Choosing a Method for Predicting Economic Performance of Companies

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27350%2F12%3A86082485" target="_blank" >RIV/61989100:27350/12:86082485 - isvavai.cz</a>

Výsledek na webu

<a href="http://hrcak.srce.hr/file/123401" target="_blank" >http://hrcak.srce.hr/file/123401</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Choosing a Method for Predicting Economic Performance of Companies

Popis výsledku v původním jazyce

This paper reports on the efforts to find method for predicting economic results of companies. The input data files consist of 93 profitable companies and 93 bankrupt firms. Each of them is characterized by eight indices. From the total number of 93 firms in both categories, data of 72 firms served for establishing a classification criterion, and for the rest of 21 firms, a prognosis of their economic development was performed. The classification criterion for prognosticating the future economic development of a firm has been established by applications of discriminate analysis, logit analysis and artificial neuron network methods. The application of artificial neural networks has provided for better classification accuracies of 90.48 successful firmsand 100% for bankrupt firms

Název v anglickém jazyce

Choosing a Method for Predicting Economic Performance of Companies

Popis výsledku anglicky

This paper reports on the efforts to find method for predicting economic results of companies. The input data files consist of 93 profitable companies and 93 bankrupt firms. Each of them is characterized by eight indices. From the total number of 93 firms in both categories, data of 72 firms served for establishing a classification criterion, and for the rest of 21 firms, a prognosis of their economic development was performed. The classification criterion for prognosticating the future economic development of a firm has been established by applications of discriminate analysis, logit analysis and artificial neuron network methods. The application of artificial neural networks has provided for better classification accuracies of 90.48 successful firmsand 100% for bankrupt firms

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

Metalurgija = Metallurgy

ISSN

0543-5846

e-ISSN

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Svazek periodika

51

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

HR - Chorvatská republika

Počet stran výsledku

4

Strana od-do

525-528

Kód UT WoS článku

000305205800023

EID výsledku v databázi Scopus

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