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Title:Modelling long-run trends and cycles in financial time series data PDF Logo
Authors:Caporale, Guglielmo Maria
Cunado, Juncal
Gil-Alana, Luis A.
Issue Date:2008
Series/Report no.:CESifo working paper 2330
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.
Subjects:Fractional integration
financial time series data
trends
cycles
JEL:C22
G1
Document Type:Working Paper
Appears in Collections:CESifo Working Papers, CESifo Group Munich

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