IDEAS home Printed from https://ideas.repec.org/a/vrs/foeste/v19y2019i1p114-125n8.html
   My bibliography  Save this article

Parameterized Trade on the Futures Market on the WIG20

Author

Listed:
  • Piekunko-Mantiuk Iwona

    (Białystok University of Technology, Faculty of Engineering Management, Ojca Tarasiuka # 2 Street, 16-001Kleosin, Poland)

Abstract

Research background: Market participants have been trying to forecast future price movements and create tools to facilitate making the right investment decisions since the beginning of the operation of stock exchanges. As a result, there are an increasing number of methods, tools, strategies and models to make the decision process which is becoming extremely complicated.Purpose: to maximize the simplification of trade rules and to check whether it is possible to parameterize transactions based on the length of price movements in order that the system built in this way would generate profits.Research methodology: empirical research was conducted on data from the period between 20/01/1998 and 29/06/2018 covering listing futures contracts for the WIG20. First, the length of the price movements was determined according to the closing rate, then the frequency of individual lengths of the price movements was determined so transaction parameters were fixed. Next, the parameters were optimized and the rates of return from the tested options were examined.Result: It is possible to parameterize transactions based on the length of price movements and to create a simple investment strategy which generates profits. In the audited period, the optimal length of traffic was 25 points with a simultaneous use of a profit/loss ratio of 1 : 1, 1 : 2 or 1 : 3.Novelty: an original investment strategy based on the parameterization of transactions that is based on length of price movement and profit/loss ratio.

Suggested Citation

  • Piekunko-Mantiuk Iwona, 2019. "Parameterized Trade on the Futures Market on the WIG20," Folia Oeconomica Stetinensia, Sciendo, vol. 19(1), pages 114-125, June.
    • Handle: RePEc:vrs:foeste:v:19:y:2019:i:1:p:114-125:n:8
    DOI: 10.2478/foli-2019-0008
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/foli-2019-0008
    Download Restriction: no
    File URL: https://libkey.io/10.2478/foli-2019-0008?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
    ---><---

    References listed on IDEAS

    as
    1. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda & Dirk Helbing, 2013. "Are Random Trading Strategies More Successful than Technical Ones?," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-13, July.
    2. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    3. R. Rosillo & D. de la Fuente & J. A. L. Brugos, 2013. "Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies," Applied Economics, Taylor & Francis Journals, vol. 45(12), pages 1541-1550, April.
    4. J. B. Satinover & D. Sornette, 2007. "”Illusion of control” in Time-Horizon Minority and Parrondo Games," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 60(3), pages 369-384, December.
    5. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    6. Terence Tai-Leung Chong & Wing-Kam Ng & Venus Khim-Sen Liew, 2014. "Revisiting the Performance of MACD and RSI Oscillators," JRFM, MDPI, vol. 7(1), pages 1-12, February.
    7. Gil Cohen & Elinor Cabiri, 2015. "Can technical oscillators outperform the buy and hold strategy?," Applied Economics, Taylor & Francis Journals, vol. 47(30), pages 3189-3197, June.
    8. repec:bla:jfinan:v:53:y:1998:i:5:p:1775-1798 is not listed on IDEAS
    9. repec:icf:icfjaf:v:20:y:2014:i:1:p:76-91 is not listed on IDEAS
    10. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda, 2012. "The beneficial role of random strategies in social and financial systems," Papers 1209.5881, arXiv.org, revised Jan 2013.
    11. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda, 2014. "Micro and Macro Benefits of Random Investments in Financial Markets," Papers 1405.5805, arXiv.org.
    12. A. E. Biondo & A. Pluchino & A. Rapisarda & D. Helbing, 2013. "Are random trading strategies more successful than technical ones?," Papers 1303.4351, arXiv.org, revised Jul 2013.
    13. 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.
    14. Yu, Hao & Nartea, Gilbert V. & Gan, Christopher & Yao, Lee J., 2013. "Predictive ability and profitability of simple technical trading rules: Recent evidence from Southeast Asian stock markets," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 356-371.
    Full references (including those not matched with items on IDEAS)

