IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2010.15586.html
   My bibliography  Save this paper

Event-Driven Learning of Systematic Behaviours in Stock Markets

Author

Listed:
  • Xianchao Wu

Abstract

It is reported that financial news, especially financial events expressed in news, provide information to investors' long/short decisions and influence the movements of stock markets. Motivated by this, we leverage financial event streams to train a classification neural network that detects latent event-stock linkages and stock markets' systematic behaviours in the U.S. stock market. Our proposed pipeline includes (1) a combined event extraction method that utilizes Open Information Extraction and neural co-reference resolution, (2) a BERT/ALBERT enhanced representation of events, and (3) an extended hierarchical attention network that includes attentions on event, news and temporal levels. Our pipeline achieves significantly better accuracies and higher simulated annualized returns than state-of-the-art models when being applied to predicting Standard\&Poor 500, Dow Jones, Nasdaq indices and 10 individual stocks.

Suggested Citation

  • Xianchao Wu, 2020. "Event-Driven Learning of Systematic Behaviours in Stock Markets," Papers 2010.15586, arXiv.org.
    • Handle: RePEc:arx:papers:2010.15586
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2010.15586
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    2. Daiki Matsunaga & Toyotaro Suzumura & Toshihiro Takahashi, 2019. "Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis," Papers 1909.10660, arXiv.org, revised Nov 2019.
    3. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    4. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    5. Raehyun Kim & Chan Ho So & Minbyul Jeong & Sanghoon Lee & Jinkyu Kim & Jaewoo Kang, 2019. "HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction," Papers 1908.07999, arXiv.org, revised Nov 2019.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yu Zhao & Huaming Du & Ying Liu & Shaopeng Wei & Xingyan Chen & Fuzhen Zhuang & Qing Li & Ji Liu & Gang Kou, 2022. "Stock Movement Prediction Based on Bi-typed Hybrid-relational Market Knowledge Graph via Dual Attention Networks," Papers 2201.04965, arXiv.org, revised Jan 2022.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    2. Nathan Jensen, 2007. "International institutions and market expectations: Stock price responses to the WTO ruling on the 2002 U.S. steel tariffs," The Review of International Organizations, Springer, vol. 2(3), pages 261-280, September.
    3. Saggese, Pietro & Belmonte, Alessandro & Dimitri, Nicola & Facchini, Angelo & Böhme, Rainer, 2023. "Arbitrageurs in the Bitcoin ecosystem: Evidence from user-level trading patterns in the Mt. Gox exchange platform," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 251-270.
    4. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, October.
    5. Lucena, Pierre & Fugueiredo, Antonio Carlos, 2004. "Pressupostos de Eficiência de Mercado: um estudo empírico na Bovespa [Assumptions of Market Efficiency: an empirical analysis at Bovespa/Brazil]," MPRA Paper 40884, University Library of Munich, Germany.
    6. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    7. Lu Zhang, 2017. "The Investment CAPM," European Financial Management, European Financial Management Association, vol. 23(4), pages 545-603, September.
    8. Lu Zhang, 2019. "Q-factors and Investment CAPM," NBER Working Papers 26538, National Bureau of Economic Research, Inc.
    9. Chhabra, Damini & Gupta, Mohit, 2022. "Calendar anomalies in commodity markets for natural resources: Evidence from India," Resources Policy, Elsevier, vol. 79(C).
    10. Trabelsi, Mohamed Ali, 2010. "Choix de portefeuille: comparaison des différentes stratégies [Portfolio selection: comparison of different strategies]," MPRA Paper 82946, University Library of Munich, Germany, revised 01 Dec 2010.
    11. Jan A. Kempkes & Francesco Suprano & Andreas Wömpener, 2023. "An empirical evaluation of dynamic approaches for estimating firms’ expected cost of equity capital," The Financial Review, Eastern Finance Association, vol. 58(4), pages 859-886, November.
    12. Ditimi Amassoma & O. Adeleke, 2018. "Testing for the Causality between Interest Rate and Stock Market Performance in Nigeria," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 109-124.
    13. Lucena, Pierre & Figueiredo, Antonio Carlos & Lachtermacher, Gerson, 2008. "Critérios de formação de carteiras de ativos através de hierarchical clusters [Criteria of portfolio formation of stocks through hierarchical clusters]," MPRA Paper 38105, University Library of Munich, Germany.
    14. Godfrey Akileng & Eric Nzibonera & Micheal Mutegana, 2019. "The Influence of Foreign Exchange Volatility, Interest Rates on the Stock Performance of Uganda Securities Exchange," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 8(2), pages 1-1.
    15. Jaime Alberto Vásquez & John Willmer Escobar & Diego Fernando Manotas, 2021. "AHP–TOPSIS Methodology for Stock Portfolio Investments," Risks, MDPI, vol. 10(1), pages 1-20, December.
    16. Fu, Jie & Zhang, Xiaoqi & Zhou, Wenyuan & Lyu, Yang, 2024. "A continuous heterogeneous agent model for multi-asset pricing and portfolio construction under market matching friction," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 267-283.
    17. Majeed, Raseena & Masih, Mansur, 2016. "Impact of macroeconomic variables on shariah stock markets: evidence from Malaysia based on ARDL approach," MPRA Paper 106118, University Library of Munich, Germany.
    18. Ho, Sin-Yu, 2017. "The Macroeconomic Determinants of Stock Market Development: Evidence from Malaysia," MPRA Paper 77232, University Library of Munich, Germany.
    19. Kiran Lohano & Muhammad Kashif, 2018. "Testing asset pricing models on the Pakistan Stock Exchange," Business Review, School of Economics and Social Sciences, IBA Karachi, vol. 13(2), pages 1-19, July-Dece.
    20. Sidika Gulfem Bayram, 2017. "Rational–Irrational Investor Sentiments and Emerging Stock Market Returns: A Comparison from Turkey," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 16(3), pages 219-245, December.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2010.15586. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.