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Prediction of Corporate Bankruptcy using Financial Ratios and News

Isha Arora, Navjot Singh
2020 International Journal of Engineering and Management Research  
The financial ratios of the companies were extracted from yearly financial reports of the companies, and the news data of the companies was scrapped from online newspapers, reports and articles using Google  ...  The news data was analyzed for negative and positive sentiments. The sentiment scores, along with the financial ratios of the companies, were given as features to the machine learning models.  ...  News data of both bankrupt and non-bankrupt companies were also extracted for the same years, t1 and t2, as of financial ratios data.  ... 
doi:10.31033/ijemr.10.5.15 fatcat:7kntrszj4fgg7h3tpbrqzgrg2u

Study on Early Warning of Enterprise Financial Distress — Based on Partial Least-squares Logistic Regression

Kun Xu, Qilan Zhao, Xinzhong Bao
2015 Acta Oeconomica  
The data of real estate industry listed companies in China are used to compare and analyze the early warning of fi nancial distress by using the logistic model and the partial least-squares logistic model  ...  This paper applies the partial least-squares logistic regression model for the analysis on early warning of enterprise fi nancial distress in consideration of quite sensitive characteristics of common  ...  National Social Science Foundation of China (No. 14BGL034), the Key Program of Beijing Social Science Foundation of China (No. 15JGA003) and the Funding Project for Academic Human Resources Development in  ... 
doi:10.1556/032.65.2015.s2.2 fatcat:27k6qnpo2zeojgyboyurw3bz5m

Integrated early warning prediction model for Islamic banks: the Malaysian case

Jaizah Othman, Mehmet Asutay
2017 Journal of Banking Regulation  
Before extraction, SPSS has identified 13 linear components or factors within the data set.  ...  In the early stage, all 13 ratios are standardized and the three factor scores are determined by using the factor score coefficient matrix calculated using SPSS.  ... 
doi:10.1057/s41261-017-0040-5 fatcat:qwedoschbjhnlkazr6o2bkqera

Multi-agent hybrid mechanism for financial risk management

Jianyuan Yan, Jui-Jung Liao, Ching-Hui Shih
2015 Journal of Industrial Engineering and Management  
Originality/value: The use of multi-agent model to predict the corporate financial distress.  ...  Purpose: The goal of this study was to propose the multi-agent mechanism to forecast the corporate financial distress.  ...  Although the aforementioned techniques can be implemented to assess financial risk, the ability to discriminate non-financial distress firms from financial distress firms still needs further improvement  ... 
doi:10.3926/jiem.1313 fatcat:biix56b5sbfn5egmwyu2w45jf4

AN APPLICATION OF THE COX MODEL TO BANK FAILURE

William R. Lane, Stephen W. Looney, James W. Wansley
1985 The Financial Review  
This study provides a test of early warning model using an enhanced linear discriminant model to forecast the rate of bank failure in Nigeria.  ...  The discriminant model can correctly predict the financial status of about 20 banks out of 21 sampled banks respectively.  ...  Linear discriminant analysis is a conventional method for discriminant feature extraction.  ... 
doi:10.1111/j.1540-6288.1985.tb00251.x fatcat:zcelobgfkfaunolu7fkul4yr2u

EEG-based Classification of Epileptic and Non-Epileptic Events using Multi-Array Decomposition

Evangelia Pippa, Vasileios G. Kanas, Evangelia I. Zacharaki, Vasiliki Tsirka, Michael Koutroumanidis, Vasileios Megalooikonomou
2016 International Journal of Monitoring and Surveillance Technologies Research  
Aiming to evaluate the ability of the extracted signature features to discriminate between 6 epileptic and non-epileptic events widely used classifiers were used, namely the random forest (RF)7 [32], the  ...  , we examined the discriminative power of 7 the extracted features for the classification of epileptic and non-epileptic EEG events by feature 8 ranking.  ... 
doi:10.4018/ijmstr.2016040101 fatcat:ercixprfkfhqfeivoykyw6rmza

Financial Distress Prediction of Chinese Listed Companies Using the Combination of Optimization Model and Convolutional Neural Network

Lin Zhu, Dawen Yan, Zhihua Zhang, Guotai Chi, Firdous Khan
2022 Mathematical Problems in Engineering  
In order to predict financial distress in 3424 Chinese listed companies, we incorporate a novel time windows optimization model into a convolutional neural network and use 576 financial/nonfinancial/macroindicators  ...  as the model input data.  ...  SVM can perform well with high-dimensional feature spaces since it aims to determine an optimum direction of discrimination in the feature space [42] .  ... 
doi:10.1155/2022/9038992 fatcat:ahf7kllo3zautmczu6rj7vns3m

FİNANS SEKTÖRÜNDE ETKİLİ RİSK YÖNETİMİ İÇİN PERFORMANS DEĞERLENDİRME VE BAŞARISIZLIK TAHMİNİ: BÜTÜNLEŞİK BİR KARAR VERME PROSEDÜRÜ

Hasan SELİM, Şebnem Yılmaz BALAMAN
2017 Business And Management Studies An International Journal  
To this aim, 44 commercial banks operating in Turkish financial sector are assessed as healthy and non-healthy by using 57 selected fundamental financial ratios to provide a comprehensive insight to the  ...  using the selected factors and predict the future distress/bankruptcy possibility of the institutions by a comparative analysis employing a quantitative three-step decision making procedure.  ...  They used 20 financial ratios with six feature groups in their analyses.Öğüt et al. (2012) used two multivariate statistical techniques, multiple discriminant analysis and ordered logistic regression,  ... 
doi:10.15295/bmij.v5i1.99 fatcat:tg4mebf36jgx7licuyssayl264

