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Tests and Properties of Variance Ratios in Microstructure Studies

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  • Ronen, Tavy

Abstract

The properties of variance ratio tests across trading and non-trading periods are examined using the generalized method of moments. For the case of opening and closing return variances, the joint tests indicate that the null hypothesis that the variance of opening returns equals the variance of closing returns cannot be rejected for a sample of New York Stock Exchange stocks. This example demonstrates the importance of accounting for overlapping observations and cross correlation in such frameworks. The conventional average (across assets) variance ratio test is shown to be biased against the null in small samples. Specifically, when non-zero correlations are ignored, previous tests have the wrong asymptotic size. This bias persists in other frameworks as well: although this study confirms earlier findings that the return variance during non-trading periods is significantly lower than during trading periods, test statistics that ignore correlations are shown to be inflated.

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  • Ronen, Tavy, 1997. "Tests and Properties of Variance Ratios in Microstructure Studies," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(2), pages 183-204, June.
    • Handle: RePEc:cup:jfinqa:v:32:y:1997:i:02:p:183-204_00
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    Cited by:

    1. Harvey, Campbell R. & Huang, Roger D., 2002. "The impact of the Federal Reserve Bank's open market operations," Journal of Financial Markets, Elsevier, vol. 5(2), pages 223-257, April.
    2. Yamori, Nobuyoshi, 1998. "Does international trading of stocks decrease pricing errors? Evidence from Japan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 8(3-4), pages 413-432, December.
    3. Albuquerque, Rui & H. Bauer, Gregory & Schneider, Martin, 2009. "Global private information in international equity markets," Journal of Financial Economics, Elsevier, vol. 94(1), pages 18-46, October.
    4. Ronen, Tavy & Weaver, Daniel G., 2001. "'Teenies' anyone?," Journal of Financial Markets, Elsevier, vol. 4(3), pages 231-260, June.
    5. Semenov, Andrei, 2015. "The small-cap effect in the predictability of individual stock returns," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 178-197.
    6. Madhavan, Ananth & Panchapagesan, Venkatesh, 2000. "Price Discovery in Auction Markets: A Look Inside the Black Box," The Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 627-658.
    7. Biais, Bruno & Glosten, Larry & Spatt, Chester, 2005. "Market microstructure: A survey of microfoundations, empirical results, and policy implications," Journal of Financial Markets, Elsevier, vol. 8(2), pages 217-264, May.
    8. Piccotti, Louis R., 2016. "Pricing errors and the geography of trade in the foreign exchange market," Journal of Financial Markets, Elsevier, vol. 28(C), pages 46-69.
    9. Charles Cao & Bing Liang & Andrew W Lo & Lubomir Petrasek, 2018. "Hedge Fund Holdings and Stock Market Efficiency," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 8(1), pages 77-116.
    10. George, Thomas J & Hwang, Chuan-Yang, 2001. "Information Flow and Pricing Errors: A Unified Approach to Estimation and Testing," The Review of Financial Studies, Society for Financial Studies, vol. 14(4), pages 979-1020.
    11. Ronen, Tavy, 1998. "Trading structure and overnight information: A natural experiment from the Tel-Aviv Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 22(5), pages 489-512, May.
    12. Chang, Rosita P. & Rhee, S. Ghon & Stone, Gregory R. & Tang, Ning, 2008. "How does the call market method affect price efficiency? Evidence from the Singapore Stock Market," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2205-2219, October.
    13. Syed Mujahid Hussain & Sergey Osmekhin & Frédéric Délèze, 2021. "Short-term market efficiency indicator based on the waiting-time distribution," Review of Managerial Science, Springer, vol. 15(6), pages 1561-1572, August.

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