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DC Field | Value | Language |
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dc.contributor.author | Cuñado, J | - |
dc.contributor.author | Gil-Alana, LA | - |
dc.date.accessioned | 2014-06-03T11:33:01Z | - |
dc.date.available | 2014-06-03T11:33:01Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | Journal of Time Series Analysis, 34(3), 405 - 421, May 2013 | en_US |
dc.identifier.issn | 0143-9782 | - |
dc.identifier.uri | http://onlinelibrary.wiley.com/doi/10.1111/jtsa.12010/abstract | en |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/8548 | - |
dc.description | Copyright @ 2012 Wiley Publishing Ltd. This is the accepted version of the following article: "Modelling long-run trends and cycles in financial time series data", Journal of Time Series Analysis, 34(3), 405-421, 2013, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/jtsa.12010/abstract. | en_US |
dc.description.abstract | This article 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 non-stationary 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. | en_US |
dc.description.sponsorship | Ministerio de Ciencia y Tecnologia and Jeronimo de Ayanz project of the Government of Navarra. | en_US |
dc.language | English | - |
dc.language.iso | en | en_US |
dc.publisher | John Wiley & Sons, Inc | en_US |
dc.subject | Fractional integration | en_US |
dc.subject | Financial time series data | en_US |
dc.subject | Trends | en_US |
dc.subject | Cycles | en_US |
dc.title | Modelling long-run trends and cycles in financial time series data | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1111/jtsa.12010 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel Active Staff | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Social Sciences | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Social Sciences/Economics and Finance | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Social Sciences - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Social Sciences - URCs and Groups/Centre for Empirical Finance | - |
Appears in Collections: | Economics and Finance Dept of Economics and Finance Research Papers |
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Fulltext.pdf | 699.96 kB | Adobe PDF | View/Open |
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