英文摘要 |
In the volatility of the stock market, the company did not return to the market caused by a serious loss of investors, is the company in the business, decision-making management and personal finance should pay attention to the subject. This study uses the computer to extract the financial information of the effective listed companies, use the financial variables to accurately predict the return rate of stock price from the chaos of the transaction information in the spinning to find clues into useful knowledge, and then make the right decisions to help companies and investors to avoid risk raising profit margins. In this research, we study the data from the Taiwan's listed companies in six different industries of financial statements, based on the Taiwan Economic Journl (TEJ) online financial database. In the financial statement data, 25 condition attributes and one decision attribute –return rate of stock price - are selected. Using attribute selection to establish models and different classifier evaluations, such as Stacked Integration (Stacking), Naive Bayes (NB) and Radial-Basis-Function Network (RBF Network) three assessment performance. Find out the important decision factors that affect the return rate of stock price, and improve the correctness of the forecast. The empirical results are current liabilities, interest protection multiple and earnings per share business interestare important determinants that affect the return rate of stock price. From the empirical results, use different classifiers for financial data has different performance measures. |