| Summary: | 碩士 === 中原大學 === 資訊管理研究所 === 105 === The developement of the financial industry is driven by globalization and the Internet''s rise in popularity. Now, investors can trade stocks wherever that are. In this globalized market, investors can trade with more confidence and profit more than usual in return with the help of an accurate tool that predicts the market.
In recent years, the bumpy stock index has been valued by investors. We can observe that the variation of stock index is depending on the country economic status. It means that we can tell the economic development status from a bumpy stock index, and the investors can understand when is the best time to invest in the stock market. It is normal to forecast the variation of stock index by technical indicators and chip indicators. In addition, the international financial information communication is more convenient, we can tell that the financial transaction between different country can influence the variation of stock index from the international stock market transaction information. To predict the variation of the stock index for the next day more accurately , the research sums up the international stock market indicators and international exchange rate indicators to predict the variation.
Therefore, a model based on the neural network and multi-oriented indicators was created from the research. By beginning with combining the technical indicators, chip indicators, international stock market indicators and international exchange rate indicators. Then conduct experiments to find out the best parameters on different training set length of time, and observed which multi-oriented indicators combination that can result in the optimal neural network model. The point is to find out the accurate neural network model to make the investors predict the stock market accurately every day, and provide the researchers and investors data for reference.
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