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Modelling Long Run Trends and Cycles in Financial Time Series Data

Listed author(s):
  • Luis A. Gil-Alana

    ()

    (School of Economics and Business Administration, University of Navarra)

  • Juncal Cuñado

    ()

    (School of Economics and Business Administration, University of Navarra)

  • Guglielmo Maria Caporale

    ()

    (School of Social Sciences, Brunel University)

This paper proposes a general time series framework to capture the long-run behaviour of financial series. The suggested approach includes linear and segmented 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 both zero but non-zero (cyclical) frequencies. This framework is used to analyse five annual time series with a long span, namely dividends, earnings, interest rates, stock prices and long-term government bond yields. The results based on several likelihood criteria indicate that the five series exhibit fractional integration with one or two poles in the spectrum, and are quite stable over the sample period examined.

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File URL: http://www.unav.edu/documents/10174/6546776/1352908915_WP_UNAV_13_12.pdf
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Paper provided by School of Economics and Business Administration, University of Navarra in its series Faculty Working Papers with number 13/12.

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Length: 46 pages
Date of creation: 12 Oct 2012
Handle: RePEc:una:unccee:wp1312
Contact details of provider: Web page: http://www.unav.edu/web/facultad-de-ciencias-economicas-y-empresariales

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