PREDICTING FINANCIAL DISTRESS FOR ROMANIAN COMPANIES

Gheorghe Ruxanda, Cătălina Zamfir, Andreea Muraru
2018 Technological and Economic Development of Economy  
As the literature related to the topic on Romanian data is very scarce, our study, by using a variety of methods and combining feature selection and principal components analysis, brings a new approach  ...  Using a moderately large number of financial ratios, we tried to build models for classifying the companies listed on the Bucharest Stock Exchange into low and high risk classes of financial distress.  ...  The problem of data selection in predicting financial distress was also a topic of research in Tian, Yu, and Zhou (2015) .  ... 
doi:10.3846/tede.2018.6736 fatcat:caccn3hy6jeltpkdgkb7f5kvma

Bankruptcy prediction in firms with statistical and intelligent techniques and a comparison of evolutionary computation approaches

Mu-Yen Chen
2011 Computers and Mathematics with Applications  
Empirical experiments were conducted using a total of 42 ratios including 33 financial, 8 non-financial and 1 combined macroeconomic index, using principle component analysis (PCA) to extract suitable  ...  computation techniques, using data collected from 200 Taiwan Stock Exchange Corporation (TSEC) listed companies.  ...  For this study, the performance matrix was built using overall accuracy, precision, true positive rate and true negative rate.  ... 
doi:10.1016/j.camwa.2011.10.030 fatcat:4cbe3m2kpve7xol74yeewbba2a

An Optimal Model of Financial Distress Prediction: A Comparative Study between Neural Networks and Logistic Regression

Youssef Zizi, Amine Jamali-Alaoui, Badreddine El Goumi, Mohamed Oudgou, Abdeslam El Moudden
2021 Risks  
In the face of rising defaults and limited studies on the prediction of financial distress in Morocco, this article aims to determine the most relevant predictors of financial distress and identify its  ...  to financial distress.  ...  The selection of financial ratios as initial features for predicting financial distress is based on their predictive and discriminative ability between non-distressed and distressed firms in previous works  ... 
doi:10.3390/risks9110200 fatcat:byjyxdikhff2nhxwvez2cos22u

Deep Learning Based on Hierarchical Self-Attention for Finance Distress Prediction Incorporating Text

Sumei Ruan, Xusheng Sun, Ruanxingchen Yao, Wei Li, Nian Zhang
2021 Computational Intelligence and Neuroscience  
To detect comprehensive clues and provide more accurate forecasting in the early stage of financial distress, in addition to financial indicators, digitalization of lengthy but indispensable textual disclosure  ...  For visualization, the elements in the weight matrix of hierarchical self-attention act as scalers to estimate the importance of each word and sentence.  ...  In this study, there are 860 positive samples and 11140 negative samples in the original data set listed in Table 1 . e ratio of positive samples (with financial distress) to negative samples is 1 : 12  ... 
doi:10.1155/2021/1165296 pmid:34925482 pmcid:PMC8683239 fatcat:d2qsd7df3reozib4k5eafqu4ua

Financial distress model prediction using SVM+

Bernardete Ribeiro, Catarina Silva, Armando Vieira, A. Gaspar-Cunha, Joao C. das Neves
2010 The 2010 International Joint Conference on Neural Networks (IJCNN)  
Financial distress prediction is of great importance to all stakeholders in order to enable better decision-making in evaluating firms.  ...  Experimental results in the setting of a heterogeneous data set of French companies demonstrated that the proposed model showed superior performance in terms of prediction accuracy in bankruptcy prediction  ...  With the same goal, non-negative matrix factorization (NMF) is used in [12] for extracting the most discriminative features.  ... 
doi:10.1109/ijcnn.2010.5596729 dblp:conf/ijcnn/RibeiroSVGN10 fatcat:gmen4jg7vvafdgggxml3x65nly

Decision trees to identify companies' distress: the ai at work

SERGIO BARILE, IRENE BUZZI, ERNESTO D'AVANZO, FRANCESCA IANDOLO
2021 Sinergie Italian Journal of Management  
Two experimental settings, which make use of decision trees, allow us in this study to automatically identify the unique combination of variables from the dataset that explains two target variables -'zone  ...  The combination of a new set of variables, allows to understand -within a given range of accuracy -the company's financial health, and conversely, the company's distress, regardless of the Altman Z-score  ...  Five variables Sales, Total Assets, ROA, EBIT, Non-current assets %, Total Debt%, and ROA are featured in R4, which predicts the distress zone.  ... 
doi:10.7433/s115.2021.05 fatcat:m6yfjoiqcngfvh6adtkyb2nyuq

Corporate Bankruptcy Prediction Model, a Special Focus on Listed Companies in Kenya

Daniel Ogachi, Richard Ndege, Peter Gaturu, Zeman Zoltan
2020 Journal of Risk and Financial Management  
Logistic analysis was used in building a model for predicting the financial distress of a company.  ...  The rationale for developing and predicting the financial distress of a company is to develop a predictive model used to forecast the financial condition of a company by combining several econometric variables  ...  Acknowledgments: I would like to acknowledge the Tempus Public Foundation for awarding me a PhD scholarship to study in Hungary.  ... 
doi:10.3390/jrfm13030047 fatcat:6i5ts7yu55bbxfxyqsmdcye5si
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