    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. Krzysztof Borowski & Izabela Pruchnicka-Grabias, 2019. "Optimal lengths of moving averages for the MACD oscillator for companies listed on the Warsaw Stock Exchange," Bank i Kredyt, Narodowy Bank Polski, vol. 50(5), pages 457-478.
    2. Alessandro Pluchino & Alessio Emanuele Biondo & Andrea Rapisarda, 2018. "Talent Versus Luck: The Role Of Randomness In Success And Failure," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(03n04), pages 1-31, May.
    3. Caserta, Maurizio & Pluchino, Alessandro & Rapisarda, Andrea & Spagano, Salvatore, 2021. "Why lot? How sortition could help representative democracy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    4. Biondo, A.E. & Pluchino, A. & Rapisarda, A., 2018. "Modeling surveys effects in political competitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 714-726.
    5. Alessio Emanuele Biondo & Alfio Giarlotta & Alessandro Pluchino & Andrea Rapisarda, 2016. "Perfect Information vs Random Investigation: Safety Guidelines for a Consumer in the Jungle of Product Differentiation," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-26, January.
    6. Biondo, Alessio Emanuele, 2017. "Learning to forecast, risk aversion, and microstructural aspects of financial stability," Economics Discussion Papers 2017-104, Kiel Institute for the World Economy (IfW Kiel).
    7. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, December.
    8. Alessandro Pluchino & Giulio Burgio & Andrea Rapisarda & Alessio Emanuele Biondo & Alfredo Pulvirenti & Alfredo Ferro & Toni Giorgino, 2019. "Exploring the role of interdisciplinarity in physics: Success, talent and luck," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-15, June.
    9. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    10. Lukas Menkhoff & Mark P. Taylor, 2007. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 936-972, December.
    11. Andrew Phiri, 2022. "Changing efficiency of BRICS currency markets during the COVID-19 pandemic," Economic Change and Restructuring, Springer, vol. 55(3), pages 1673-1699, August.
    12. Anghel, Dan Gabriel, 2021. "Data Snooping Bias in Tests of the Relative Performance of Multiple Forecasting Models," Journal of Banking & Finance, Elsevier, vol. 126(C).
    13. Tran Phuoc & Pham Thi Kim Anh & Phan Huy Tam & Chien V. Nguyen, 2024. "Applying machine learning algorithms to predict the stock price trend in the stock market – The case of Vietnam," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.
    14. Alessandro Pluchino & Alessio. E. Biondo & Andrea Rapisarda, 2018. "Exploring the role of talent and luck in getting success," Papers 1811.05206, arXiv.org.
    15. Alhashel, Bader S. & Almudhaf, Fahad W. & Hansz, J. Andrew, 2018. "Can technical analysis generate superior returns in securitized property markets? Evidence from East Asia markets," Pacific-Basin Finance Journal, Elsevier, vol. 47(C), pages 92-108.
    16. Dan Gabriel ANGHEL, 2017. "Intraday Market Efficiency for a Typical Central and Eastern European Stock Market: The Case of Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 88-109, September.
    17. Menkhoff, Lukas, 2010. "The use of technical analysis by fund managers: International evidence," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2573-2586, November.
    18. Yensen Ni & Min-Yuh Day & Yirung Cheng & Paoyu Huang, 2022. "Can investors profit by utilizing technical trading strategies? Evidence from the Korean and Chinese stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    19. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    20. Alessio Emanuele Biondo, 2018. "Order book microstructure and policies for financial stability," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 35(1), pages 196-218, March.

    More about this item

    Keywords

    parameterized trade; futures contract; futures on WIG20; futures contract market;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:vrs:foeste:v:19:y:2019:i:1:p:114-125:n:8. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.