Practical Use of Box-Jenkins Methodology for Seasonal Financial Data Prediction

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Practical Use of Box-Jenkins Methodology for Seasonal Financial Data Prediction

Popis výsledku v původním jazyce

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 pronouncedinfluence 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.

Název v anglickém jazyce

Practical Use of Box-Jenkins Methodology for Seasonal Financial Data Prediction

Popis výsledku anglicky

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 pronouncedinfluence 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.

Druh

D - Stať ve sborníku

CEP obor

AE - Řízení, správa a administrativa

OECD FORD obor

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Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 7th International Scientific Conference Finance and the Performance of Firms in Science, Education and Practice

ISBN

978-80-7454-482-8

ISSN

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e-ISSN

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Počet stran výsledku

14

Strana od-do

"598-611"

Název nakladatele

Fakulta managementu a ekonomiky, UTB ve Zlíně

Místo vydání

Zlín

Místo konání akce

Zlín

Datum konání akce

23. 4. 2015

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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