Stock Price Regression Based on Order Book Information

Kenichi Yoshida, Akito Sakurai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Efficient market hypothesis, which entails the unpredictability of future stock prices, is widely accepted in financial market studies. In [1], we showed that a rule obtained by a simple analysis classifies short-term stock price changes with an 82.9% accuracy. In the analysis, the order book of high-frequency trading was the subject. The volume of high-frequency trading is increasing dramatically in these days, which is mainly responsible for short-term stock price changes, therefore, our study suggests the necessity of analyzing short-term market fluctuations caused by the high-frequency trading, an aspect that has not been well studied in conventional financial theories. In this paper, we extend our study to predict stock price by changing research framework from classification problem to regression problem. As expected based on [1], the regression model based on the proposed method can achieve very accurate results (e.g., correlation coefficient 0.48).

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE 40th Annual Computer Software and Applications Conference Workshops, COMPSAC 2016
PublisherIEEE Computer Society
Pages89-94
Number of pages6
Volume2
ISBN (Electronic)9781467388450
DOIs
Publication statusPublished - 2016 Aug 24
Event2016 IEEE 40th Annual Computer Software and Applications Conference, COMPSAC 2016 - Atlanta, United States
Duration: 2016 Jun 102016 Jun 14

Other

Other2016 IEEE 40th Annual Computer Software and Applications Conference, COMPSAC 2016
CountryUnited States
CityAtlanta
Period16/6/1016/6/14

Fingerprint

Financial markets

ASJC Scopus subject areas

  • Software

Cite this

Yoshida, K., & Sakurai, A. (2016). Stock Price Regression Based on Order Book Information. In Proceedings - 2016 IEEE 40th Annual Computer Software and Applications Conference Workshops, COMPSAC 2016 (Vol. 2, pp. 89-94). [7552185] IEEE Computer Society. https://doi.org/10.1109/COMPSAC.2016.199

Stock Price Regression Based on Order Book Information. / Yoshida, Kenichi; Sakurai, Akito.

Proceedings - 2016 IEEE 40th Annual Computer Software and Applications Conference Workshops, COMPSAC 2016. Vol. 2 IEEE Computer Society, 2016. p. 89-94 7552185.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yoshida, K & Sakurai, A 2016, Stock Price Regression Based on Order Book Information. in Proceedings - 2016 IEEE 40th Annual Computer Software and Applications Conference Workshops, COMPSAC 2016. vol. 2, 7552185, IEEE Computer Society, pp. 89-94, 2016 IEEE 40th Annual Computer Software and Applications Conference, COMPSAC 2016, Atlanta, United States, 16/6/10. https://doi.org/10.1109/COMPSAC.2016.199
Yoshida K, Sakurai A. Stock Price Regression Based on Order Book Information. In Proceedings - 2016 IEEE 40th Annual Computer Software and Applications Conference Workshops, COMPSAC 2016. Vol. 2. IEEE Computer Society. 2016. p. 89-94. 7552185 https://doi.org/10.1109/COMPSAC.2016.199
Yoshida, Kenichi ; Sakurai, Akito. / Stock Price Regression Based on Order Book Information. Proceedings - 2016 IEEE 40th Annual Computer Software and Applications Conference Workshops, COMPSAC 2016. Vol. 2 IEEE Computer Society, 2016. pp. 89-94
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