IDEAS home Printed from https://ideas.repec.org/a/spr/comgts/v9y2012i1p89-107.html
   My bibliography  Save this article

Regime-switching recurrent reinforcement learning for investment decision making

Author

Listed:
  • Dietmar Maringer
  • Tikesh Ramtohul

Abstract

No abstract is available for this item.

Suggested Citation

  • Dietmar Maringer & Tikesh Ramtohul, 2012. "Regime-switching recurrent reinforcement learning for investment decision making," Computational Management Science, Springer, vol. 9(1), pages 89-107, February.
    • Handle: RePEc:spr:comgts:v:9:y:2012:i:1:p:89-107
    DOI: 10.1007/s10287-011-0131-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10287-011-0131-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10287-011-0131-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sentana, Enrique & Wadhwani, Sushil B, 1992. "Feedback Traders and Stock Return Autocorrelations: Evidence from a Century of Daily Data," Economic Journal, Royal Economic Society, vol. 102(411), pages 415-425, March.
    2. John Moody & Lizhong Wu, "undated". "Optimization of Trading Systems and Portfolios," Computing in Economics and Finance 1997 55, Society for Computational Economics.
    3. LeBaron, Blake, 1992. "Some Relations between Volatility and Serial Correlations in Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 65(2), pages 199-219, April.
    4. Koutmos, Gregory, 1997. "Feedback trading and the autocorrelation pattern of stock returns: further empirical evidence," Journal of International Money and Finance, Elsevier, vol. 16(4), pages 625-636, August.
    5. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    6. Michael D. McKenzie & Robert W. Faff, 2003. "The Determinants of Conditional Autocorrelation in Stock Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 26(2), pages 259-274, June.
    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. L.-F. Pau, 2014. "Discovering the dynamics of smart business networks," Computational Management Science, Springer, vol. 11(4), pages 445-458, October.
    2. Jin Zhang & Dietmar Maringer, 2016. "Using a Genetic Algorithm to Improve Recurrent Reinforcement Learning for Equity Trading," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 551-567, April.
    3. Xiangyu Cui & Xun Li & Yun Shi & Si Zhao, 2023. "Discrete-Time Mean-Variance Strategy Based on Reinforcement Learning," Papers 2312.15385, arXiv.org.

    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. Chau, Frankie & Deesomsak, Rataporn & Lau, Marco C.K., 2011. "Investor sentiment and feedback trading: Evidence from the exchange-traded fund markets," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 292-305.
    2. Chen, Carl R. & Su, Yuli & Huang, Ying, 2008. "Hourly index return autocorrelation and conditional volatility in an EAR-GJR-GARCH model with generalized error distribution," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 789-798, September.
    3. Hou, Yang & Li, Steven, 2014. "The impact of the CSI 300 stock index futures: Positive feedback trading and autocorrelation of stock returns," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 319-337.
    4. Chau, Frankie & Deesomsak, Rataporn, 2015. "Business cycle variation in positive feedback trading: Evidence from the G-7 economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 35(C), pages 147-159.
    5. Kinnunen, Jyri, 2017. "Dynamic cross-autocorrelation in stock returns," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 162-173.
    6. Fotini Economou & Konstantinos Gavriilidis & Bartosz Gebka & Vasileios Kallinterakis, 2022. "Feedback trading: a review of theory and empirical evidence," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 15(4), pages 429-476, February.
    7. Schuppli, Michael & Bohl, Martin T., 2010. "Do foreign institutional investors destabilize China's A-share markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(1), pages 36-50, February.
    8. Michael Schuppli & Martin T. Bohl, 2009. "Do Foreign Institutional Investors Destabilize China’s A-Share Markets?," CQE Working Papers 0909, Center for Quantitative Economics (CQE), University of Muenster.
    9. Martin T. Bohl & Pierre Siklos, 2004. "Empirical Evidence on Feedback Trading in Mature and Emerging Stock Markets," Research Paper Series 137, Quantitative Finance Research Centre, University of Technology, Sydney.
    10. Kusen, Alex & Rudolf, Markus, 2019. "Feedback trading: Strategies during day and night with global interconnectedness," Research in International Business and Finance, Elsevier, vol. 48(C), pages 438-463.
    11. Bohl, Martin T. & Brzeszczynski, Janusz, 2006. "Do institutional investors destabilize stock prices? evidence from an emerging market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(4), pages 370-383, October.
    12. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    13. Siklos, Pierre L. & Bohl, Martin T., 2005. "Trading Behavior During Stock Market Downturns: The Dow, 1915 - 2004," Working Paper Series 2005,7, European University Viadrina Frankfurt (Oder), The Postgraduate Research Programme Capital Markets and Finance in the Enlarged Europe.
    14. Gregory Koutmos, 1999. "Asymmetric index stock returns: evidence from the G-7," Applied Economics Letters, Taylor & Francis Journals, vol. 6(12), pages 817-820.
    15. Klein, Arne C., 2013. "Time-variations in herding behavior: Evidence from a Markov switching SUR model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 291-304.
    16. Toshiaki Watanabe, 2002. "Margin requirements, positive feedback trading, and stock return autocorrelations: the case of Japan," Applied Financial Economics, Taylor & Francis Journals, vol. 12(6), pages 395-403.
    17. Imran Riaz MALIK* & Attaullah SHAH*, 2014. "Market Varying Conditional Risk-Return Relationship," Pakistan Journal of Applied Economics, Applied Economics Research Centre, vol. 24(2), pages 121-142.
    18. Michael Thorpe, 2005. "Financial Sector Reform in China," CERT Discussion Papers 0502, Centre for Economic Reform and Transformation, Heriot Watt University.
    19. Henryk Gurgul & Paweł Majdosz, 2006. "The impact of institutional investors on risk and stock return autocorrelations in the context of the Polish pension reform," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(2), pages 5-30.
    20. McKenzie, Michael D. & Kim, Suk-Joong, 2007. "Evidence of an asymmetry in the relationship between volatility and autocorrelation," International Review of Financial Analysis, Elsevier, vol. 16(1), pages 22-40.

    More about this item

    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:spr:comgts:v:9:y:2012:i:1:p:89-107. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.