| Summary: | 碩士 === 國立交通大學 === 管理學院碩士在職專班資訊管理組 === 96 === That many domestic corporations have suffered financial crises recently victimizes shareholders of those corporations and negatively affects the overall economy. Prior researches on those financial crises are basically one-dimensional while basing on static balance sheets or variables of macroeconomics to support their conclusions. This research based on the above factors expectation can by omnibearing consideration under the dynamic environment the corporations anomaly.A number of scholars apply an unsupervised learning：Self-Organizing Map (SOM) of a neural network to their analyses of those financial crises taking advantage of characteristics of the competitive learning and the Self-Organizing Map , which help obtain the rules for internal clusters of the input data before categorizing them. As such, the study adopts a hierarchical SOM to detect the trend of corporation finances.
Anomaly financial behavior in the study borrows the definitions in Taiwan Economic Journal, which include (1) reorganization, (2) takeover, (3) delising, (4) full delivery, and (5) embezzlement. Over a 96-month period beginning from January 2000 to December 2007, seven hundred and twenty four(724) domestic companies have ever been subject to either one of the aforementioned anomalies.The study relies on the macroeconomics and finance indicators,”one-step variable” processes and normalizes them, and utilizes the Hierarchical SOM to establish the trend of the financial anomaly of corporations. The present research further shows the combination of macroeconomics indicators and finance indicators is superior to the use of finance indicators only in predicting anomaly corporation finance behaviors and the utilizing of hierarchical SOM helps identify anomaly of corporate operations more effectively.
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