IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/64497.html
   My bibliography  Save this paper

Financial Market Efficiency Should be Gauged in Relative Rather than Absolute Terms

Author

Listed:
  • Da Silva, Sergio

Abstract

Economists assess the efficiency of financial markets in absolute, all-or-nothing terms. However, this is at odds with a no-nonsense physics approach. Here, I describe how the relative efficiency of markets can be gauged taking advantage of algorithmic complexity theory. This is not physics-envy because the approach is superior in considering the proper randomness present in complex financial markets.

Suggested Citation

  • Da Silva, Sergio, 2015. "Financial Market Efficiency Should be Gauged in Relative Rather than Absolute Terms," MPRA Paper 64497, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:64497
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/64497/1/MPRA_paper_64497.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Meredith Beechey & David Gruen & James Vickery, 2000. "The Efficient Market Hypothesis: A Survey," RBA Research Discussion Papers rdp2000-01, Reserve Bank of Australia.
    2. Sergio Da Silva & Roberto Meurer & Caio Guttler, 2008. "Is the Brazilian stockmarket efficient?," Economics Bulletin, AccessEcon, vol. 7(1), pages 1-16.
    3. Giglio, Ricardo & Matsushita, Raul & Figueiredo, Annibal & Gleria, Iram & Da Silva, Sergio, 2008. "Algorithmic complexity theory and the relative efficiency of financial markets," MPRA Paper 8704, University Library of Munich, Germany.
    4. repec:ebl:ecbull:v:7:y:2008:i:1:p:1-16 is not listed on IDEAS
    5. Giglio, Ricardo & Da Silva, Sergio, 2009. "Ranking the stocks listed on Bovespa according to their relative efficiency," MPRA Paper 22720, University Library of Munich, Germany.
    6. Cleiton Taufemback & Ricardo Giglio & Sergio Da Silva, 2011. "Algorithmic complexity theory detects decreases in the relative efficiency of stock markets in the aftermath of the 2008 financial crisis," Economics Bulletin, AccessEcon, vol. 31(2), pages 1631-1647.
    7. repec:ebl:ecbull:v:7:y:2008:i:6:p:1-12 is not listed on IDEAS
    8. Giglio, Ricardo & Matsushita, Raul & Figueiredo, Annibal & Gleria, Iram & Da Silva, Sergio, 2008. "Algorithmic complexity theory and the relative efficiency of financial markets - Updated," MPRA Paper 11150, University Library of Munich, Germany.
    9. Sergio Da Silva & Raul Matsushita & Ricardo Giglio, 2008. "The relative efficiency of stockmarkets," Economics Bulletin, AccessEcon, vol. 7(6), pages 1-12.
    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. Kei Takeuchi & Akimichi Takemura & Masayuki Kumon, 2011. "New Procedures for Testing Whether Stock Price Processes are Martingales," Computational Economics, Springer;Society for Computational Economics, vol. 37(1), pages 67-88, January.
    2. Lahmiri, Salim & Bekiros, Stelios & Avdoulas, Christos, 2018. "Time-dependent complexity measurement of causality in international equity markets: A spatial approach," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 215-219.
    3. Li, Yiying & Ren, Xiaohang & Taghizadeh-Hesary, Farhad, 2023. "Vulnerability of sustainable markets to fossil energy shocks," Resources Policy, Elsevier, vol. 85(PB).
    4. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.
    5. Brandouy, Olivier & Delahaye, Jean-Paul & Ma, Lin & Zenil, Hector, 2014. "Algorithmic complexity of financial motions," Research in International Business and Finance, Elsevier, vol. 30(C), pages 336-347.
    6. Wang, Fang & Gacesa, Marko, 2023. "Semi-strong efficient market of Bitcoin and Twitter: An analysis of semantic vector spaces of extracted keywords and light gradient boosting machine models," International Review of Financial Analysis, Elsevier, vol. 88(C).
    7. Lucio Maria Calcagnile & Fulvio Corsi & Stefano Marmi, 2016. "Entropy and efficiency of the ETF market," Papers 1609.04199, arXiv.org.
    8. Lucio Maria Calcagnile & Fulvio Corsi & Stefano Marmi, 2020. "Entropy and Efficiency of the ETF Market," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 143-184, January.
    9. Olivier Brandouy & Jean-Paul Delahaye & Lin Ma, 2015. "Estimating the Algorithmic Complexity of Stock Markets," Papers 1504.04296, arXiv.org.
    10. Abounoori, Esmaiel & Shahrazi, Mahdi & Rasekhi, Saeed, 2012. "An investigation of Forex market efficiency based on detrended fluctuation analysis: A case study for Iran," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3170-3179.
    11. Brouty, Xavier & Garcin, Matthieu, 2024. "Fractal properties, information theory, and market efficiency," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    12. Alvarez-Ramirez, J. & Rodriguez, E. & Espinosa-Paredes, G., 2012. "A partisan effect in the efficiency of the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4923-4932.
    13. Cristescu, C.P. & Stan, C. & Scarlat, E.I., 2009. "The dynamics of exchange rate time series and the chaos game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4845-4855.
    14. Andrey Shternshis & Piero Mazzarisi, 2022. "Variance of entropy for testing time-varying regimes with an application to meme stocks," Papers 2211.05415, arXiv.org, revised Jun 2023.
    15. Shternshis, Andrey & Mazzarisi, Piero & Marmi, Stefano, 2022. "Measuring market efficiency: The Shannon entropy of high-frequency financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    16. Giglio, Ricardo & Da Silva, Sergio, 2009. "Ranking the stocks listed on Bovespa according to their relative efficiency," MPRA Paper 22720, University Library of Munich, Germany.
    17. Oxelheim, Lars & Rafferty, Michael, 2005. "On the static efficiency of secondary bond markets," Journal of Multinational Financial Management, Elsevier, vol. 15(2), pages 117-135, April.
    18. Ortiz-Cruz, Alejandro & Rodriguez, Eduardo & Ibarra-Valdez, Carlos & Alvarez-Ramirez, Jose, 2012. "Efficiency of crude oil markets: Evidences from informational entropy analysis," Energy Policy, Elsevier, vol. 41(C), pages 365-373.
    19. Amaresh Das, 2011. "Martingales, Efficient Market Hypothesis and Kolmogorov’s Complexity Theory," Information Management and Business Review, AMH International, vol. 2(6), pages 252-258.
    20. Roland Rothenstein, 2018. "Quantification of market efficiency based on informational-entropy," Papers 1812.02371, arXiv.org.

    More about this item

    Keywords

    Algorithmic complexity theory; Efficient market hypothesis; Financial market efficiency; Relative market efficiency; Mild type I randomness; Wild type II randomness;
    All these keywords.

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:pra:mprapa:64497. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.