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Exchange Traded Funds, Size-Based Portfolios, And Market Efficiency

Author

Listed:
  • Palani-Rajan Kadapakkam

    (UTSA)

  • Timothy Krause
  • Yiuman Tse

Abstract

We examine the informational efficiency of size-based U.S. Exchange Traded Funds (ETFs) and comparable CRSP portfolios using weekly and daily returns. Compared to the CRSP portfolios, ETFs are better suited for market efficiency tests. ETFs avoid the problems created by asynchronous pricing of underlying securities. Further, their negligible bid-ask spreads greatly diminish noise due to the bid-ask bounce. Variance ratio analysis demonstrates that return autocorrelations have diminished significantly over the past decade. Granger causality tests reject the presence of lead-lag effects among size-based ETFs. Volatility spills over from large firm ETFs to those of smaller firms, and correlations increase during periods of market volatility. We confirm these spillovers by examining implied volatilities derived from ETF option prices.

Suggested Citation

  • Palani-Rajan Kadapakkam & Timothy Krause & Yiuman Tse, 2013. "Exchange Traded Funds, Size-Based Portfolios, And Market Efficiency," Working Papers 0214fin, College of Business, University of Texas at San Antonio.
    • Handle: RePEc:tsa:wpaper:0214fin
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    References listed on IDEAS

    as
    1. Kewei Hou, 2007. "Industry Information Diffusion and the Lead-lag Effect in Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1113-1138.
    2. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    3. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2002. "Dynamic Volume-Return Relation of Individual Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1005-1047.
    4. Wright, Jonathan H, 2000. "Alternative Variance-Ratio Tests Using Ranks and Signs," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 1-9, January.
    5. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    6. Lo, Andrew W. & Craig MacKinlay, A., 1990. "An econometric analysis of nonsynchronous trading," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 181-211.
    7. Hibbert, Ann Marie & Daigler, Robert T. & Dupoyet, Brice, 2008. "A behavioral explanation for the negative asymmetric return-volatility relation," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2254-2266, October.
    8. Chung, Kee H. & Zhang, Hao, 2014. "A simple approximation of intraday spreads using daily data," Journal of Financial Markets, Elsevier, vol. 17(C), pages 94-120.
    9. Malinova, Katya & Park, Andreas, 2010. "Trading Volume in Dealer Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(6), pages 1447-1484, December.
    10. Mech, Timothy S., 1993. "Portfolio return autocorrelation," Journal of Financial Economics, Elsevier, vol. 34(3), pages 307-344, December.
    11. O'Hara, Maureen & Ye, Mao, 2011. "Is market fragmentation harming market quality?," Journal of Financial Economics, Elsevier, vol. 100(3), pages 459-474, June.
    12. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    13. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    14. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    15. Amit Goyal & Pedro Santa-Clara, 2003. "Idiosyncratic Risk Matters!," Journal of Finance, American Finance Association, vol. 58(3), pages 975-1008, June.
    16. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    17. Conrad, Christian & Karanasos, Menelaos, 2010. "Negative Volatility Spillovers In The Unrestricted Eccc-Garch Model," Econometric Theory, Cambridge University Press, vol. 26(3), pages 838-862, June.
    18. Ólan T. Henry & John Sharma, 1999. "Asymmetric Conditional Volatility and Firm Size: Evidence from Australian Equity Portfolios," Australian Economic Papers, Wiley Blackwell, vol. 38(4), pages 393-406, December.
    19. Amélie Charles & Olivier Darné, 2009. "Variance‐Ratio Tests Of Random Walk: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 503-527, July.
    20. Neil L. Fargher & Robert A. Weigand, 1998. "Changes In The Stock Price Reaction Of Small Firms To Common Information," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 21(1), pages 105-121, March.
    21. Doron Avramov & Tarun Chordia & Amit Goyal, 2006. "The Impact of Trades on Daily Volatility," Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1241-1277.
    22. Conrad, Jennifer & Kaul, Gautam, 1988. "Time-Variation in Expected Returns," The Journal of Business, University of Chicago Press, vol. 61(4), pages 409-425, October.
    23. Boudoukh, Jacob & Richardson, Matthew P & Whitelaw, Robert F, 1994. "A Tale of Three Schools: Insights on Autocorrelations of Short-Horizon Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 7(3), pages 539-573.
    24. Jegadeesh N. & Titman S., 1995. "Short-Horizon Return Reversals and the Bid-Ask Spread," Journal of Financial Intermediation, Elsevier, vol. 4(2), pages 116-132, April.
    25. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    26. Fargher, Neil L & Weigand, Robert A, 1998. "Changes in the Stock Price Reaction of Small Firms to Common Information," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 21(1), pages 105-121, Spring.
    27. Badrinath, S G & Kale, Jayant R & Noe, Thomas H, 1995. "Of Shepherds, Sheep, and the Cross-autocorrelations in Equity Returns," Review of Financial Studies, Society for Financial Studies, vol. 8(2), pages 401-430.
    28. Pedro A. C. Saffi & Kari Sigurdsson, 2011. "Price Efficiency and Short Selling," Review of Financial Studies, Society for Financial Studies, vol. 24(3), pages 821-852.
    29. John M. Griffin & Patrick J. Kelly & Federico Nardari, 2010. "Do Market Efficiency Measures Yield Correct Inferences? A Comparison of Developed and Emerging Markets," Review of Financial Studies, Society for Financial Studies, vol. 23(8), pages 3225-3277, August.
    30. Hoque, Hafiz A.A.B. & Kim, Jae H. & Pyun, Chong Soo, 2007. "A comparison of variance ratio tests of random walk: A case of Asian emerging stock markets," International Review of Economics & Finance, Elsevier, vol. 16(4), pages 488-502.
    31. 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.
    32. Conrad, Jennifer & Gultekin, Mustafa N & Kaul, Gautam, 1991. "Asymmetric Predictability of Conditional Variances," Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 597-622.
    33. Chordia, Tarun & Sarkar, Asani & Subrahmanyam, Avanidhar, 2011. "Liquidity Dynamics and Cross-Autocorrelations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 46(3), pages 709-736, June.
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