Financial failure prediction using efficiency as a predictor

Xu, Xiaoyan; Wang, Yu

doi:10.1016/j.eswa.2007.09.040

Cited by 71 publications

(53 citation statements)

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“…Firstly, DEA has been used to derive a classification algorithm to separate distressed firms from non-distressed firms (Paradi et al, 2004;Cielen et al 2004;Emel et al, 2003). Secondly, the relative efficiency of firms has been computed using DEA and this relative efficiency has been used as a feature of each firm in a subsequently developed classification rule (Xu and Wang, 2009;Yeh et al, 2010;Psillaki et al, 2010). We consider the former first.…”

Section: Literature Reviewmentioning

confidence: 99%

Chinese companies distress prediction: an application of data envelopment analysis

Crook

Andreeva

2014

Journal of the Operational Research Society

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Bankruptcy prediction is a key part in corporate credit risk management. Traditional bankruptcy prediction models employ financial ratios or market prices to predict bankruptcy or financial distress prior to its occurrence. We investigate the predictive accuracy of corporate efficiency measures along with standard financial ratios in predicting corporate distress in Chinese companies. Data Envelopment Analysis (DEA) is used to measure corporate efficiency.In contrast to previous applications of DEA in credit risk modelling where it was used to generate a single efficiency -Technical Efficiency, we assume Variable Returns to Scale, and decompose Technical Efficiency into Pure Technical Efficiency and Scale Efficiency. These measures are introduced into Logistic Regression to predict the probability of distress, along with the levels of Returns to Scale. Effects of efficiency variables are allowed to vary across industries through the use of interaction terms, whilst the financial ratios are assumed to have the same effects across all sectors. The results show that the predictive power is improved by this corporate efficiency information.

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Section: Literature Reviewmentioning

confidence: 99%

Chinese companies distress prediction: an application of data envelopment analysis

Crook

Andreeva

2014

Journal of the Operational Research Society

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“…prediktora. Jednými z prvých autorov, ktorí aplikovali tento prístup, boli Xu a Wang (2009). S cieľom predpovedať finančný bankrot spoločností kótovaných zo Shanghai Stock Exchange autori použili mieru efektívnosti, tzv.…”

Section: Súčasný Stav Využívania Dea Pri Diagnostikovaní Finančného Zunclassified

Diagnosing of the Corporate Financial Health Using DEA: an Application to Companies in the Slovak Republic

Mendelová¹,

Bieliková²

2017

Politicka ekonomie

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Diagnosing of the Corporate Financial Health Using DEA: an Application to Companies in the Slovak RepublicThe paper deals with the examining the possibilities for diagnosing the corporate financial health using Data Envelopment Analysis (DEA) technique. The main aim of the paper is to present a new proposal for diagnosing the corporate financial health by DEA, to predict financial distress of Slovak manufacturing companies using the proposed procedure, and to assess the potential of DEA as a tool for predicting financial distress of the company. Due to the special input and output variables selection and the construction of the Corporate Distress Frontier, the proposed procedure is very different from the conventional use of DEA. The proposed two-step procedure results into the identification of three zones of corporate financial health with different stage of corporate distress risk. The application of the proposed procedure to Slovak manufacturing companies and its comparison with the logistic regression model and decision tree show relatively satisfactory results of the proposed methodology in terms of correct classification of non-bankrupt firms.Keywords: data envelopment analysis, company, corporate distress, diagnosing, financial health JEL Classification: C14, G30 ÚvodZa účelom udržania prosperity a konkurencieschopnosti podniku je pre manažment a ostatné záujmové strany dôležité dôkladne poznať v akej ekonomickej a finančnej situácii sa ich podnik nachádza. Predpokladom pre detailné poznanie finančnej situácie je venovanie dostatočnej pozornosti diagnostikovaniu finančného zdravia podniku a včasné identifikovanie potenciálnych problémov ohrozujúcich jeho činnosť. Potreba včasného diagnostikovania finančných problémov podnikov podnietila vznik rôznych diagnostických modelov založených na finančných ukazovateľoch. Vo vedeckých štúdiách sa obzvlášť vysoká pozornosť venuje aplikácii variantných nástrojov na konštrukciu diagnostických modelov. K najviac využívaným nástrojom v súčasnosti patrí diskriminačná analýza (DA), logistická regresia (LR), rozhodovacie stromy (RS) a rôzne typy neuró-nových sietí (NS). Potreba splnenia viacerých štatistických predpokladov, či pomerne striktné požiadavky na veľkosť dátovej množiny týchto tradičných nástrojov sa však stali stimulom na vývoj nových prístupov, ktorých ambíciou je tieto nevýhody tradičných nástrojov čiastočne eliminovať. Nakoľko diagnostikovanie finančného zdravia podnikov je jednou z pomerne často diskutovaných tém v manažérskej praxi i v kruhoch odbornej *1 Viera Mendelová, Tatiana Bieliková (viera.mendelova@umb.sk, tatiana.bielikova@umb.sk ), Univerzita Mateja Bela v Banskej Bystrici, Ekonomická fakulta. Článok bol vypracovaný v rámci riešenia projektu VEGA 1/0647/14 -Variantné metódy predikcie finančného zdravia podnikov v podmienkach dynamického ekonomického prostredia.

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“…Non-distressed (healthy) corporations are expected to exist inside a ''distress possibility set", which is shaped by the distress frontier (See Premachandra et al (2009), Xu, X. andWang, Y. (2009)).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Under the assumption that a corporation's financial statements appropriately reflect all of its characteristics, current prediction models select variables directly from various financial ratios defined based on information that appears in the corporation's financial statements (Xu, X. and Wang, Y., 2009). Although financial ratios, originated in a corporation's financial statements, can reflect some characteristics of a corporation from various aspects to a certain extent.…”

Section: Introductionmentioning

confidence: 99%

Financial Distress Prediction Using Distress Score as a Predictor

Sheikhi¹,

Shams²,

Sheikhi³

2011

IJBM

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Financial distress can be the reflection of corporation's management condition. Consequently the distress score of corporations should be considered as a new predictor variable in predicting the financial distress.The analysis of ROC curve, among the models employed to compare the effectiveness of different statistical models, is often used in the fields of psychology and bio-physics in order to summarize the discriminatory of a diagnostic test and also to compare the performance of different models for binary outcomes. Therefore, concerning the topic of this research and the use of ROC curves in predicting the financial distress of corporations, we use logit models to study the financial distress of the manufacturing corporations in Tehran Stock Exchange. We also compare the accuracy of the prediction method with financial distress score variable to the method without this variable.Concerning the accuracy of prediction and classification, the results of this research show that the accuracy of prediction can be enhanced by using the distressed score, gained from DEA, as a new predictor variable in predicting the financial distress.

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Financial failure prediction using efficiency as a predictor

Cited by 71 publications

References 30 publications

Chinese companies distress prediction: an application of data envelopment analysis

Chinese companies distress prediction: an application of data envelopment analysis

Diagnosing of the Corporate Financial Health Using DEA: an Application to Companies in the Slovak Republic

Financial Distress Prediction Using Distress Score as a Predictor

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