股市漲跌的預測是商業界與學術界非常看重的議題，以往學者針對大盤漲跌的預測，大多使用技術面和籌碼面指標來進行研究;然而國際間金融交易也會緊密的影響著台股市場。本研究透過類神經網路結合多面向指標（技術面、籌碼面、國際股市和國際匯率）以建構預測模型；並充分探討各種指標與不同的類神經網路對預測模型的影響。

Stock forecasting has been a popular and challenging issue in finance and academic researches. Technical and chip indicators are commonly used to forecast the variation of stock index. In addition, the international economic transactions can also influence the variation of stock indices for different countries. Therefore, this research proposes a multiindicator-oriented model based on neural networks. The proposed model combines the technical indicators, chip indicators, international stock market indicators and international exchange rate indicators. The experiments are conducted to find the best parameters on different training set with different lengths of time. The observed multiindicators provide supportive references for researchers and investors. Keywords：neural network ,stock market index prediction ,technical