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Bankruptcy Prediction on Margin Trading and Applications
https://doi.org/10.24517/00011106
https://doi.org/10.24517/00011106272e85d5-a1a9-4367-bdfe-4726e54d88da
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
AA00835991-59_1-26.pdf (3.8 MB)
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| Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2017-10-03 | |||||
| タイトル | ||||||
| タイトル | Bankruptcy Prediction on Margin Trading and Applications | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | margin trading | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | credit scoring | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | bankruptcy prediction | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | stock market simulation | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | bubble bursting | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | departmental bulletin paper | |||||
| ID登録 | ||||||
| ID登録 | 10.24517/00011106 | |||||
| ID登録タイプ | JaLC | |||||
| 著者 |
Tristiyanto
× Tristiyanto |
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| 書誌情報 |
The science reports of the Kanazawa University = 金沢大学理科報告 巻 59, p. 1-26, 発行日 2015-01-01 |
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| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 0022-8338 | |||||
| NCID | ||||||
| 収録物識別子タイプ | NCID | |||||
| 収録物識別子 | AA00835991 | |||||
| 出版者 | ||||||
| 出版者 | Institute of Science and Engineering, Kanazawa University = 金沢大学 | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Although bankruptcy and default are well known as critical factors leading to various financial recessions or financial bubbles, such as the Great Depression in the USA that began in 1929 and the Lost Decade of Japan in the 1990s, predicting when they will occur has not been studied sufficiently. In this paper, we propose a method that filters out risky investors and keeps good investors in a margin-trading simulation. Investors are divided into three classes (bankrupt, surviving and profitable) instead of the standard two (bankrupt/bad and surviving/good). As a result, bubble bursting can be thwarted, since maintaining credit absorption for the qualified investors can prevent the collapse of prices. We expose the problems with using the minimum margin as the de facto tool for controlling trading on the margin. We compare the results of four well-known data classification methods (multiple discriminant analysis, neural networks, decision trees and support vector machines) in order to determine the one that is most suitable for building a credit-scoring schema. Of the methods considered, the C4.5 algorithm for building decision trees was found to be the best. Our proposed strategy can successfully use credit scoring to tame the bubble phenomenon. | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
