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The importance of variance stationarity in economic time series modelling. A practical approach

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  • Alexandros Milionis

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 financial 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. Implications for the tests of 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.

Suggested Citation

  • Alexandros Milionis, 2004. "The importance of variance stationarity in economic time series modelling. A practical approach," Applied Financial Economics, Taylor & Francis Journals, vol. 14(4), pages 265-278.
    • Handle: RePEc:taf:apfiec:v:14:y:2004:i:4:p:265-278
    DOI: 10.1080/0960310042000201200
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    Cited by:

    1. Alexandros E. Milionis & Nikolaos G. Galanopoulos & Peter Hatzopoulos & Aliki Sagianou, 2022. "Forecasting actuarial time series: a practical study of the effect of statistical pre-adjustments," Working Papers 297, Bank of Greece.
    2. Alexandros E. Milionis & Nikolaos G. Galanopoulos, 2020. "A study of the effect of data transformation and «linearization» on time series forecasts. A practical approach," Working Papers 280, Bank of Greece.
    3. Alexandros E. Milionis & Nikolaos G. Galanopoulos, 2018. "Time series with interdependent level and second moment: statistical testing and applications with Greek external trade and simulated data," Working Papers 246, Bank of Greece.

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