Modelling Long Run Trends and Cycles in Financial Time Series Data
Juncal CuÃ±ado () and
Guglielmo Maria Caporale
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Juncal CuÃ±ado: School of Economics and Business Administration, University of Navarra
Authors registered in the RePEc Author Service: Juncal Cuñado ()
No 13/12, Faculty Working Papers from School of Economics and Business Administration, University of Navarra
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.
Pages: 46 pages
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Journal Article: Modelling long-run trends and cycles in financial time series data (2013)
Working Paper: Modelling Long-Run Trends and Cycles in Financial Time Series Data (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:una:unccee:wp1312
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