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A multiscale entropy approach for market efficiency

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  • Alvarez-Ramirez, Jose
  • Rodriguez, Eduardo
  • Alvarez, Jesus

Abstract

Motivated by the recently evolutionary economic theories, we propose to study market efficiency from an informational entropy viewpoint. The basic idea is that, rather than being an all-or-none concept as in classic economic theories, market efficiency changes over time and over time horizons. Within this framework, market efficiency is measured in terms of the patterns contained in the price changes sequence relative to the patterns in a random sequence. In line with evolutionary finance ideas, the empirical results for the Dow Jones Index showed that the degree of market efficiency varies over time and is dependent of the time scale. In general, the DJI is more efficient for shorter (about days) than for longer (about months and quarters) time scales. On the other hand, the market efficiency exhibits a cyclic behavior with two dominant periods of about 4.5 and 22years. It is apparent that the 4.5-year cycle is related to inventory (Kitchin-type) effects, while the 22-year cycle to structure inversion (Kondriatev-type) cycles.

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  • Alvarez-Ramirez, Jose & Rodriguez, Eduardo & Alvarez, Jesus, 2012. "A multiscale entropy approach for market efficiency," International Review of Financial Analysis, Elsevier, vol. 21(C), pages 64-69.
    • Handle: RePEc:eee:finana:v:21:y:2012:i:c:p:64-69
    DOI: 10.1016/j.irfa.2011.12.001
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    1. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    2. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    3. Risso, Wiston Adrián, 2008. "The informational efficiency and the financial crashes," Research in International Business and Finance, Elsevier, vol. 22(3), pages 396-408, September.
    4. Ito, Mikio & Sugiyama, Shunsuke, 2009. "Measuring the degree of time varying market inefficiency," Economics Letters, Elsevier, vol. 103(1), pages 62-64, April.
    5. repec:ebl:ecbull:v:7:y:2008:i:6:p:1-12 is not listed on IDEAS
    6. 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.
    7. Oh, Gabjin & Kim, Seunghwan & Eom, Cheoljun, 2007. "Market efficiency in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 209-212.
    8. Burton Malkiel & Sendhil Mullainathan & Bruce Stangle, 2005. "Market Efficiency versus Behavioral Finance," Journal of Applied Corporate Finance, Morgan Stanley, vol. 17(3), pages 124-136, June.
    9. J. Doyne Farmer & Andrew W. Lo, 1999. "Frontiers of Finance: Evolution and Efficient Markets," Working Papers 99-06-039, Santa Fe Institute.
    10. Darbellay, Georges A & Wuertz, Diethelm, 2000. "The entropy as a tool for analysing statistical dependences in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 429-439.
    11. Les Gulko, 1999. "The Entropic Market Hypothesis," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 293-329.
    12. Jeremy C. Stein, 2009. "Presidential Address: Sophisticated Investors and Market Efficiency," Journal of Finance, American Finance Association, vol. 64(4), pages 1517-1548, August.
    13. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
    14. Sergio Da Silva & Raul Matsushita & Ricardo Giglio, 2008. "The relative efficiency of stockmarkets," Economics Bulletin, AccessEcon, vol. 7(6), pages 1-12.
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    Cited by:

    1. Alvarez-Ramirez, Jose & Rodriguez, Eduardo, 2021. "A singular value decomposition entropy approach for testing stock market efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
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    3. Billio, Monica & Casarin, Roberto & Costola, Michele & Pasqualini, Andrea, 2016. "An entropy-based early warning indicator for systemic risk," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 42-59.
    4. Ioan Roxana, 2020. "Capital Market Correlations Structure During The Covid-19 Crisis," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 67-79, December.
    5. Aurelio F. Bariviera & Luciano Zunino & M. Belen Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "Efficiency and credit ratings: a permutation-information-theory analysis," Papers 1509.01839, arXiv.org.
    6. Alonso-Rivera, Angélica & Cruz-Aké, Salvador & Venegas-Martínez, Francisco, 2014. "Impact of Monetary Policy on Financial Markets Efficiency and Speculative Bubbles: A Non-linear Entropy-based Approach," MPRA Paper 56127, University Library of Munich, Germany.
    7. Wang, Jingjing & Wang, Xiaoyang, 2021. "COVID-19 and financial market efficiency: Evidence from an entropy-based analysis," Finance Research Letters, Elsevier, vol. 42(C).
    8. Gu, Rongbao & Xiong, Wei & Li, Xinjie, 2015. "Does the singular value decomposition entropy have predictive power for stock market? — Evidence from the Shenzhen stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 103-113.
    9. Xavier Brouty & Matthieu Garcin, 2023. "Fractal properties, information theory, and market efficiency," Papers 2306.13371, arXiv.org.
    10. Li, Yiying & Ren, Xiaohang & Taghizadeh-Hesary, Farhad, 2023. "Vulnerability of sustainable markets to fossil energy shocks," Resources Policy, Elsevier, vol. 85(PB).
    11. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    12. Busu, Cristian & Busu, Mihail, 2019. "Modeling the predictive power of the singular value decomposition-based entropy. Empirical evidence from the Dow Jones Global Titans 50 Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    13. Albarracín E., Eva Susana & Gamboa, Juan C. Rodríguez & Marques, Elaine C.M. & Stosic, Tatijana, 2019. "Complexity analysis of Brazilian agriculture and energy market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 933-941.
    14. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & de Oliveira, Wilson & Stosic, Tatijana, 2016. "Foreign exchange rate entropy evolution during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 233-239.
    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. Kunal Saha & Vinodh Madhavan & G. R. Chandrashekhar, 2022. "Effect of COVID-19 on ETF and index efficiency: evidence from an entropy-based analysis," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(2), pages 347-359, April.
    17. Syed Jawad Hussain Shahzad & Jose Arreola‐Hernandez & Md Lutfur Rahman & Gazi Salah Uddin & Muhammad Yahya, 2021. "Asymmetric interdependence between currency markets' volatilities across frequencies and time scales," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2436-2457, April.
    18. Ibarra-Valdez, C. & Alvarez, J. & Alvarez-Ramirez, J., 2016. "Randomness confidence bands of fractal scaling exponents for financial price returns," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 119-124.
    19. Hazem Krichene & Mhamed-Ali El-Aroui, 2018. "Artificial stock markets with different maturity levels: simulation of information asymmetry and herd behavior using agent-based and network models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 511-535, October.
    20. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & Stosic, Tatijana, 2016. "Correlations of multiscale entropy in the FX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 52-61.
    21. Subhamitra Patra & Gourishankar S. Hiremath, 2022. "An Entropy Approach to Measure the Dynamic Stock Market Efficiency," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(2), pages 337-377, June.

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    More about this item

    Keywords

    Market efficiency; Entropy; Dow Jones Index; Cycle;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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