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Practical use of the Box-Jenkins methodology for seasonal financial data prediction

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dc.title Practical use of the Box-Jenkins methodology for seasonal financial data prediction en
dc.contributor.author Klímek, Petr
dc.relation.ispartof Finance and Performance of Firms in Science, Education and Practice 2015
dc.identifier.isbn 978-80-7454-482-8
dc.date.issued 2015
dc.citation.spage 598
dc.citation.epage 611
dc.event.title 7th International Scientific Conference on Finance and Performance of Firms in Science, Education and Practice
dc.event.location Zlín
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2015-04-23
dc.event.edate 2015-04-24
dc.type conferenceObject
dc.language.iso en
dc.publisher Univerzita Tomáše Bati ve Zlíně (UTB)
dc.publisher Tomas Bata University in Zlín en
dc.relation.uri https://web.archive.org/web/20180722041033/http://www.ufu.utb.cz/konference/sbornik2015.pdf
dc.subject Box-Jenkins Methodology en
dc.subject autocorrelation en
dc.subject partial autocorrelation function en
dc.subject seasonality en
dc.subject SARIMA models en
dc.description.abstract Many economic/financial processes exhibit some form of seasonality. The agricultural, construction, and travel sectors have obvious seasonal patterns resulting from their dependence on the weather. Similarly, the Christmas holiday season has a pronounced influence on the retail trade. In fact, seasonal variation of a series may account for the preponderance of its total variance. Forecasts that ignore important seasonal patterns will have a high variance. One of the possibilities to implement quality forecasts in the seasonal data is to use the Box-Jenkins methodology, which seems to be a useful tool for this purpose. The research study of this paper is devoted to application of ARIMA/SARIMA models to the seasonal financial data that are sensitive to the mean shifting while calculating the autocorrelation in the data. Results are compared with other common models with appropriate commentary. en
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1006481
utb.identifier.obdid 43874233
utb.identifier.wok 000374107300047
utb.source d-wok
dc.date.accessioned 2016-07-26T14:58:37Z
dc.date.available 2016-07-26T14:58:37Z
utb.contributor.internalauthor Klímek, Petr
utb.fulltext.affiliation Klímek Petr Tomas Bata University in Zlín, Faculty of Management and Economics Department of Statistics and Quantitative Methods Mostní 5139, 760 01 Zlín Tel: +420 576 032 815 E-mail: klimek@fame.utb.cz
utb.fulltext.dates -
utb.fulltext.faculty Faculty of Management and Economics
utb.fulltext.ou Department of Statistics and Quantitative Methods
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