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Relevant bibliographies by topics / Corporate bankruptcy prediction

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Dissertations / Theses

Academic literature on the topic 'Corporate bankruptcy prediction'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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Dissertations / Theses on the topic "Corporate bankruptcy prediction"

1

Perkins, Alexander H. "Accounting Conservatism and the Prediction of Corporate Bankruptcy." Scholarship @ Claremont, 2013. http://scholarship.claremont.edu/cmc_theses/711.

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This paper examines the relationship between the accounting conservatism construct and the prediction of corporate bankruptcy. Prior research has explored the link between accounting quality and bankruptcy prediction, but it has not examined the relationship between accounting conservatism and bankruptcy prediction. This study hypothesizes that the inclusion of conservatism metrics in the bankruptcy hazard model estimation process should have an incremental effect on the predictive ability of bankruptcy hazard models. This paper finds that the inclusion of conservatism metrics does enhance the

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2

Fitzpatrick, Margo L. "Evaluating Bayesian Classifiers and Rough Sets for Corporate Bankruptcy Prediction." NSUWorks, 2004. http://nsuworks.nova.edu/gscis_etd/517.

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Corporate failure or bankruptcy is costly to investors as well as to society in general. Given the high costs of corporate failure, there is much interest in improved methods for bankruptcy prediction. A promising approach to solve this problem is to provide auditors with a tool that aids in estimating the likelihood of bankruptcy. Recent studies indicate that some success has been achieved in identifying a model and good predictive variables, but the research has been limited to narrow industry segments or small samples. This research evaluated and contrasted two approaches for predicting cor

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3

Tian, Shaonan. "Essays on Corporate Default Prediction." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1352403546.

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4

Danilov, Konstantin A. "Corporate bankruptcy : assessment, analysis and prediction of financial distress, insolvency, and failure." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90237.

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Thesis: S.M. in Management Studies, Massachusetts Institute of Technology, Sloan School of Management, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 89-90).<br>This paper is divided into three sections that address the various elements of understanding, predicting and analyzing corporate failure and bankruptcy. Part I covers the definitions of corporate failure, explains the bankruptcy process and then classifies various potential causes of failure into broad categories. The causes are bifurcated into company-specific versus external factors. The

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5

Li, Shaobo. "Two Essays on High-Dimensional Robust Variable Selection and an Application to Corporate Bankruptcy Prediction." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1530270511492443.

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6

Chan, Ho-cheong, and 陳浩昌. "Financial ratios, discriminant analysis and the prediction of corporate financial distress in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1985. http://hub.hku.hk/bib/B31263100.

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7

Mousavi, Biouki Seyed Mohammad Mahdi. "Design and performance evaluation of failure prediction models." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/25925.

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Prediction of corporate bankruptcy (or distress) is one of the major activities in auditing firms’ risks and uncertainties. The design of reliable models to predict distress is crucial for many decision-making processes. Although a variety of models have been designed to predict distress, the relative performance evaluation of competing prediction models remains an exercise that is unidimensional in nature. To be more specific, although some studies use several performance criteria and their measures to assess the relative performance of distress prediction models, the assessment exercise of c

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8

GRASSELLI, FRANCESCA. "L'Analisi e la Previsione delle Insolvenze: Lo Studio del Caso Italiano." Doctoral thesis, Università Cattolica del Sacro Cuore, 2007. http://hdl.handle.net/10280/132.

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A causa delle conseguenze che il fenomeno comporta, sia sul piano finanziario sia sul fronte dell'economia reale, l'analisi e la previsione delle insolvenze societarie continua a rappresentare un argomento attuale nell'ambito della ricerca economica. I recenti sforzi condotti dal Comitato di Basilea verso la diffusione di criteri di valutazione del rischio di credito più precisi ed oggettivi, hanno ulteriormente accresciuto l'importanza della materia. L'obiettivo del presente studio è l'analisi del fenomeno del fallimento sul territorio italiano, al fine di valutare quali variabili sono più ef

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9

Hátle, Lukáš. "Využití Bayesovských sítí pro predikci korporátních bankrotů." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-192331.

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The aim of this study is to evaluate feasibility of using Bayes classifiers for predicting corporate bankruptcies. The results obtain show that Bayes classifiers do reach comparable results to then more commonly used methods such the logistic regression and the decision trees. The comparison has been carried out based on Czech and Polish data sets. The overall accuracy rate of these so called naive Bayes classifiers, using entropic discretization along with the hybrid pre-selection of the explanatory attributes, reaches 77.19 % for the Czech dataset and 79.76 % for the Polish set respectively.

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10

Hoteit, Tarek. "Effects of Investor Sentiment Using Social Media on Corporate Financial Distress." ScholarWorks, 2015. https://scholarworks.waldenu.edu/dissertations/464.

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The mainstream quantitative models in the finance literature have been ineffective in detecting possible bankruptcies during the 2007 to 2009 financial crisis. Coinciding with the same period, various researchers suggested that sentiments in social media can predict future events. The purpose of the study was to examine the relationship between investor sentiment within the social media and the financial distress of firms Grounded on the social amplification of risk framework that shows the media as an amplified channel for risk events, the central hypothesis of the study was that investor sen

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