Pattern Prediction in Stock Market

  • Saroj Kaushik
  • Naman Singhal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5866)


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.


Support Vector Machine Pattern Trend Stock Prediction Finance 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Saroj Kaushik
    • 1
  • Naman Singhal
    • 1
  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology, DelhiNew DelhiIndia

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