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Usage of control charts for time series analysis in financial management

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dc.title Usage of control charts for time series analysis in financial management en
dc.contributor.author Kovářík, Martin
dc.contributor.author Sarga, Libor
dc.contributor.author Klímek, Petr
dc.relation.ispartof Journal of Business Economics and Management
dc.identifier.issn 1611-1699 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2015
utb.relation.volume 16
utb.relation.issue 1
dc.citation.spage 138
dc.citation.epage 158
dc.type article
dc.language.iso en
dc.publisher Vilnius Gediminas Technical University
dc.publisher Taylor and Francis Inc.
dc.identifier.doi 10.3846/16111699.2012.732106
dc.relation.uri https://journals.vgtu.lt/index.php/JBEM/article/view/2716
dc.relation.uri http://www.tandfonline.com/doi/abs/10.3846/16111699.2012.732106
dc.subject autocorrelation en
dc.subject control chart CUSUM en
dc.subject statistical process control en
dc.subject control chart ARIMA en
dc.subject Shewhart's control charts en
dc.subject control chart EWMA en
dc.description.abstract We will deal with corporate financial proceeding using statistical process control, specifically time series control charts. The article outlines intersection of two disciplines, namely econometrics and statistical process control. Theoretical part discusses methodology of time series control charts, and in research part, the methodology is demonstrated on two case studies. The first focuses on analysis of Slovak currency from the perspective of its usefulness for generating profits through time series control charts. The second involves regulation of financial flows for a heteroskedastic financial process by EWMA and ARIMA control charts. We use Box-Jenkins methodology to find models of time series of annual Argentinian Gross Domestic Product available as a basic index from 1951-1998. We demonstrate the versatility of control charts not only in manufacturing but also in managing financial stability of cash flows. Specifically, we show their sensitivity in detecting even small shifts in mean which may indicate financial instability. This analytical approach is widely applicable and therefore of theoretical and practical interest. en
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1004116
utb.identifier.obdid 43872080
utb.identifier.scopus 2-s2.0-84925935959
utb.identifier.wok 000346357900008
utb.source j-wok
dc.date.accessioned 2015-01-29T11:35:05Z
dc.date.available 2015-01-29T11:35:05Z
dc.rights Attribution 4.0 International
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Kovářík, Martin
utb.contributor.internalauthor Sarga, Libor
utb.contributor.internalauthor Klímek, Petr
utb.fulltext.affiliation Martin KOVÁŘÍK1, Libor SARGA2, Petr KLÍMEK3 Department of Statistics and Quantitative Methods, Faculty of Management and Economics, Tomas Bata University, Mostní 5139, 760 01 Zlín, Czech Republic E-mails: 1kovarik.fame@seznam.cz; 2sarga@fame.utb.cz (corresponding author); 3klimek@fame.utb.cz Martin KOVÁŘÍK, PhD, graduated at the Faculty of Management and Economics, Tomas Bata University in Zlin, where he is lecturing at the Department of Statistics and Quantitative Methods since 2009. He also graduated at Faculty of Applied Informatics, Tomas Bata University in Zlin in the field of Information Technology. Author and co-author of 7 books and 5 lecture notes, his research is focused on mathematical and statistical methods in quality management and computationally-intensive statistical data analyses with results published in numerous peer-reviewed journals and presented at conferences in the Czech Republic as well as internationally. Martin Kovářík is also a consultant of statistical data analysis, application of statistical methods in quality management and questionnairebased surveys data processing. Libor SARGA, Ing., is a PhD candidate at the Department of Statistics and Quantitative Methods, Faculty of Management and Economics, Tomas Bata University in Zlin, Czech Republic. His professional interests include information technology, data security policies, and quantitative data processing. His dissertation will focus on setting a suitable data security framework in organizations. Petr KLÍMEK, Associate Professor, is a university teacher and a scientific researcher currently with the Department of Statistics and Quantitative Methods, Faculty of Management and Economics, Tomas Bata University in Zlín. He is the author or co-author of many publications in the field of statistical data analysis in books, teaching scripts, and scientific articles.
utb.fulltext.dates Received 10 July 2012; accepted 17 September 2012
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