IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0284918.html
   My bibliography  Save this article

Using Heatmap Visualization to assess the performance of the DJ30 and NASDAQ100 Indices under diverse VMA trading rules

Author

Listed:
  • Yuhsin Chen
  • Paoyu Huang
  • Min-Yuh Day
  • Yensen Ni
  • Mei-Chu Liang

Abstract

We investigate whether using various VMA trading rules would improve investment performance due to the flexibility of VMA trading rules and the aid of Heatmap Visualization. Previously, investors frequently chose the best performance derived from limited VMA trading rules. However, our new design, which can display all results using Heatmap Visualization, shows that the NASDAQ100 index outperforms the DJ30 index and that weekly data outperforms daily data when measured by annualized return. These findings may be useful to those who trade index ETFs tracking the DJ30 and NASDAQ100 indices, as well as investors making investment decisions, and may contribute to the existing literature by evaluating the outcomes of VMA trading rules and providing insights for index ETF investors using a heatmap matrix, which is rarely explored and presented in the relevant literature.

Suggested Citation

  • Yuhsin Chen & Paoyu Huang & Min-Yuh Day & Yensen Ni & Mei-Chu Liang, 2023. "Using Heatmap Visualization to assess the performance of the DJ30 and NASDAQ100 Indices under diverse VMA trading rules," PLOS ONE, Public Library of Science, vol. 18(5), pages 1-16, May.
    • Handle: RePEc:plo:pone00:0284918
    DOI: 10.1371/journal.pone.0284918
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0284918
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0284918&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0284918?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. Liyun Zhou & Jialiang Huang, 2019. "Investor trading behaviour and stock price crash risk," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 227-240, January.
    2. Maria Rosa Borges, 2010. "Efficient market hypothesis in European stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 16(7), pages 711-726.
    3. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    4. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    5. 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.
    6. Cysne, Rubens Penha & Turchick, David, 2010. "Welfare costs of inflation when interest-bearing deposits are disregarded: A calculation of the bias," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1015-1030, June.
    7. Noman Arshed & Rukhsana Kalim, 2021. "Modelling demand and supply of Islamic banking deposits," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2813-2831, April.
    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. Christiane Goodfellow & Dirk Schiereck & Steffen Wippler, 2013. "Are behavioural finance equity funds a superior investment? A note on fund performance and market efficiency," Journal of Asset Management, Palgrave Macmillan, vol. 14(2), pages 111-119, April.
    2. David Peón & Anxo Calvo, 2012. "Using Behavioral Economics to Analyze Credit Policies in the Banking Industry," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 145-160.
    3. Stephan Schulmeister, 2000. "Technical Analysis and Exchange Rate Dynamics," WIFO Studies, WIFO, number 25857, June.
    4. Giuseppe Garofalo, 2014. "Irreducible complexities: from Gödel and Turing to the paradigm of Imperfect Knowledge Economics," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3463-3474, November.
    5. Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
    6. J. Doyne Farmer, 2002. "Market force, ecology and evolution," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(5), pages 895-953, November.
    7. Ni, Yensen & Cheng, Yirung & Huang, Paoyu & Day, Min-Yuh, 2018. "Trading strategies in terms of continuous rising (falling) prices or continuous bullish (bearish) candlesticks emitted," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 188-204.
    8. Akber, Ushna & Muhammad, Nabeel, 2013. "Is Pakistan Stock Market moving towards Weak-form efficiency? Evidence from the Karachi Stock Exchange and the Random Walk Nature of free-float of shares of KSE 30 Index," MPRA Paper 49128, University Library of Munich, Germany.
    9. Mustapha Chaffai & Imed Medhioub, 2014. "Behavioral Finance: An Empirical Study of the Tunisian Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 4(3), pages 527-538.
    10. Bradley Jones, 2015. "Asset Bubbles: Re-thinking Policy for the Age of Asset Management," IMF Working Papers 2015/027, International Monetary Fund.
    11. Xu, Hedong & Tian, Cunzhi & Ye, Wenxing & Fan, Suohai, 2018. "Effects of investors’ power correlations in the power-based game on networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 424-432.
    12. Glaser, Markus & Nöth, Markus & Weber, Martin, 2003. "Behavioral finance," Papers 03-14, Sonderforschungsbreich 504.
    13. Shi, Huai-Long & Zhou, Wei-Xing, 2017. "Wax and wane of the cross-sectional momentum and contrarian effects: Evidence from the Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 397-407.
    14. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034, Decembrie.
    15. Jürgen Huber & Michael Kirchler & Thomas Stöckl, 2010. "The hot hand belief and the gambler’s fallacy in investment decisions under risk," Theory and Decision, Springer, vol. 68(4), pages 445-462, April.
    16. Marcin Rzeszutek & Adam Szyszka & Monika Czerwonka, 2015. "Investors’ Expertise, Personality Traits and Susceptibility to Behavioral Biases in the Decision Making Process," Contemporary Economics, Vizja University, vol. 9(3), September.
    17. Frey, Bruno S. & Gallus, Jana, 2014. "Aggregate effects of behavioral anomalies: A new research area," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 8, pages 1-15.
    18. Sonntag, Dominik, 2018. "Die Theorie der fairen geometrischen Rendite [The Theory of Fair Geometric Returns]," MPRA Paper 87082, University Library of Munich, Germany.
    19. Erdas Mehmet Levent, 2019. "Validity of Weak-Form Market Efficiency in Central and Eastern European Countries (CEECs): Evidence from Linear and Nonlinear Unit Root Tests," Review of Economic Perspectives, Sciendo, vol. 19(4), pages 399-428, December.
    20. Fernando Rubio, 2005. "Eficiencia De Mercado, Administracion De Carteras De Fondos Y Behavioural Finance," Finance 0503028, University Library of Munich, Germany, revised 23 Jul 2005.

    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:plo:pone00:0284918. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.