Relevant bibliographies by topics / Corporate bankruptcy prediction / Dissertations / Theses
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Dissertations / Theses on the topic 'Corporate bankruptcy prediction'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 February 2022

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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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11

Wu, Jia-yu, and 吳家妤. "Distressed Prediction Models of Corporate Bankruptcy." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/98714350249214990406.

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碩士<br>東吳大學<br>企業管理學系<br>96<br>Based on prior empirical studies of distressed prediction models of corporate bankruptcy that have concentrated exclusively on financial ratio data, this paper also includes corporate governance data to build the model.. All of the data come from the Taiwan Economic Journal Co. Ltd and the Market Observation Open System. Total of 156 usable sample data were collected and analyzed, 52 from distressed firms and 104 from regular firms. The sample periods are from1999 to 2007. Logistic regression analysis are used to determine the relationship between dependent variab
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12

Ferreira, Eva Maria Ribeiro Silva. "Corporate bankruptcy : can machine learning methods enhance the prediction of failure?" Master's thesis, 2021. http://hdl.handle.net/10400.14/35290.

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This dissertation aims to enhance the performance of traditional corporate bankruptcy prediction models through the application of machine learning techniques and models, and industry effects. The data used includes 3664 companies out of which 144 went bankrupt throughout the period of 2000 until 2019, and it was structured to emulate the design of the variables Campbell et al. (2008) used in their study. Evidence was found that implies the improvement of various metrics’ results from the use of machine learning techniques and models. The model with the highest F1-score, meaning the most balan
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13

Dwyer, Margaret Devine. "A comparison of statistical techniques and artificial neural network models in corporate bankruptcy prediction." 1992. http://catalog.hathitrust.org/api/volumes/oclc/28467495.html.

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Thesis (Ph. D.)--University of Wisconsin--Madison, 1992.<br>Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.
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14

Chou, Chen-Pang, and 周振邦. "Comparing the performance of market-based, accounting-based and corporate-governance bankruptcy prediction models." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/79495334391065007785.

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碩士<br>國立中興大學<br>高階經理人碩士在職專班<br>100<br>This study investigates and compares the performance of different approaches to bankruptcy prediction in Taiwan. Through the trace of development of credit models, we try to find new insights based on the current structure of credit measurement and related corporate governance variables which carrying marginal contribution to the latent characteristics of “willingness to pay”. To extract and approximate the pure element of ethics, we use Logit and OLS regression covering specific market-based, accounting-based credit models and sorted variables of corporat
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15

Loureiro, Francisco Soares da Cruz. "Corporate bankruptcy prediction : can KMV-Merton model add value to support vector machines forecasts?" Master's thesis, 2020. http://hdl.handle.net/10400.14/29837.

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This dissertation aims to assess if the output from the KMV-Merton model, the so-called distance to default, can contribute to the support vector machines model with the ultimate goal of better forecasting the bankruptcy of a company. The considered dataset covers 248 non-financial U.S. companies between 2000 and 2018. It was found evidence that the distance to default contributes, within a given range of variables considered, to a better F1-Score using both cross-validation and percentage ratio split. Additionally, the results show that the distance to default is a better predictor than a sim
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16

Juo, Yi-Ru, and 卓怡如. "The Prediction of Corporate Bankruptcy: The Case of Listing and Non-listing Compnies in Taiwan." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/20777245348548198556.

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碩士<br>國立臺灣大學<br>財務金融學研究所<br>83<br>The paper uses two different kinds of samples-- listing and non-listing companies --to establish predictiong model of corporate bankruptcy and discuss the following topics: 　　1.Are successful companies and bankrupt companies different in financial conditions? 　　2.which prediction model is better--traditional statistical model ( MDA or logit ) or neural network model? 　　3.which prediction variable is the best--corporate ratio( CR ), industry - relative ratio ( RR ), change of corporate ratio ( CR), and change of industry-relative ratio( RR )? 　　The results are
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17

Bruhn, Sina. "Corporate bankruptcy prediction: a comparison of logistic regression and random forest on portuguese company data." Master's thesis, 2020. http://hdl.handle.net/10362/105622.

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In the currentfield ofbankruptcy prediction studies, the geographical focus usually is on larger economiesrather than economies the size of Portugal. For the purpose of this studyfinancial statement data from five consecutive years prior to the event of bankruptcy in 2017 was selected. Within the data328,542healthy and unhealthy Portuguese companieswere included.Two predictive models using the Logistic Regression and Random Forest algorithm were fitted to be able to predict bankruptcy.Both developed models deliver good results even though the RandomForestmodel performs slightly bett
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18

Kosturák, Matej. "Predikce korporátních bankrotů a kreditního rizika." Master's thesis, 2013. http://www.nusl.cz/ntk/nusl-321353.

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This thesis present concise but comprehensive overview of most important paper dedicated to prediction of corporate bankruptcy, as well as overview of the theory behind the employed models and crucial indicators for quality assessment and comparison of the estimations. Manually collected data includes financial statement, identification information and especially specifications of management and responsible persons. From this point of view, data collected are of high quality and in Czech Republic relatively unique. Noticeable is also multiple imputation method used, current "state-of-the-art"
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19

"Predicting the reorganization potential of bankrupt firms." Chinese University of Hong Kong, 1989. http://library.cuhk.edu.hk/record=b5886167.

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20

Lee, Chun Yi, and 李俊毅. "Predicting Corporate Bankruptcy and Financial Distress by Gray Forecasting Theory and Artificial Neural Networks." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/38553485334822167320.

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碩士<br>義守大學<br>管理科學研究所<br>87<br>Business operations are closely related to the status quo of the society. When a business is in distress, it will result a serious loss in the whole society, especially the listed stock companies. So it is necessary to build a finance distress prediction model. In the previous researches, traditional statistical techniques such as multivariate statistical and artificial intelligence algorithm such as neural network were the majority methods. Lots of models have only considered with ex-post cross-section financial data, but they ignore useful information from ex-p
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