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The performance of insolvency prediction and credit risk models in the UK: A comparative study. (2013). , Richard ; Wood, Anthony.
In: The British Accounting Review.
RePEc:eee:bracre:v:45:y:2013:i:3:p:183-202.

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  1. Does the bankrupt cheat? Impact of accounting manipulations on the effectiveness of a bankruptcy prediction. (2023). Muko, Przemysaw ; Adamczyk, Adam.
    In: PLOS ONE.
    RePEc:plo:pone00:0280384.

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  2. Analyzing Insolvency Prediction Models in the Period Before and After the Financial Crisis: A Case Study on the Example of US Firms. (2022). Sardar, Sophia Ali ; Salti, Rebecca ; Sykianakis, Nicos ; Giannopoulos, George.
    In: International Journal of Finance, Insurance and Risk Management.
    RePEc:ers:ijfirm:v:12:y:2022:i:3:p:23-45.

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  3. Predicting industry sectors from financial statements: An illustration of machine learning in accounting research. (2022). van der Heijden, Hans.
    In: The British Accounting Review.
    RePEc:eee:bracre:v:54:y:2022:i:5:s0890838922000257.

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  4. Uncertainty of Claims Provisions from the Analysis of Financial Statements. (2022). Cazzari, Roberto Bomgiovani ; Fernandes, Guilherme Rodovalho.
    In: RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration).
    RePEc:abg:anprac:v:26:y:2022:i:3:1510.

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  5. Multi-class Models for Assessing the Financial Condition of Manufacturing Enterprises. (2020). Tomczak, Sebastian Klaudiusz.
    In: Contemporary Economics.
    RePEc:wyz:journl:id:606.

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  6. Factors influencing SME owners’ continuance intention in Bangladesh: a logistic regression model. (2020). Sokhanvar, Amin ; Aghaei, Iman.
    In: Eurasian Business Review.
    RePEc:spr:eurasi:v:10:y:2020:i:3:d:10.1007_s40821-019-00137-6.

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  7. Predicting SMEs Failure: Logistic Regression vs Artificial Neural Network Models. (2020). Hiau, Nur Adiana ; Khaw, Karren Lee-Hwei ; Abidin, Juraini Zainol.
    In: Capital Markets Review.
    RePEc:mfa:journl:v:28:y:2020:i:2:p:29-41.

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  8. Do words reveal the latent truth? Identifying communication patterns of corporate losers. (2020). Deb, Soumya Guha ; Mukherjee, Shubhadeep ; Kumar, Rahul.
    In: Journal of Behavioral and Experimental Finance.
    RePEc:eee:beexfi:v:26:y:2020:i:c:s221463501930228x.

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  9. PREDICTIVE MODELS OF CORPORATE INSOLVENCY RISKS. (2019). Kovalova, Erika.
    In: Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE.
    RePEc:rom:mancon:v:13:y:2019:i:1:p:989-995.

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  10. Dynamic Bankruptcy Prediction Models for European Enterprises. (2019). Korol, Tomasz.
    In: JRFM.
    RePEc:gam:jjrfmx:v:12:y:2019:i:4:p:185-:d:295688.

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  11. Financial distress in electricity distributors from the perspective of Brazilian regulation. (2019). Scalzer, Rodrigo S ; Wanke, Peter ; Da, Marcelo Alvaro ; Rodrigues, Adriano.
    In: Energy Policy.
    RePEc:eee:enepol:v:125:y:2019:i:c:p:250-259.

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  12. Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions. (2018). Mousavi, Mohammad Mahdi ; Ouenniche, Jamal.
    In: Annals of Operations Research.
    RePEc:spr:annopr:v:271:y:2018:i:2:d:10.1007_s10479-018-2814-2.

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  13. Bankruptcy and Insolvency: An Exploration of Relevant Theories. (2017). Onakoya, Adegbemi ; Olotu, Ayooluwa Eunice .
    In: International Journal of Economics and Financial Issues.
    RePEc:eco:journ1:2017-03-90.

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  14. An Empirical Analysis of Financially Distressed Italian Companies. (2016). Sensini, Luca.
    In: International Business Research.
    RePEc:ibn:ibrjnl:v:9:y:2016:i:10:p:75-85.

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  15. MEASURING FINANCIAL DISTRESS AND PREDICTING CORPORATE BANKRUPTCY: AN INDEX APPROACH. (2016). Mehdian, Seyed ; Liao, Qunfeng.
    In: Review of Economic and Business Studies.
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    RePEc:pab:fiecac:12.03.

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  40. Multi-period credit default prediction with time-varying covariates.. (2011). Orth, Walter .
    In: MPRA Paper.
    RePEc:pra:mprapa:30507.

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  41. Assessing bankruptcy prediction models via information content of technical inefficiency. (2011). Hwang, Ruey-Ching ; Siao, Jhao-Siang ; Chung, Huimin.
    In: Journal of Productivity Analysis.
    RePEc:kap:jproda:v:36:y:2011:i:3:p:263-273.

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  42. The predictive ability of “conservatism” and “governance” variables in corporate financial disclosures. (2011). Ren, Yun ; Dong, Yinan ; Smith, Malcolm.
    In: Asian Review of Accounting.
    RePEc:eme:arapps:v:19:y:2011:i:2:p:171-185.

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  43. The term structure of banking crisis risk in the United States: A market data based compound option approach. (2011). Eichler, Stefan ; Maltritz, Dominik ; Karmann, Alexander.
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:35:y:2011:i:4:p:876-885.

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  44. Dynamic analysis of the business failure process: A study of bankruptcy trajectories. (2010). du Jardin, Philippe ; Severin, Eric.
    In: MPRA Paper.
    RePEc:pra:mprapa:44379.

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  45. Is hazard or probit more accurate in predicting financial distress? Evidence from U.S. bank failures. (2010). Cole, Rebel ; Wu, Qiongbing.
    In: MPRA Paper.
    RePEc:pra:mprapa:24688.

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  46. A compound option approach to model the interrelation between banking crises and country defaults: The case of Hungary 2008. (2010). Maltritz, Dominik.
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:34:y:2010:i:12:p:3025-3036.

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  47. Is the diversification discount caused by the book value bias of debt?. (2010). Muller, Sebastian ; Glaser, Markus.
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:34:y:2010:i:10:p:2307-2317.

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  48. A hybrid bankruptcy prediction model with dynamic loadings on accounting-ratio-based and market-based information: A binary quantile regression approach. (2010). Miu, Peter ; Li, Ming-Yuan Leon.
    In: Journal of Empirical Finance.
    RePEc:eee:empfin:v:17:y:2010:i:4:p:818-833.

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  49. Bankruptcy prediction models: How to choose the most relevant variables?. (2009). du Jardin, Philippe.
    In: MPRA Paper.
    RePEc:pra:mprapa:44380.

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  50. Accounting-based versus market-based cross-sectional models of CDS spreads. (2009). Sarin, Atulya ; Das, Sanjiv ; Hanouna, Paul.
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:33:y:2009:i:4:p:719-730.

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