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The application of graphic methods and the DEA in predicting the risk of bankruptcy
Štefko, Róbert; Horváthová, Jarmila; Mokrišová, … - In: Journal of risk and financial management : JRFM 14 (2021) 5, pp. 1-19
companies that are at risk of bankruptcy using the DEA method. The originality is the selection of key inputs and outputs to the …
Persistent link: https://www.econbiz.de/10012587360
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Determination of disease risk factors using binary data envelopment analysis and logistic regression analysis (case study: a stroke risk factors)
Gholamazad, Maedeh; Pourmahmoud, Jafar; Atashi, Alireza; … - In: Journal of modelling in management 19 (2024) 2, pp. 693-714
Persistent link: https://www.econbiz.de/10014486864
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Integration of grey-based Taguchi method and principal component analysis for multi-response decision-making in Kansei engineering
Sugoro Bhakti Sutono; Abdul-Rashid, Salwa Hanim; Zahari Taha - In: European journal of industrial engineering : EJIE 11 (2017) 2, pp. 205-227
Persistent link: https://www.econbiz.de/10011710500
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PREDICTION OF FINANCIAL DISTRESS BY MULTIVARIATE STATISTICAL ANALYSIS: THE CASE OF FIRMS TAKEN INTO THE SURVEILLANCE MARKET IN THE ISTANBUL STOCK EXCHANGE
CANBAŞ, SERPIL; ÖNAL, YILDIRIM B.; DÜZAKIN, HATICE G.; … - In: International Journal of Theoretical and Applied … 09 (2006) 01, pp. 133-150
early warning model for financial distress prediction. …
Persistent link: https://www.econbiz.de/10005060235
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Using cutting-edge tree-based stochastic models to predict credit risk
Halteh, Khaled; Kumar, Kuldeep; Gepp, Adrian - In: Risks 6 (2018) 2, pp. 1-13
Credit risk is a critical issue that affects banks and companies on a global scale. Possessing the ability to … accurately predict the level of credit risk has the potential to help the lender and borrower. This is achieved by alleviating … trees, random forests, and stochastic gradient boosting to add to the current literature on credit-risk modelling. The …
Persistent link: https://www.econbiz.de/10011996613
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Using cutting-edge tree-based stochastic models to predict credit risk
Halteh, Khaled; Kumar, Kuldeep; Gepp, Adrian - In: Risks : open access journal 6 (2018) 2, pp. 1-13
Credit risk is a critical issue that affects banks and companies on a global scale. Possessing the ability to … accurately predict the level of credit risk has the potential to help the lender and borrower. This is achieved by alleviating … trees, random forests, and stochastic gradient boosting to add to the current literature on credit-risk modelling. The …
Persistent link: https://www.econbiz.de/10011867384
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A generic model of predicting probability of success-distress of an organization : a logistic regression analysis
Bhandari, Shyam; Johnson-Syder, Anna J. - In: The journal of applied business research 34 (2018) 1, pp. 169-182
Persistent link: https://www.econbiz.de/10011889840
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Unveiling the diverse efficacy of artificial neural networks and logistic regression : a comparative analysis in predicting financial distress
Sabek, Amine - In: Croatian review of economic, business and social … 9 (2023) 1, pp. 16-32
The prediction of financial distress has emerged as a significant concern over a prolonged period spanning more than …
Persistent link: https://www.econbiz.de/10014372938
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Global hidden factors predicting financial distress in Gulf Arab states : a quantile-time-frequency analysis
Trabelsi, Nader - In: Journal of financial economic policy 15 (2023) 4/5, pp. 284-312
Persistent link: https://www.econbiz.de/10014380774
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PREDICTING FINANCIAL DISTRESS OF CHINESE LISTED COMPANIES USING ROUGH SET THEORY AND SUPPORT VECTOR MACHINE
CAO, YU; WAN, GUANGYU; WANG, FUQIANG - In: Asia-Pacific Journal of Operational Research (APJOR) 28 (2011) 01, pp. 95-109
), in order to find a better early warning method and enhance the prediction accuracy. After several comparative experiments … prediction. …
Persistent link: https://www.econbiz.de/10008852562