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The Evolution of Market Efficiency: 103 Years Daily Data of the Dow

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  • Gu, Anthony Yanxiang
  • Finnerty, Joseph

Abstract

Autocorrelation in daily returns of the Dow 30 Index fluctuates significantly over time and reveals a declining trend after World War II. The relation between autocorrelation and volatility is negative and nonlinear. The relation between autocorrelation and volume is also negative and nonlinear. Returns exhibit positive autocorrelation during years with higher autocorrelation, and negative autocorrelation during years with lower autocorrelation. Positive autocorrelation appears more frequently during periods of low volatility, while negative autocorrelation appears more frequently during periods of high volatility. Current period's autocorrelation is related to previous period's autocorrelation and to both the previous and the current period's volatility and rate of return, which implies that investors incorporate previous period's pattern of market behavior into their trading strategy. Copyright 2002 by Kluwer Academic Publishers

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  • Gu, Anthony Yanxiang & Finnerty, Joseph, 2002. "The Evolution of Market Efficiency: 103 Years Daily Data of the Dow," Review of Quantitative Finance and Accounting, Springer, vol. 18(3), pages 219-237, May.
    • Handle: RePEc:kap:rqfnac:v:18:y:2002:i:3:p:219-37
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    Cited by:

    1. Kwang-il Choe & Joshua Krausz & Kiseok Nam, 2011. "Technical trading rules for nonlinear dynamics of stock returns: evidence from the G-7 stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 36(3), pages 323-353, April.
    2. Kim, Jae & Doucouliagos, Hristos & Stanley, T. D., 2014. "Market efficiency in Asian and Australasian stock markets: a fresh look at the evidence," Working Papers eco_2014_9, Deakin University, Department of Economics.
    3. Fatima Syed & Naimat U. Khan, 2017. "Islamic Calendar Anomalies: Evidence from Pakistan," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 9(3), pages 104-122, September.
    4. Pawan Jain & Wen-Jun Xue, 2017. "Global Investigation of Return Autocorrelation and its Determinants," Working Papers 1704, Florida International University, Department of Economics.
    5. Xu Li, 2011. "Behavioral theories and the pricing of IPOs’ discretionary current accruals," Review of Quantitative Finance and Accounting, Springer, vol. 37(1), pages 87-104, July.
    6. Verheyden, Tim & De Moor, Lieven & Van den Bossche, Filip, 2015. "Towards a new framework on efficient markets," Research in International Business and Finance, Elsevier, vol. 34(C), pages 294-308.
    7. Gelman, Sergey & Burhop, Carsten, 2008. "Taxation, regulation and the information efficiency of the Berlin stock exchange, 1892–1913," European Review of Economic History, Cambridge University Press, vol. 12(1), pages 39-66, April.
    8. Gu, Anthony Yanxiang, 2003. "The declining January effect: evidences from the U.S. equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 43(2), pages 395-404.
    9. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    10. Lo, Melody & Lee, Cheng-Few, 2006. "A reexamination of the market efficiency hypothesis: Evidence from an electronic intra-day, inter-dealer FX market," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(4), pages 565-585, September.
    11. Jain, Pawan & Xue, Wenjun, 2017. "Global investigation of return autocorrelation and its determinants," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 200-217.
    12. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2015. "Will precious metals shine? A market efficiency perspective," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 284-291.
    13. Abul Shamsuddin & Jae H. Kim, 2010. "Short‐Horizon Return Predictability in International Equity Markets," The Financial Review, Eastern Finance Association, vol. 45(2), pages 469-484, May.
    14. Graham Smith & Aneta Dyakova, 2016. "The Relative Predictability of Stock Markets in the Americas," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 131-142, April.
    15. Lim, Kian-Ping & Brooks, Robert D. & Hinich, Melvin J., 2008. "Nonlinear serial dependence and the weak-form efficiency of Asian emerging stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 527-544, December.
    16. Zaremba, Adam & Umutlu, Mehmet & Maydybura, Alina, 2020. "Where have the profits gone? Market efficiency and the disappearing equity anomalies in country and industry returns," Journal of Banking & Finance, Elsevier, vol. 121(C).
    17. Gholipour, Hassan F. & Arjomandi, Amir & Andargoli, Amirhossein Eslami & Bennett, Rohan, 2023. "On real estate market transparency: The relationship with ICT trade and investment," Land Use Policy, Elsevier, vol. 133(C).
    18. Kim, Jae H. & Shamsuddin, Abul & Lim, Kian-Ping, 2011. "Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 868-879.
    19. Amélie Charles & Olivier Darné & Jae H. Kim, 2014. "Precious metals shine? A market efficiency perspective," Working Papers hal-01010516, HAL.
    20. Kian-Ping Lim & Weiwei Luo & Jae H. Kim, 2013. "Are US stock index returns predictable? Evidence from automatic autocorrelation-based tests," Applied Economics, Taylor & Francis Journals, vol. 45(8), pages 953-962, March.
    21. Anthony Gu, 2004. "The Reversing Weekend Effect: Evidence from the U.S. Equity Markets," Review of Quantitative Finance and Accounting, Springer, vol. 22(1), pages 5-14, January.
    22. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    23. Debarati Bhattacharya & Wei-Hsien Li & Gokhan Sonaer, 2017. "Has momentum lost its momentum?," Review of Quantitative Finance and Accounting, Springer, vol. 48(1), pages 191-218, January.
    24. Roy, Archi & Soni, Anchal & Deb, Soudeep, 2023. "A wavelet-based methodology to compare the impact of pandemic versus Russia–Ukraine conflict on crude oil sector and its interconnectedness with other energy and non-energy markets," Energy Economics, Elsevier, vol. 124(C).

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