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Ten Things We Should Know About Time Series

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  • Michael McAleer
  • Les Oxley

Abstract

Time series data affect many aspects of our lives. This paper highlights ten things we should all know about time series, namely: a good working knowledge of econometrics and statistics, an awareness of measurement errors, testing for zero frequency, seasonal and periodic unit roots, analysing fractionally integrated and long memory processes, estimating VARFIMA models, using and interpreting cointegrating models carefully, choosing sensibly among univariate conditional, stochastic and realized volatility models, not confusing thresholds, asymmetry and leverage, not underestimating the complexity of multivariate volatility models, and thinking carefully about forecasting models and expertise.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Michael McAleer & Les Oxley, 2011. "Ten Things We Should Know About Time Series," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 185-188, February.
  • Handle: RePEc:bla:jecsur:v:25:y:2011:i:1:p:185-188
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    References listed on IDEAS

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    1. Michael McAleer, 2005. "The ten commandments for ranking university quality," Journal of Economic Surveys, Wiley Blackwell, vol. 19(4), pages 649-653, September.
    2. Michael McAleer & Les Oxley, 2005. "The Ten Commandments for Academics," Journal of Economic Surveys, Wiley Blackwell, vol. 19(5), pages 823-826, December.
    3. McAleer, Michael & Oxley, Les, 2002. " The Ten Commandments for Presenting a Conference Paper," Journal of Economic Surveys, Wiley Blackwell, vol. 16(2), pages 215-218, April.
    4. Leamer, Edward E, 1988. "Things That Bother Me," The Economic Record, The Economic Society of Australia, vol. 64(187), pages 331-335, December.
    5. McAleer, Michael & Oxley, Les, 2001. " The Ten Commandments for Attending a Conference," Journal of Economic Surveys, Wiley Blackwell, vol. 15(5), pages 671-678, December.
    6. McAleer, Michael, 1997. " The Ten Commandments for Organizing a Conference," Journal of Economic Surveys, Wiley Blackwell, vol. 11(2), pages 231-233, June.
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    Cited by:

    1. Michael McAleer, 2014. "Discussion of “Principal Volatility Component Analysis” by Yu-Pin Hu and Ruey Tsay," Tinbergen Institute Discussion Papers 14-025/III, Tinbergen Institute.
    2. Jean-David Fermanian & Hassan Malongo, 2013. "On the Stationarity of Dynamic Conditional Correlation Models," Working Papers 2013-26, Center for Research in Economics and Statistics.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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