| Summary: | 碩士 === 朝陽科技大學 === 財務金融系碩士班 === 97 === To estimate and predict the fluctuation of a stock market is difficult because lot of variables including both macroeconomic and microeconomic factors influence the stock price. Due to the world financial storm resulted from Wall Street financial crisis, global economy plunged to the valley bottom in a flash and the stock market collapsed and met with many a setback. Many companies suffer the unprosperous influence and therefore choose the ways to layoff staffs, to cut salaries and even shutdown branches to reduce the operation cost for the reason of budget. As a result, the rate of unemployment increases and unpaid leave sweeps across large and small scale companies, even a large High-Tech company strives to keep alive.
As the global stock market slumps continuously, it is exactly a good opportunity of marching into the arena at a low price for investors. However, to acquire maximum returns, the investors need not only basic analysis and technological analysis but also other effective approaches. This research work applies artificial intelligence methods to predict the trend of the Taiwan Weighted Stock Index and Taiwan Top 50 Exchange Tracker Fund. Various approaches including Genetic Algorithm, Artificial Neural Networks, Genetic Programming, Grey Prediction with Class Ratio and Grey Decision are employed in this study. The results suggest that the Grey Prediction with Class Ratio performs better than others and the Genetic Programming ranks as second through the periods of short-time, middle-term and long-term training and prediction.
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