On The Theory and Practice of Singular Spectrum Analysis Forecasting

Atikur Khan and Donald Poskitt

No 3/14, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: Theoretical results on the properties of forecasts obtained using singular spectrum analysis are presented in this paper. The mean squared forecast error is derived under broad regularity conditions, and it is shown that the forecasts obtained in practice will converge to their population ensemble counterparts. The theoretical results are illustrated by examining the performance of singular spectrum analysis forecasts when applied to autoregressive processes and a random walk process. Simulation experiments suggest that the asymptotic properties developed are reflected in observed finite sample behaviour. Empirical applications using real world data sets indicate that forecasts based on singular spectrum analysis are competitive with other methods currently in vogue.

Keywords: Linear recurrent formula; Mean squared forecast error; Signal dimension; Window length. (search for similar items in EconPapers)
JEL-codes: C51 C52 C53 (search for similar items in EconPapers)
Pages: 25
Date: 2014
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
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