermite polynomial series expansion to approximate the conditional density of a multivariate process. An appealing feature of this expansion is that it is a nonlinear nonparametric model that directly nests the Gaussian VAR model, the semiparametric VAR model, the Gaussian GARCH model, and the multivariate BEKK GARCH. The SNP model is fitted using conventional maximum likelihood together with a model selection strategy that determines the appropriate degree of the polynomial.

Languages: FORTRAN 77 and C++

Platforms: PCs under the free GNU g77 FORTRAN and Intel FORTRAN; UNIX/LINUX workstations including SUNs, HPs, and Intel-based boxes that run either LINUX or Solaris and support cpp and f77.

Support: For more information on the SNP package contact its authors: A. Ronald Gallant,, or George Tauchen,