Estimating MA Parameters Through Factorization of the Autocovariance Matrix and an Ma‐Sieve Bootstrap

14 Pages Posted: 16 Apr 2018

See all articles by Timothy L. McMurry

Timothy L. McMurry

DePaul University

Dimitris N. Politis

University of California, San Diego (UCSD) - Department of Mathematics

Date Written: May 2018

Abstract

A new method to estimate the moving‐average (MA) coefficients of a stationary time series is proposed. The new approach is based on the modified Cholesky factorization of a consistent estimator of the autocovariance matrix. Convergence rates are established, and the new estimates are used to implement an MA‐type sieve bootstrap. Finite‐sample simulations corroborate the good performance of the proposed methodology.

Keywords: ARMA models, sieve bootstrap, Wold representation

Suggested Citation

McMurry, Timothy L. and Politis, Dimitris, Estimating MA Parameters Through Factorization of the Autocovariance Matrix and an Ma‐Sieve Bootstrap (May 2018). Journal of Time Series Analysis, Vol. 39, Issue 3, pp. 433-446, 2018, Available at SSRN: https://ssrn.com/abstract=3163180 or http://dx.doi.org/10.1111/jtsa.12296

Timothy L. McMurry (Contact Author)

DePaul University ( email )

1 East Jackson Blvd.
Chicago, IL 60604
United States

Dimitris Politis

University of California, San Diego (UCSD) - Department of Mathematics ( email )

9500 Gilman Drive
La Jolla, CA 92093-0112
United States
858-534-5861 (Phone)
858-534-5273 (Fax)

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