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Predicting Corporate Financial Sustainability Using Novel Business Analytics

Kyoung-jae Kim, Kichun Lee, Hyunchul Ahn
2018 Sustainability  
In this study, we propose globally optimized SVMs, denoted by GOSVM, a novel hybrid SVM model designed to optimize feature selection, instance selection, and kernel parameters altogether.  ...  As a result, building an effective corporate financial distress prediction model has been an important research topic for a long time.  ...  From this perspective, we propose a global optimization model that optimizes the selection of proper features, instances, and kernel parameters of SVMs using GA for financial distress prediction.  ... 
doi:10.3390/su11010064 fatcat:qfixcnghnzbkxbjjts7gqcjjsa

A hybrid model for business failure prediction -- Utilization of particle swarm optimization and support vector machines

Mu-Yen Chen
2011 Neural Network World  
This research applies particle swarm optimization (PSO) to obtain suitable parameter settings for a support vector machine (SVM) model and to select a subset of beneficial features without reducing the  ...  with SVM provides better classification accuracy than the Grid search, and genetic algorithm (GA) with SVM approaches for companies as normal or under threat. (4) The PSO-SVM model also provides better  ...  The author also gratefully acknowledges the Editor and anonymous reviewers for their valuable comments and constructive suggestions.  ... 
doi:10.14311/nnw.2011.21.009 fatcat:e54aap2yknevxjcmz3oixtt2ne

Research on Early Warning of Financial Crisis of Listed Companies Based on Random Forest and Time Series

Chi Zhang, Huaigong Zhong, Aiping Hu, Ateeq Rehman
2022 Mobile Information Systems  
To address this research objective, this study proposes a k-fold random forest algorithm combined with a time series analysis model as an early warning algorithm for corporate financial crises.  ...  The k-fold random forest is used to analyze the financial situation of the predicted financial data and achieve the purpose of dynamic financial crisis early warning.  ...  Acknowledgments is work was supported by the General Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province Construction of manufacturing cost management model  ... 
doi:10.1155/2022/1573966 fatcat:3ipnhwrkqjbofc3cfqgf3wrqna

A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy

Chih-Hung Wu, Gwo-Hshiung Tzeng, Yeong-Jia Goo, Wen-Chang Fang
2007 Expert systems with applications  
Additionally, the proposed GA-SVM model was tested on the prediction of financial crisis in Taiwan to compare the accuracy of the proposed GA-SVM model with that of other models in multivariate statistics  ...  Therefore, the purpose of this study is to develop a genetic-based SVM (GA-SVM) model that can automatically determine the optimal parameters, C and r, of SVM with the highest predictive accuracy and generalization  ...  Min and Lee (2005) stated that the optimal parameter search on SVM plays a crucial role to build a bankruptcy prediction model with high prediction accuracy and stability.  ... 
doi:10.1016/j.eswa.2005.12.008 fatcat:ir4hsm4pivgifkqkk2so4daw7m

An improved boosting based on feature selection for corporate bankruptcy prediction

Gang Wang, Jian Ma, Shanlin Yang
2014 Expert systems with applications  
With the recent financial crisis and European debt crisis, corporate bankruptcy prediction has become an increasingly important issue for financial institutions.  ...  Experimental results reveal that FS-Boosting could be used as an alternative method for the corporate bankruptcy prediction.  ...  Conclusions and future directions Owing to recent financial crisis and European debt crisis, bankruptcy prediction has become an increasingly important issue for financial institutions.  ... 
doi:10.1016/j.eswa.2013.09.033 fatcat:louklz6clnftpkxnier546dfi4

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  
Therefore, the experimental results show that the Particle Swarm Optimization (PSO) integrated with SVM (PSO-SVM) approach could be considered for predicting potential financial distress.  ...  (SVMs) with evolutionary computation provide a good balance of high-accuracy shortand long-term performance predictions for healthy and distressed firms.  ...  NSC-98-2410-H-025-011 and NSC-99-2410-H-025-011. The author also gratefully acknowledges the Editor and anonymous reviewers for their valuable comments and constructive suggestions.  ... 
doi:10.1016/j.camwa.2011.10.030 fatcat:4cbe3m2kpve7xol74yeewbba2a

Enterprise Credit Risk Evaluation models: A Review of Current Research Trends

Ming-Chang Lee
2012 International Journal of Computer Applications  
We found that the current research trends are necessary a method for reduction the feature subset, many hybrids SVM based model and rough model are proposed.  ...  It includes bankruptcy prediction, financial distress, corporate performance clustering / prediction and credit risk estimation.  ...  This heuristic is routinely used to generate useful solutions to optimization and search problems.  ... 
doi:10.5120/6311-8643 fatcat:n4gqs53qqzdg7g3hjrzhlmjd5y

Ten-year evolution on credit risk research: a systematic literature review approach and discussion

Fernanda Medeiros Assef, Maria Teresinha Arns Steiner
2020 Ingeniería e Investigación  
Different steps were followed to select the papers for the analysis, as well as the exclusion criteria, in order to verify only papers with Machine Learning approaches.  ...  In this work, a systematic literature review is proposed which considers both "Credit Risk" and "Credit risk" as search parameters to answer two main research questions: are machine learning techniques  ...  Acknowledgments This study was partially funded by PUCPR and by the Coordination for the Improvement of Education Personnel -Brazil (CAPES, represented by thefirst author) and by the National Council for  ... 
doi:10.15446/ing.investig.v40n2.78649 doaj:49fab6209b7f4390938e44fa1c83b518 fatcat:tm5glc2tz5hddmlfqaznc5na4q

