Title :
Price-Earnings Prediction System Based on Internet Stock Information
Author_Institution :
Inst. of Comput. Sci. & Technol., Peking Univ., Beijing, China
Abstract :
As it is well known, there are lots of factors causing the fluctuation of stock prices. This paper studies this problem from the aspect of Internet information. The significant changes of Internet stock information usually reflect that some special events have occurred in that company. The fluctuation of stock prices must be an associated action. This paper firstly harvests financial information on the Internet, and preprocesses the Internet information, and then completes the relevant study on stock information and on fluctuation of stock prices, with the aid of the learning function of neural networks. Finally, it presents investors the results of neural network forecast in a graphical form, so as to help investors to make decisions. Amazon, the listed company of Wall Street, is taken as an example for analysis.
Keywords :
Internet; economic cycles; financial data processing; learning (artificial intelligence); neural nets; stock markets; Internet stock information; financial information; learning function; neural network; price-earnings prediction system; stock prices fluctuation; Application software; Computer applications; Economic forecasting; Fluctuations; IP networks; Internet; Neural networks; Share prices; Statistics; Stock markets; Internet; prediction; stock information; stock price volatility;
Conference_Titel :
Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
Conference_Location :
Chongqing
Print_ISBN :
978-0-7695-3930-0
Electronic_ISBN :
978-1-4244-5423-5
DOI :
10.1109/IFCSTA.2009.311