| Summary: | 碩士 === 國立臺北大學 === 企業管理學系 === 96 === Taiwan’s security market has been established more than 40 years. In this period have been many times bullish market and many times bear market. Everyone who buys stock knows the only way to make money in the stock market is buys stock at low price and sells stock at high. But investors don’t know when to buy stock and when to sell. This research used Back Propagation Neural Network to forecast the return of TAIEX, and used monthly data from August 1988 to June 2006 of the TAIEX, macroeconomic variables, Technical Indexes variables, Foreign Stock Indexes variables, all variables. From the result of the research, we have several findings. First, using the all variables to forecast has the best directional and explainable effect in training period and best directional effect in testing period. Second, the result of the Mean Absolute Percentage Error (MAPE) and root mean squared error (RMSE) are different in training period.
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