Applying Fuzzy Logic to Corporate Governance Rating Systems

• Main Authors: Chia-Chieh Lin, 林家頡
• Other Authors: 李存修
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/94333854798190311721

碩士 === 國立臺灣大學 === 財務金融學研究所 === 95 === The purpose of this thesis is to solve the problem of subjective weighting judgments in the domestic and overseas corporate governance rating systems and to take CLSA corporate governance rating system and Yeh et al.’s Taiwan corporate governance rating system as the improvable systems. Integrating the fuzzy logic technique into each corporate governance rating system is to solve the uncertainty and the vagueness of how good or how bad in the degree of corporate governance. At first, this thesis builds each fuzzy logic model for these two corporate governance rating systems. The fuzzy logic models treat the scores of indicators in these two corporate governance rating systems as the input values in order to output the fuzzy logic corporate governance indicators. Furthermore, the thesis verifies the correlation between fuzzy logic corporate governance indicators and the performance of firms. The empirical results show that each fuzzy logic corporate governance indicator is quite different from each original weighted corporate governance indicator in these two corporate governance rating systems. The empirical results of multiple regressions imply that the fuzzy logic tool can solve the problem of subjectively weighting judgments when it applies in the corporate governance rating system. The fuzzy logic corporate governance indicator is more objective than the weighted corporate governance indicator. Its explanation ability in the performance of firms is stronger than the weighted corporate governance indicator’s.