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Modelling long-run trends and cycles in financial time series data

  • Guglielmo Maria Caporale
  • Juncal Cuñado
  • Luis A. Gil-Alana

This paper proposes a very general time series framework to capture the long-run behaviour of financial series. The suggested model includes linear and non-linear time trends, and stationary and nonstationary processes based on integer and/or fractional degrees of differentiation. Moreover, the spectrum is allowed to contain more than a single pole or singularity, occurring at zero and non-zero (cyclical) frequencies. This model is used to analyse four annual time series with a long span, namely dividends, earnings, interest rates and long-term government bond yields. The results indicate that the four series exhibit fractional integration with one or two poles in the spectrum. A forecasting comparison shows that a model with a non-linear trend along with fractional integration outperforms alternative models over long horizons.

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Article provided by Wiley Blackwell in its journal Journal of Time Series Analysis.

Volume (Year): 34 (2013)
Issue (Month): 3 (05)
Pages: 405-421

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Handle: RePEc:bla:jtsera:v:34:y:2013:i:3:p:405-421
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