DocumentCode
2016576
Title
Financial Forecasting: Advanced Machine Learning Techniques in Stock Market Analysis
Author
Yoo, Paul D. ; Kim, Maria H. ; Jan, Tony
Author_Institution
Dept. of Comput. Syst., Univ. of Technol., Sydney, NSW
fYear
2005
fDate
24-25 Dec. 2005
Firstpage
1
Lastpage
7
Abstract
The prediction of stock market has been an important issue in the field of finance, mathematics and engineering due to its great potential financial gain. In addition, uncertainty in the prediction of the financial time series has attracted interest from many researchers. In this study, we present recent developments in stock market prediction models, and discuss their strengths and limitations. In addition, we investigate diverse macroeconomic factors and their issues in the prediction of stock market. From this study, we found that incorporating event information into the prediction models plays important roles for more accurate prediction. Hence, an accurate event weighting method and a stable automated event extraction system are required for more accurate and reliable stock market prediction
Keywords
economic forecasting; learning (artificial intelligence); macroeconomics; stock markets; time series; event weighting method; financial forecasting; financial time series; machine learning; macroeconomic factor; stock market analysis; Data mining; Economic forecasting; Finance; Internet; Machine learning; Mathematics; Neural networks; Predictive models; Stock markets; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
9th International Multitopic Conference, IEEE INMIC 2005
Conference_Location
Karachi
Print_ISBN
0-7803-9429-1
Electronic_ISBN
0-7803-9430-5
Type
conf
DOI
10.1109/INMIC.2005.334420
Filename
4133435
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