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Modelling Long-Run Trends and Cycles in Financial Time Series Data

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

Abstract

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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Bibliographic Info

Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 2330.

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Date of creation: 2008
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Handle: RePEc:ces:ceswps:_2330

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Keywords: fractional integration; financial time series data; trends; cycles;

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