Short-term Stock Price Analysis Based on Order Book Information

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    • Sakurai Akito
    • Graduate School of Science and Technology, Keio University, Japan


Efficient market hypothesis is widely accepted in financial market studies and entails the unpredictability of future stock prices. In this study, we show that a simple analysis can classify short-term stock price changes with an 82.9% accuracy. Our analysis uses the order book information of high-frequency trading. The volume of high-frequency trading, which is responsible for short-term stock price changes, is increasing dramatically; therefore, our study suggests the importance of analyzing short-term market fluctuations, an aspect that is not well studied in conventional market theories. The experimental results also suggest the importance of the new data representation and analysis methods we propose, neither of which have been thoroughly investigated in conventional financial studies.


  • Transactions of the Japanese Society for Artificial Intelligence

    Transactions of the Japanese Society for Artificial Intelligence 30(5), 683-692, 2015

    The Japanese Society for Artificial Intelligence


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