Classify unexpected news impacts to stock price by incorporating time series analysis into support vector machine

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn , Issue , 2006, Pages 2993-2998

  Yu, Ting ^a,b   Jan, Tony ^a   Debenham, John ^a   Simoff, Simeon ^a  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

^b CAPITAL MARKETS CRC LIMITED   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA REDUCTION; SUPPORT VECTOR MACHINES; TIME SERIES ANALYSIS;

DATA PREPARATION; STOCK PRICE MOVEMENTS; STOCK PRICES;

FINANCIAL DATA PROCESSING;

EID: 40649103200     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. Yu, T.. T. Jan, J. Debenham, and S. Simoi'f. Incorporating Prior Domain Knowledge in Machine Learning: A Review, in AISTA 2004: International Conference on Advances in Intelligence Systems - Theory and Applications in cooperation with IEEE Computer Society. 2004. Luxembourg.
2. Hommes, C.H., Financial Markets as Nonlinear Adaptive Evolutionary Systems, in Tinbergen Institute Discussion Paper. 2000, University of Amsterdam.
3. Maheu. J.M. and T.H. McCurdy, News Arrival, Jump Dynamics and Volatility Components for Individual Stock Returns. Journal of Finance, 2004. 59(2): p. 755.
4. Mittermayer, M.-A. Forecasting Intraday Stock Price Trends with Text Mining Techniques, in The 37th Hawaii International Conference on System Sciences. 2004.
5. Wuthrich. B., et al., Daily Stock Market Forecast from Textual Web Data, in IT Magazine. 1998. p. 46-47.
6. Zhang, D., S.J. Simoff, and J. Debenham. Exchange Rate Modelling using News Articles and Economic Data, in The 18th Australian Joint Conference on Artificial Intelligence. 2005. Sydney Australia.
7. Lee, C.C., M.J. Ready, and P.J. Seguin, Volume, volatility, and New York Stock Exchange trading halts. Journal of Finance, 1994. 49(1): p. 183-214.
8. Collopy, F. and J.S. Armstrong. Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations. Journal of Management Science, 1992. 38(10): p. 1394-1414.
9. Lavrenko. V., et al., Language Models for Financial News Recommendation. 2000, Department of Computer Science. University of Massachusetts: Amhers, MA.
10. Roddick, J.F. and M. Spiliopoulou, A survey of temporal knowledge discovery paradigms and methods. Knowledge and Data Engineering, IEEE Transactions on. 2002. 14(4): p. 750-767.
11. Keogh. E., S. Chu, D. Hart, and M. Pazzani. An Online Algorithm for Segmenting Time Series, in In Proceedings of IEEE International Conference on Data Mining. 2001.
12. Keogh, E.. S. Chu. D. Hart, and M. Pazzani. Segmenting Time Series: A Survey and Novel Approach, in Data Mining in Time Series Databases. 2003, World Scientific Publishing Company.
13. Guralnik, V. and J. Srivastava. Event Detection From Time Series Data, in KDD-99. 1999. San Diego, CA USA.
14. Dale, R., R. Calvo, and M. Tilbrook. Key Element Summarisation: Extracting Information from Company Announcements, in Proceedings of the 17th Australian Joint Conference on Artificial Intelligence. 2004. Cairns, Queensland. Australia.
15. Losada, D.E. and A. Barreiro, Embedding term similarity and inverse document frequency into a logical model of information retrieval. Journal of the American Society for Information Science and Technology, 2003. 54(4): p. 285-301.
16. Porter. M., An algorithm for suffix stripping. Program, 1980. 14(3): p. 130-137.
17. Chang. C.-C. and C-J. Lin. UBSVM: a Library for Support Vecter Machine. 2004, Department of Computer Sicence and Information Engineering. National Taiwan University.
18. Hautsch, N. and D. Hess, Bayesian Learning in Financial Markets - Testing for the Relevance of Information Precision in Price Discovery. Journal of Financial and Quantitative Analysis, 2005.