lecture notes in computer science (including subseries lecture
TRANSCRIPT
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Volume 5866 LNAI, 2009, Pages 81-90
ISSN: 03029743ISBN: 364210438X; 978-364210438-1DOI: 10.1007/978-3-642-10439-8_9Document Type: Conference PaperSource Type: Book seriesSponsors: Cent. Res. Intelligent Syst. (CRIS), Monash Univ., Platform Technologies Research Institute (PTRI), RMIT University
22nd Australasian Joint Conference on Artificial Intelligence, AI 2009; Melbourne, VIC; 1 December 2009 through 1 December 2009; Code 83108View at publisher|
Pattern prediction in stock market
Kaushik, S. , Singhal, N. Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi - 110019, India
Abstract In this paper, we have presented a new approach to predict pattern of the financial time series in stock market for next 10 days and compared it with the existing method of exact value prediction [2, 3, and 4]. The proposed pattern prediction technique performs better than value prediction. It has been shown that the average for pattern prediction is 58.7% while that for value prediction is 51.3%. Similarly, maximum for pattern and value prediction are 100% and 88.9% respectively. It is of more practical significance if one can predict an approximate pattern that can be expected in the financial time series in the near future rather than the exact value. This way one can know the periods when the stock will be at a high or at a low and use the information to buy or sell accordingly. We have used Support Vector Machine based prediction system as a basis for predicting pattern. MATLAB has been used for implementation. © Springer-Verlag Berlin Heidelberg 2009.
Language of original document English
Author keywords Finance; Pattern; Prediction; Stock; Support Vector Machine; Trend
Index Keywords Existing method; Financial time series; New approaches; Pattern; Prediction; Prediction systems; Prediction techniques; Stock; Stock market; Trend; Value prediction
Engineering controlled terms: Artificial intelligence; Commerce; Finance; Financial data processing; Support vector machines; Time series; Value engineering
Engineering main heading: Forecasting
Kaushik, S.; Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi - 110019, India; email:[email protected] © Copyright 2011 Elsevier B.V., All rights reserved.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Volume 5866 LNAI, 2009, Pages 81-90