Best proxy to determine firm performance using financial ratios: A CHAID approach

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F22%3A63551658" target="_blank" >RIV/70883521:28120/22:63551658 - isvavai.cz</a>
Result on the web
<a href="https://sciendo.com/article/10.2478/revecp-2022-0010" target="_blank" >https://sciendo.com/article/10.2478/revecp-2022-0010</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.2478/revecp-2022-0010" target="_blank" >10.2478/revecp-2022-0010</a>

Result language
angličtina
Original language name
Best proxy to determine firm performance using financial ratios: A CHAID approach
Original language description
The main purpose of this study is to investigate the best predictor of firm performance among different proxies. A sample of 287 Czech firms was taken from automobile, construction, and anufacturing sectors. Panel data of the firms was acquired from the Albertina database for the time period from 2016 to 2020. Three different proxies of firm performance, return of assets (RoA), return of equity (RoE), and return of capital employed (RoCE) were used as dependent variables. Including three proxies of firm's performance, 16 financial ratios were measured based on the previous literature. A machine learning-based decision tree algorithm, Chi-squared Automatic Interaction Detector (CHAID), was deployed to gauge each proxy's efficacy and examine the best proxy of the firm performance. A partitioning rule of 70:30 was maintained, which implied that 70% of the dataset was used for training and the remaining 30% for testing. The results revealed that return on assets (RoA) was detected to be a robust proxy to predict financial performance among the targeted indicators. The results and the methodology will be useful for policy-makers, stakeholders, academics and managers to take trategic business decisions and forecast financial performance.
Czech name
—
Czech description
—

Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
50201 - Economic Theory

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical
Národohospodářský obzor - Review of Economic Perspectives
ISSN
1213-2446
e-ISSN
1804-1663
Volume of the periodical
22
Issue of the periodical within the volume
3
Country of publishing house
PL - POLAND
Number of pages
21
Pages from-to
"219 "- 239
UT code for WoS article
000862631900003
EID of the result in the Scopus database
2-s2.0-85139490029

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