DEA and Logit Models for Predicting Corporate Financial Distress PDF Download
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Author: Maryam Sheikhi
Publisher: LAP Lambert Academic Publishing
ISBN: 9783848486991
Category :
Languages : en
Pages : 140
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Book Description
The financial ratios coming out of financial statements can reflect some of the characteristics of companies in different aspects, but generally, it has been proved that weak management is the main cause of financial distress. So, the distress of companies can be the reflection of its management condition. Consequently the distress score of companies should be considered as a new variable in prediction of financial distress model. Among the methods applied to compare the efficiency of different statistic models, the ROC curves analysis are often used in the fields of psychology and bio-physics to measure a diagnosis test and to compare the performance of various models for two-category results. Therefore, concerning the topic of this research and the use of ROC curves in predicting the financial distress of corporations, current research aims at designing Logit model using the distress score of the corporations and investigates the predictability of this new variable. Also, a model based on the DEA is designed and finally for better analyzing the results are compared with the Logit models.
Author: Maryam Sheikhi
Publisher: LAP Lambert Academic Publishing
ISBN: 9783848486991
Category :
Languages : en
Pages : 140
Get Book Here
Book Description
The financial ratios coming out of financial statements can reflect some of the characteristics of companies in different aspects, but generally, it has been proved that weak management is the main cause of financial distress. So, the distress of companies can be the reflection of its management condition. Consequently the distress score of companies should be considered as a new variable in prediction of financial distress model. Among the methods applied to compare the efficiency of different statistic models, the ROC curves analysis are often used in the fields of psychology and bio-physics to measure a diagnosis test and to compare the performance of various models for two-category results. Therefore, concerning the topic of this research and the use of ROC curves in predicting the financial distress of corporations, current research aims at designing Logit model using the distress score of the corporations and investigates the predictability of this new variable. Also, a model based on the DEA is designed and finally for better analyzing the results are compared with the Logit models.
Author: You Hoo Tew
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: D'Andre Wilson
Publisher:
ISBN: 9780494858004
Category :
Languages : en
Pages :
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Book Description
Author: Edward I. Altman
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 408
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Book Description
"A Wiley-Interscience publication."Includes index. Bibliography: p. 355-361.
Author: Zhiyong Li
Publisher:
ISBN:
Category :
Languages : en
Pages : 13
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Book Description
Creditors such as banks frequently use expert systems to support their decisions when issuing loans and credit assessment has been an important area of application of machine learning techniques for decades. In practice, banks are often required to provide the rationale behind their decisions in addition to being able to predict the performance of companies when assessing corporate applicants for loans. One solution is to use Data Envelopment Analysis (DEA) to evaluate multiple decision-making units (DMUs or companies) which are ranked according to the best practice in their industrial sector. A linear programming algorithm is employed to calculate corporate efficiency as a measure to distinguish healthy companies from those in financial distress. This paper extends the cross-sectional DEA models to time-varying Malmquist DEA, since dynamic predictive models allow one to incorporate changes over time. This decision-support system can adjust the efficiency frontier intelligently over time and make robust predictions. Results based on a sample of 742 Chinese listed companies observed over 10 years suggest that Malmquist DEA offers insights into the competitive position of a company in addition to accurate financial distress predictions based on the DEA efficiency measures.
Author: Emel Kahya
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
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Book Description
This paper develops a financial distress model using the statistical methodology of time-series Cumulative Sums (CUSUM). The model has the ability to distinguish between changes in the financial variables of a firm that are the result of serial correlation and changes that are the result of permanent shifts in the mean structure of the variables due to financial distress. Tests performed show that the CUSUM model is robust over time and outperforms other models based on the popular statistical methods of Linear Discriminant Analysis and Logit.
Author: Stefan Cristian Gherghina
Publisher: MDPI
ISBN: 3036505709
Category : Business & Economics
Languages : en
Pages : 408
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Book Description
This book comprises 19 papers published in the Special Issue entitled “Corporate Finance”, focused on capital structure (Kedzior et al., 2020; Ntoung et al., 2020; Vintilă et al., 2019), dividend policy (Dragotă and Delcea, 2019; Pinto and Rastogi, 2019) and open-market share repurchase announcements (Ding et al., 2020), risk management (Chen et al., 2020; Nguyen Thanh, 2019; Štefko et al., 2020), financial reporting (Fossung et al., 2020), corporate brand and innovation (Barros et al., 2020; Błach et al., 2020), and corporate governance (Aluchna and Kuszewski, 2020; Dragotă et al.,2020; Gruszczyński, 2020; Kjærland et al., 2020; Koji et al., 2020; Lukason and Camacho-Miñano, 2020; Rashid Khan et al., 2020). It covers a broad range of companies worldwide (Cameroon, China, Estonia, India, Japan, Norway, Poland, Romania, Slovakia, Spain, United States, Vietnam), as well as various industries (heat supply, high-tech, manufacturing).
Author: Li-Tze Lee
Publisher:
ISBN:
Category : Biometry
Languages : en
Pages : 6
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Book Description
The purpose of this study is to evaluate financial and non-financial variables using the bankruptcy prediction model. Considering Taiwan companies listed between 2001 and 2005, the estimation sample comprises 140 firms (70 failing and 70 non-failing), and the validation sample comprises 52 firms (26 failing and 26 non-failing). In contrast to previous studies, this paper provides a corporate governance index as non-financial variables to predict financial distress along with financial index. Logistic regression is applied to examine these samples for 3 year data prior to business failure. In the estimation sample, the indexes combining both financial and corporate governance indexes gave the most accurate predictions. In the validation sample, the financial variables yielded the most accurate predictions.
Author: Paul C. Simak
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Hui Hu
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659337819
Category : Bankruptcy
Languages : en
Pages : 348
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Book Description
This book presents a study which makes the first attempt to construct a particular financial distress prediction model for growth enterprises on the Growth Enterprise Markets in Hong Kong and mainland China. This study firstly establishes two financial distress prediction models: one incorporating financial factors and the other incorporating non-financial and macroeconomic factors. Based on these two models, the present work develops a financial distress prediction model, which uses all the three sets of factors. It has been found that the model including firm-specific non-financial and macroeconomic factors performs better in predicting growth enterprises' financial distress than does the model including firm-specific financial factors. Moreover, the model that considers all the three sets of factors has better predictive ability than does the model that incorporates firm-specific financial factors. It can be envisaged that investors, auditors and policymakers of the special markets would find the conclusion of this work extremely useful.
