IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v353y2005icp463-479.html
   My bibliography  Save this article

Non-linear forecasting in high-frequency financial time series

Author

Listed:
  • Strozzi, F.
  • Zaldívar, J.M.

Abstract

A new methodology based on state space reconstruction techniques has been developed for trading in financial markets. The methodology has been tested using 18 high-frequency foreign exchange time series. The results are in apparent contradiction with the efficient market hypothesis which states that no profitable information about future movements can be obtained by studying the past prices series. In our (off-line) analysis positive gain may be obtained in all those series. The trading methodology is quite general and may be adapted to other financial time series. Finally, the steps for its on-line application are discussed.

Suggested Citation

  • Strozzi, F. & Zaldívar, J.M., 2005. "Non-linear forecasting in high-frequency financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 463-479.
    • Handle: RePEc:eee:phsmap:v:353:y:2005:i:c:p:463-479
    DOI: 10.1016/j.physa.2005.01.047
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437105000750
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2005.01.047?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. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
    2. Strozzi, Fernanda & Zaldı́var, José-Manuel & Zbilut, Joseph P, 2002. "Application of nonlinear time series analysis techniques to high-frequency currency exchange data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(3), pages 520-538.
    3. 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.
    4. Ohira, Toru & Sazuka, Naoya & Marumo, Kouhei & Shimizu, Tokiko & Takayasu, Misako & Takayasu, Hideki, 2002. "Predictability of currency market exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 308(1), pages 368-374.
    5. Fabrizio Lillo & J. Doyne Farmer & Rosario N. Mantegna, 2003. "Master curve for price-impact function," Nature, Nature, vol. 421(6919), pages 129-130, January.
    6. Johnson, Neil F. & Jefferies, Paul & Hui, Pak Ming, 2003. "Financial Market Complexity," OUP Catalogue, Oxford University Press, number 9780198526650.
    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. Strozzi, Fernanda & Zaldívar, José-Manuel & Zbilut, Joseph P., 2007. "Recurrence quantification analysis and state space divergence reconstruction for financial time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 487-499.

    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. Strozzi, Fernanda & Comenges, José-Manuel Zaldívar, 2006. "Towards a non-linear trading strategy for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 28(3), pages 601-615.
    2. Strozzi, Fernanda & Zaldívar, José-Manuel & Zbilut, Joseph P., 2007. "Recurrence quantification analysis and state space divergence reconstruction for financial time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 487-499.
    3. J. Doyne Farmer & John Geanakoplos, 2008. "The virtues and vices of equilibrium and the future of financial economics," Papers 0803.2996, arXiv.org.
    4. Zhang, Wei & Bi, Zhengzheng & Shen, Dehua, 2017. "Investor structure and the price–volume relationship in a continuous double auction market: An agent-based modeling perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 345-355.
    5. Stefan Nagel, 2013. "Empirical Cross-Sectional Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 5(1), pages 167-199, November.
    6. You‐How Go & Wee‐Yeap Lau, 2023. "What do we know about informational efficiency? Three puzzles and the new direction forward," Journal of Economic Surveys, Wiley Blackwell, vol. 37(4), pages 1489-1525, September.
    7. Li, Da-Ye & Nishimura, Yusaku & Men, Ming, 2014. "Fractal markets: Liquidity and investors on different time horizons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 144-151.
    8. Moews, Ben & Ibikunle, Gbenga, 2020. "Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    9. Oldham, Matthew, 2020. "Quantifying the concerns of Dimon and Buffett with data and computation," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    10. Duygu Ider & Stefan Lessmann, 2022. "Forecasting Cryptocurrency Returns from Sentiment Signals: An Analysis of BERT Classifiers and Weak Supervision," Papers 2204.05781, arXiv.org, revised Mar 2023.
    11. Felicia Ramona Birau, 2011. "An Analysis Of Weak-Form Efficiency On The Bucharest Stock Exchange," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, vol. 3(39), pages 194-205.
    12. Haugom, Erik & Ullrich, Carl J., 2012. "Market efficiency and risk premia in short-term forward prices," Energy Economics, Elsevier, vol. 34(6), pages 1931-1941.
    13. Roland Rothenstein, 2018. "Quantification of market efficiency based on informational-entropy," Papers 1812.02371, arXiv.org.
    14. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability Of Technical Trading Rules In Us Futures Markets: A Data Snooping Free Test," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19011, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    15. Sahar Afshan & Arshian Sharif & Abdelmohsen A. Nassani & Muhammad M. Q. Abro & Rubeena Batool & Khalid Zaman, 2021. "The role of information and communication technology (internet penetration) on Asian stock market efficiency: Evidence from quantile‐on‐quantile cointegration and causality approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2307-2324, April.
    16. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    17. repec:idn:journl:v:1:y:2019:i:sp1:p:1-26 is not listed on IDEAS
    18. Vasilios Sogiakas, 2017. "Efficiency of the UK Stock Exchange," Journal of Risk & Control, Risk Market Journals, vol. 4(1), pages 51-69.
    19. Kizilaslan, Recep & Freund, Steven & Iseri, Ali, 2016. "A data analytic approach to forecasting daily stock returns in an emerging marketAuthor-Name: Oztekin, Asil," European Journal of Operational Research, Elsevier, vol. 253(3), pages 697-710.
    20. Stephanie-Carolin Grosche, 2014. "What Does Granger Causality Prove? A Critical Examination of the Interpretation of Granger Causality Results on Price Effects of Index Trading in Agricultural Commodity Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 279-302, June.
    21. Yaya, OlaOluwa S. & Vo, Xuan Vinh & Adekoya, Oluwasegun B., 2021. "Market Efficiency of Asian Stocks: Evidence based on Narayan-Liu-Westerlund GARCH-based Unit root test," MPRA Paper 109828, University Library of Munich, Germany.

    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:eee:phsmap:v:353:y:2005:i:c:p:463-479. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.