Pub Date : 2009-12-01DOI: 10.1016/S1874-8651(10)60088-9
Hao CHEN, Yu-chao MA, Mu-zi CHEN, Yue TANG, Bo WANG, Min CHEN, Xiao-guang YANG
This article modifies the Support Vector Machine (SVM) algorithm to address the issue of a large number of explantory variables in the analysis of nonperforming loan recovery. First, the stepwise SVM is employed in the selection of model structure. Secondly, the results of linear stepwise regression are used as the initial states of the model selection. Empirical results show that the method not only achieves high accurate out-sample prediction, but also stable performance with in-samples and out-samples.
{"title":"Recovery Discrimination based on Optimized-Variables Support Vector Machine for Nonperforming Loan","authors":"Hao CHEN, Yu-chao MA, Mu-zi CHEN, Yue TANG, Bo WANG, Min CHEN, Xiao-guang YANG","doi":"10.1016/S1874-8651(10)60088-9","DOIUrl":"https://doi.org/10.1016/S1874-8651(10)60088-9","url":null,"abstract":"<div><p>This article modifies the Support Vector Machine (SVM) algorithm to address the issue of a large number of explantory variables in the analysis of nonperforming loan recovery. First, the stepwise SVM is employed in the selection of model structure. Secondly, the results of linear stepwise regression are used as the initial states of the model selection. Empirical results show that the method not only achieves high accurate out-sample prediction, but also stable performance with in-samples and out-samples.</p></div>","PeriodicalId":101206,"journal":{"name":"Systems Engineering - Theory & Practice","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1874-8651(10)60088-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91756179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2009-12-01DOI: 10.1016/S1874-8651(10)60093-2
Yang LIU, Yu-qiang FENG, Zhen SHAO
By analyzing bidders' behaviors, the author proposed a new model which is based on the Bagging arithmetic and decision tree for predicting final prices of online auctions. The author collected 3310 transaction data and corresponding 8275 bids from Taobao. Data analysis shows that the final prices of 40.4% transactions can be calculated by using the times of bids. Instead of predicting the final price directly, the author predicts times of bids first and then used it to calculate the final price. The experiment proves that the model substantially outperforms the naive method of predicting the category mean price, and 21.7% of predicted results are exactly equal to the real ones. Compared with Heijst's research, the model is better in required training sample size, calculating time and percentage of accurate prediction. For training, time is only a few seconds, this research can lay the foundation for developping real-time dectsion support systems.
{"title":"Support System for Predicting Online Auction End Prices","authors":"Yang LIU, Yu-qiang FENG, Zhen SHAO","doi":"10.1016/S1874-8651(10)60093-2","DOIUrl":"https://doi.org/10.1016/S1874-8651(10)60093-2","url":null,"abstract":"<div><p>By analyzing bidders' behaviors, the author proposed a new model which is based on the Bagging arithmetic and decision tree for predicting final prices of online auctions. The author collected 3310 transaction data and corresponding 8275 bids from Taobao. Data analysis shows that the final prices of 40.4% transactions can be calculated by using the times of bids. Instead of predicting the final price directly, the author predicts times of bids first and then used it to calculate the final price. The experiment proves that the model substantially outperforms the naive method of predicting the category mean price, and 21.7% of predicted results are exactly equal to the real ones. Compared with Heijst's research, the model is better in required training sample size, calculating time and percentage of accurate prediction. For training, time is only a few seconds, this research can lay the foundation for developping real-time dectsion support systems.</p></div>","PeriodicalId":101206,"journal":{"name":"Systems Engineering - Theory & Practice","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1874-8651(10)60093-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91773086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Loan Rate Pricing of SME Financing based on Agent-based Computational Finance Approach","authors":"Xiong Xiong, Cuijing Guo, Wei Zhang, Yongjie Zhang","doi":"10.1016/S1874-8651(10)60087-7","DOIUrl":"https://doi.org/10.1016/S1874-8651(10)60087-7","url":null,"abstract":"","PeriodicalId":101206,"journal":{"name":"Systems Engineering - Theory & Practice","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74432184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2009-12-01DOI: 10.1016/S1874-8651(10)60094-4
