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How Costly is it to Ignore Breaks when Forecasting the Direction of a Time Series?

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  • Pesaran, H.M.
  • Timmermann, A.

Abstract

Empirical evidence suggests that many macroeconomic and financial time-series are subject to occasional structural breaks. In this paper we present analytical results quantifying the effects of such breaks on the correlation between the forecast and the realisation, and on the ability to forecast the sign or direction of a time-series that is subject to breaks. Our results suggest that it can be very costly to ignore breaks. Forecasting approaches that condition on the most recent break are likely to perform better over unconditional approaches that use expanding or rolling estimation windows, provided that the break is reasonably large.

Suggested Citation

  • Pesaran, H.M. & Timmermann, A., 2003. "How Costly is it to Ignore Breaks when Forecasting the Direction of a Time Series?," Cambridge Working Papers in Economics 0306, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:0306
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    References listed on IDEAS

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    More about this item

    Keywords

    sign prediction; estimation window; structural breaks;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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