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This study attempts to diagnose the financial performance improvement of commercial banks by integrating suitable soft computing methods. The diagnosis of financial performance improvement comprises of three parts: prediction, selection and improvement. The performance prediction problem involves many criteria, and the complexity among the interrelated variables impedes researchers to discover patterns...
This study aims to retrieve useful knowledge from commonly adopted technical indicators, based on a soft computing model, to support investment decisions. Though the validity of technical analysis (TA) has been examined extensively by various statistical models in financial literature, a practical approach that may consider the inconsistency among various technical indicators and the down-side risk...
In this study, an integrated soft computing method is proposed to solve the performance prediction of commercial banks. The proposed model not only shows how to explore the implicit patterns from historical data, but also supports to provide guidance regarding the performance categorization of banks on each attribute. A group of commercial banks in Taiwan is analyzed to construct the model, and three...
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