Guanqun Ni, Yinfeng Xu, Xiaowei Xu
{"title":"Online risk-reward model for time-cost tradeoff in project management","authors":"Guanqun Ni, Yinfeng Xu, Xiaowei Xu","doi":"10.1016/S1874-8651(10)60094-4","DOIUrl":"https://doi.org/10.1016/S1874-8651(10)60094-4","url":null,"abstract":"","PeriodicalId":101206,"journal":{"name":"Systems Engineering - Theory & Practice","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76429414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2009-12-01DOI: 10.1016/S1874-8651(10)60092-0
Sulin Pang, Ji-zhang Gong
{"title":"C5.0 Classification Algorithm and Application on Individual Credit Evaluation of Banks","authors":"Sulin Pang, Ji-zhang Gong","doi":"10.1016/S1874-8651(10)60092-0","DOIUrl":"https://doi.org/10.1016/S1874-8651(10)60092-0","url":null,"abstract":"","PeriodicalId":101206,"journal":{"name":"Systems Engineering - Theory & Practice","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87504652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2009-12-01DOI: 10.1016/S1874-8651(10)60091-9
Yu YANG , Xiu-hong SHI
This article presents a credit risk model for measuring personal default probability by introducing the immunity algorithm. Compared with logistic regression model with Receiver Operator Curve (ROC) test, the model which under the theoretic framework of bilateral antibody artificial immunity appears to be more sensitive to sample data and competent in prediction. The most distinguishing feature owned by this model is it could evolve if trained, and this makes it intelligent and dynamic. Furthermore, it could be implemented not only in predicting individual default probability of commercial banks' clients, but also in measuring personal credit character for other public services.
{"title":"Personal Credit Risk Measurement: Bilateral Antibody Artificial Immune Probability Model","authors":"Yu YANG , Xiu-hong SHI","doi":"10.1016/S1874-8651(10)60091-9","DOIUrl":"https://doi.org/10.1016/S1874-8651(10)60091-9","url":null,"abstract":"<div><p>This article presents a credit risk model for measuring personal default probability by introducing the immunity algorithm. Compared with logistic regression model with Receiver Operator Curve (ROC) test, the model which under the theoretic framework of bilateral antibody artificial immunity appears to be more sensitive to sample data and competent in prediction. The most distinguishing feature owned by this model is it could evolve if trained, and this makes it intelligent and dynamic. Furthermore, it could be implemented not only in predicting individual default probability of commercial banks' clients, but also in measuring personal credit character for other public services.</p></div>","PeriodicalId":101206,"journal":{"name":"Systems Engineering - Theory & Practice","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1874-8651(10)60091-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91773090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2009-12-01DOI: 10.1016/S1874-8651(10)60095-6
Guotai Chi, Zhongyuan Yang
{"title":"Optimal Model of Strip-and-Roll Hedge based on the Min-Variance","authors":"Guotai Chi, Zhongyuan Yang","doi":"10.1016/S1874-8651(10)60095-6","DOIUrl":"https://doi.org/10.1016/S1874-8651(10)60095-6","url":null,"abstract":"","PeriodicalId":101206,"journal":{"name":"Systems Engineering - Theory & Practice","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78439550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2009-12-01DOI: 10.1016/S1874-8651(10)60088-9
Hao-Feng Chen, Yuanyi Ma, Muzi Chen, Yue Tang, Bo-Fang Wang, Min Chen, Xiaoguang Yang
{"title":"Recovery Discrimination based on Optimized-Variables Support Vector Machine for Nonperforming Loan","authors":"Hao-Feng Chen, Yuanyi Ma, Muzi Chen, Yue Tang, Bo-Fang Wang, Min Chen, Xiaoguang Yang","doi":"10.1016/S1874-8651(10)60088-9","DOIUrl":"https://doi.org/10.1016/S1874-8651(10)60088-9","url":null,"abstract":"","PeriodicalId":101206,"journal":{"name":"Systems Engineering - Theory & Practice","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91541984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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