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master's thesis
Statistički modeli prognoziranja poslovnih prihoda i rashoda INA Grupe d.d.
Zagreb: University of Zagreb, Faculty of Economics and Business, 2024. urn:nbn:hr:148:298347
Šegota, Katarina
University of Zagreb
Faculty of Economics and Business
Department of Managerial Economics

Institutional repository: REPEFZG

Cite this document

Šegota, K. (2024). Statistički modeli prognoziranja poslovnih prihoda i rashoda INA Grupe d.d. (Master's thesis). Zagreb: University of Zagreb, Faculty of Economics and Business. Retrieved from https://urn.nsk.hr/urn:nbn:hr:148:298347

Šegota, Katarina. "Statistički modeli prognoziranja poslovnih prihoda i rashoda INA Grupe d.d.." Master's thesis, University of Zagreb, Faculty of Economics and Business, 2024. https://urn.nsk.hr/urn:nbn:hr:148:298347

Šegota, Katarina. "Statistički modeli prognoziranja poslovnih prihoda i rashoda INA Grupe d.d.." Master's thesis, University of Zagreb, Faculty of Economics and Business, 2024. https://urn.nsk.hr/urn:nbn:hr:148:298347

Šegota, K. (2024). 'Statistički modeli prognoziranja poslovnih prihoda i rashoda INA Grupe d.d.', Master's thesis, University of Zagreb, Faculty of Economics and Business, accessed 19 November 2024, https://urn.nsk.hr/urn:nbn:hr:148:298347

Šegota K. Statistički modeli prognoziranja poslovnih prihoda i rashoda INA Grupe d.d. [Master's thesis]. Zagreb: University of Zagreb, Faculty of Economics and Business; 2024 [cited 2024 November 19] Available at: https://urn.nsk.hr/urn:nbn:hr:148:298347

K. Šegota, "Statistički modeli prognoziranja poslovnih prihoda i rashoda INA Grupe d.d.", Master's thesis, University of Zagreb, Faculty of Economics and Business, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:148:298347

Metadata
TitleStatistički modeli prognoziranja poslovnih prihoda i rashoda INA Grupe d.d.
Title (english)Statistical revenue and expenses forecasting models based on INA Group
AuthorKatarina Šegota
MentorMirjana Čižmešija (mentor)
Committee memberBerislav Žmuk (predsjednik povjerenstva)
Committee memberZrinka Lovretin Golubić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Economics and Business
(Department of Managerial Economics)
Zagreb
Defense date and country2024-09-19, Croatia
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Economics
Abstract
Svrha ovog diplomskog rada je istražiti uspješnost statističkih modela prognoziranja u prognoziranju prihoda od prodaje i poslovnih rashoda poduzeća INA d.d. Prognoziranje je važno u poslovnom planiranju koje je sastavni dio poslovnog odlučivanja. U raznim situacijama, menadžere, investitore, kreditore i druge dionike zanimat će vrijednost poduzeća. Prognoziranje je sastavni dio i procesa vrednovanja poduzeća. Cilj istraživanja bio je utvrđivanje reprezentativnog modela za prognoziranje prihoda od prodaje i poslovnih rashoda INA d.d. Modeli su odabrani po kriteriju minimalnih prosječnih prognostičkih pogrešaka iz skupine tradicionalnih prognostičkih modela na bazi vremenskog niza. Utvrđeno je da je najbolji model za prognoziranje godišnjih prihoda od prodaje i poslovnih rashoda Brownov model jednostavnog eksponencijalnog izglađivanja, dok je za kvartalne prihode od prodaje i poslovne rashode utvrđeno da je Holt-Wintersov multiplikativni model eksponencijalnog izglađivanja najbolji.
Abstract (english)
The purpose of this master's thesis is to investigate the effectiveness of statistical forecasting models in forecasting sales revenue and business expenses of the company INA d.d. Forecasting is particularly important in business planning, which is an integral part of business decision-making. In various situations, managers, investors, creditors and other stakeholders will be interested in the value of a company. Forecasting is, therefore, an integral part of the company valuation process. The goal of the research was to determine a representative model for forecasting sales revenue and business expenses of INA d.d. The models were selected according to the criterion of minimum average prognostic errors from the group of traditional prognostic models based on time series. It was found that the best model for forecasting annual sales revenue and business expenses is Brown's single exponential smoothing model, while for quarterly sales revenue and business expenses it was determined that Holt-Winters multiplicative exponential smoothing model is the best.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:148:298347
Study programmeTitle: Business economics
Study programme type: university
Study level: integrated undergraduate and graduate
Academic / professional title: magistar/magistra ekonomije (magistar/magistra ekonomije)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2024-09-21 14:33:53