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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51629


    Title: Financial ratio selection for business crisis prediction
    Authors: Lin,FY;Liang,DR;Chen,EC
    Contributors: 資訊工程學系
    Keywords: SUPPORT VECTOR MACHINE;DISCRIMINANT-ANALYSIS;BANKRUPTCY PREDICTION;DISTRESS PREDICTION;FAILURE PREDICTION;NEURAL-NETWORKS;INTEGRATION;ALGORITHMS;MODELS
    Date: 2011
    Issue Date: 2012-03-27 18:57:55 (UTC+8)
    Publisher: 國立中央大學
    Abstract: Recent research has used financial ratios to establish the diagnosis models for business crises. This research explores a broader coverage of financial features, namely the recommended financial ratios from TEJ (Taiwan Economic Journal) database in addition to those financial ratios studied in prior literature. The aim of this research is to discover potentially useful but previously unaware financial features for better prediction accuracy. In this study, we had applied data mining techniques to identify five useful financial ratios, which two of them, tax rates and continuous four quarterly EPS are previously unaware to the research community. Our empirical experiment indicates that our proposed feature set outperforms those models proposed by prior scholars in terms of the prediction accuracy. (C) 2011 Elsevier Ltd. All rights reserved.
    Relation: EXPERT SYSTEMS WITH APPLICATIONS
    Appears in Collections:[資訊工程學系] 期刊論文

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