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Combining Support Vector Machine and Data Envelopment Analysis to Predict Corporate Failure for Nonmanufacturing Firms
https://doi.org/10.24545/00001411
https://doi.org/10.24545/00001411966e8e39-bcca-4a31-bab5-fe15b4b718ef
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
11-20_Yang,Dimitrov.pdf (101.5 kB)
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| Item type | 会議発表用資料 / Conference paper(1) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2016-06-06 | |||||||||
| タイトル | ||||||||||
| タイトル | Combining Support Vector Machine and Data Envelopment Analysis to Predict Corporate Failure for Nonmanufacturing Firms | |||||||||
| 言語 | en | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | support vector machine (SVM) | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | data envelopment analysis (DEA) | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | corporate failure | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | nonmanufacturing firms | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | predictions | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||
| 資源タイプ | conference paper | |||||||||
| ID登録 | ||||||||||
| ID登録 | 10.24545/00001411 | |||||||||
| ID登録タイプ | JaLC | |||||||||
| 著者 |
YANG, Xiaopeng
× YANG, Xiaopeng
× DIMITROV, Stanko
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| 会議概要 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | Workshop 2015 -Advances in DEA Theory and Applications (December 1-2, 2015) | |||||||||
| 抄録 | ||||||||||
| 内容記述タイプ | Abstract | |||||||||
| 内容記述 | Research on corporate failure prediction has drawn numerous scholars’ attention because of its usefulness in corporate risk management, as well as in regulating corporate operational status. Most previous research related to this topic focused on manufacturing companies and relied heavily on corporate assets. The asset size of a manufacturing company plays a vital role in traditional research methods; Altman’s Z score model is one such traditional method. However, very limited number of research studied corporate failure prediction for nonmanufacturing companies as the operational status of such companies is not solely correlated to their assets. In this manuscript we use support vector machines (SVMs) and data envelopment analysis (DEA) to provide a new method for predicting corporate failure of nonmanufacturing firms. We first generate efficiency scores using a slack-based measure (SBM) DEA model, using the recent three years historical data of nonmanufacturing firms; then we used SVMs to classify bankrupt firms and healthy ones. We show that using DEA scores as the only inputs into SVMs predict corporate failure more accurately than using the entire raw data available. | |||||||||
| 内容記述 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | The workshop is supported by JSPS (Japan Society for the Promotion of Science), Grant-in-Aid for Scientific Research (B), #25282090, titled “Studies in Theory and Applications of DEA for Forecasting Purpose. | |||||||||
| 内容記述 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | 本研究はJSPS科研費 基盤研究(B) 25282090の助成を受けたものです。 | |||||||||
| 発表年月日 | ||||||||||
| 日付 | 2015-12-01 | |||||||||
| 日付タイプ | Issued | |||||||||
| 書誌情報 |
p. 11-20 |
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| 公開者 | ||||||||||
| 出版者 | 出版社不明 | |||||||||
| 関連サイト | ||||||||||
| 関連タイプ | isDerivedFrom | |||||||||
| 識別子タイプ | URI | |||||||||
| 関連識別子 | http://www.grips.ac.jp/jp/oldseminars/20151105-3601/ | |||||||||
| 関連名称 | http://www.grips.ac.jp/jp/oldseminars/20151105-3601/ | |||||||||
| 著者版フラグ | ||||||||||
| 出版タイプ | AM | |||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||