An elm-based classification algorithm with optimal cutoff selection for credit risk assessment

Lean Yu, Xinxie Li, Ling Tang, Li Gao
2016 Filomat  
In this paper, an extreme learning machine (ELM) classification algorithm with optimal cutoff selection is proposed for credit risk assessment.  ...  Different from existing models using a fixed cutoff value (0.0 or 0.5), the proposed classification model especially considers the optimal cutoff value as one important evaluation parameter in credit risk  ...  Acknowledgements This work is supported by grants from the National Science Fund for Distinguished Young Scholars  ... 
doi:10.2298/fil1615027y fatcat:ovjyqsbk2zeh3gsw6z7jlfzi5a

Exploiting Corporate Governance and Common Size Analysis for Financial Distress Detecting Models

PEI-WEN HUANG
2006 Proceedings of the 9th Joint Conference on Information Sciences (JCIS)  
Hence, we construct two software classifiers, BPNs and SVMs, and then investigate the effects of employing features related to corporate governance and common-size analysis in financial distress model.  ...  Experimental results indicate that the proposed features may help SVMs achieve better predication quality when we try to predict financial distresses with more temporally distant data and smaller data  ...  The result indicates that combining corporate governance and common-size analysis features with Altman features helped us achieve better prediction accuracy when we used SVMs.  ... 
doi:10.2991/jcis.2006.188 dblp:conf/jcis/Huang06d fatcat:3qr4jr4am5au7o6xg33ydcerjy

An Optimized Machine Learning Model for Stock Trend Anticipation

Nalabala Deepika, Mundukur Nirupamabhat
2020 Ingénierie des Systèmes d'Information  
Feature selection, dimensionality reduction and optimization techniques can be integrated with emerging advanced machine learning models, to get improvised prediction in terms of quality, performance,  ...  This work implies the base model, boosted model and deep learning model along with optimization techniques.  ...  Ghanbari and Arian [19] , developed a novel hybrid prediction model BOA-SVR, the Butterfly Optimization Algorithm is used to select parameters of SVR.  ... 
doi:10.18280/isi.250608 fatcat:vsbnosuxpjalxlyckwl3iyqi6i

Decision analytics and machine learning in economic and financial systems

Qifeng Qiao, Peter A. Beling
2016 Environment Systems and Decisions  
Decision analytics may be viewed as the combined use of predictive modeling techniques (e.g., forecasting and machine learning) and prescriptive decision frameworks (e.g., optimization and simulation)  ...  Decision analytics has long been used in the domains of economic and financial systems, with credit scoring being an example of an early success, and the clear trend is to the development of ever more  ...  Price prediction using ANNs is commonly done with backpropagation, a training algorithm in which steepest descent gradient is used to learn optimal network parameters.  ... 
doi:10.1007/s10669-016-9601-x fatcat:idaougsjbvamph5lozot42dn6m

Financial Risk Early-Warning of Neusoft Group Based on Support Vector Machine

Yuxuan Dai, Chenhui Yu, Wei Zhang
2022 Complexity  
Finally, the classified data were input into SVM for training and testing, and the model was applied to the financial risk early warning of Neusoft Group.  ...  The research results show that the model can better predict the financial risk of Neusoft Group.  ...  To use SVM for financial early warning, we must first determine its kernel function and parameters. e adjustment of the kernel function and parameters will directly affect the accuracy of the model, with  ... 
doi:10.1155/2022/5878047 fatcat:xlt3yvr6jjh5rkkxojqxgftlcq

Investigation of the Impact of Data Comparability on Performance of Support Vector Machine Models for Credit Scoring

Yanwen DONG, Xiying HAO, Hideo SATO
2015 Innovation and Supply Chain Management  
It is obvious that guaranteeing data comparability is more important and effective than improving algorithm or turning parameters of SVM models.  ...  This paper investigate the impact of data comparability on performance of SVM models for credit scoring.  ...  Acknowledgements This work was partly supported by Grant-in-Aid for Scientific Research (C) from the Japan Society for the Promotion of Science (JSPS KAKENHI) under Grant No. 25380497.  ... 
doi:10.14327/iscm.9.31 fatcat:miwafgumtrcbddnmgacll53c6i

Social credit: a comprehensive literature review

Lean Yu, Xinxie Li, Ling Tang, Zongyi Zhang, Gang Kou
2015 Financial Innovation  
A historical review of the theoretical (or model) development of economic agents is presented together with significant works and future research directions.  ...  credit in conjunction with creation and evolution mechanisms. (2) The most popular credit scoring methods include expert systems, econometric models, artificial intelligence (AI) techniques, and their  ...  and NSFC No. 71301006), the National Program for Support of Top-Notch Young Professionals and the Fundamental Research Funds for the Central Universities in BUCT.  ... 
doi:10.1186/s40854-015-0005-6 fatcat:r4ackwjtgrapbohaowoq3optq4
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