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Predicting Corporate Financial Sustainability Using Novel Business Analytics
2018
Sustainability
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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
2011
Neural Network World
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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
2022
Mobile Information Systems
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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
2007
Expert systems with applications
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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
2014
Expert systems with applications
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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
2011
Computers and Mathematics with Applications
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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
2012
International Journal of Computer Applications
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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
2020
Ingeniería e Investigación
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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
2016
Filomat
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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
2006
Proceedings of the 9th Joint Conference on Information Sciences (JCIS)
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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
2020
Ingénierie des Systèmes d'Information
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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
2016
Environment Systems and Decisions
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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
2022
Complexity
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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
2015
Innovation and Supply Chain Management
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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
2015
Financial Innovation
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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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