Modelling Economic Time Series in the Presence of Variance Non-Stationarity: A Practical Approach

Alexandros Milionis ()
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Alexandros Milionis: Bank of Greece, Department of Statistics

No 7, Working Papers from Bank of Greece

Abstract: Although non-stationarity in the level of a time series is always tested (and there is a variety of tests for this purpose), non-stationarity in the variance is sometimes neglected in applied research. In this work, the consequences of neglecting variance non-stationarity in economic time series, and the conceptual difference between variance non-stationarity and conditional variance are discussed. An ad hoc method for testing and correcting for variance non-stationarity is suggested. It is shown that the presence of variance non-stationarity leads to misspecified univariate ARIMA models and correcting for it, the number of model parameters is vastly reduced. The implications of the tests for the hypothesis of weak form market efficiency (WFME) are discussed. More specifically it is argued that the usual autocorrelation tests are inappropriate when based on the differences of asset prices. Finally, it is shown how the analysis of outliers is affected by the presence of variance non-stationarity.

Keywords: Applied time series analysis; economic time series; Box-Jenkins modelling; variance non-stationarity; conditional variance; outlier analysis; efficient market hypothesis. (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2003-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Published in Applied Financial Economics, 2004, 14 (4), pp. 265-278. Titled "The Importance of Variance Stationarity in Economic Time Series Modelling. A Practical Approach".

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