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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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&apos;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&apos;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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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&apos;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&apos;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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50201 - Economic Theory

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Národohospodářský obzor - Review of Economic Perspectives

ISSN

1213-2446

e-ISSN

1804-1663

Svazek periodika

22

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

PL - Polská republika

Počet stran výsledku

21

Strana od-do

"219 "- 239

Kód UT WoS článku

000862631900003

EID výsledku v databázi Scopus

2-s2.0-85139490029