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A test of efficiency for the S&P 500 index option market using the generalized spectrum method

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  • Huang, Henry H.
  • Wang, Kent
  • Wang, Zhanglong

Abstract

This paper examines the efficiency of the S&P 500 options market by testing the martingale properties of the Model-Free Forward Variance (MFFV) time series using the Generalized Spectral Test (GST). Based on a sample from January 1, 1996 to May 31, 2010, our tests show robust evidence that the S&P 500 options market is not efficient. By examining the subsamples before and after the 2008 financial crisis, we find this options market inefficiency is mainly driven by the outbreak of the subprime crisis. Our diagnostic tests further indicate that this inefficiency is due to the skewness-in-mean effect of forward variance. Specifically, the skewness-in-mean effect is weakened once we account for the S&P 500 index jump effects. Hence, we can establish a link between jumps and options market inefficiency. Finally, we find that the lagged skewness of the forward variance can help forecasting the forward variance both in-sample and out-of-sample. The economic significance of this forecasting ability is further highlighted by the performance of a trading strategy based on forward variance. In sum, out study provides robust evidence and a trading implication on testing the S&P 500 options market efficiency.

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  • Huang, Henry H. & Wang, Kent & Wang, Zhanglong, 2016. "A test of efficiency for the S&P 500 index option market using the generalized spectrum method," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 52-70.
    • Handle: RePEc:eee:jbfina:v:64:y:2016:i:c:p:52-70
    DOI: 10.1016/j.jbankfin.2015.11.007
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    as
    1. Ole E. Barndorff-Nielsen & Neil Shephard, 2006. "Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation," Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 1-30.
    2. Sekkel, Rodrigo, 2011. "International evidence on bond risk premia," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 174-181, January.
    3. Bryan Kelly & Hao Jiang, 2014. "Editor's Choice Tail Risk and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 27(10), pages 2841-2871.
    4. Tim Bollerslev & Viktor Todorov, 2011. "Tails, Fears, and Risk Premia," Journal of Finance, American Finance Association, vol. 66(6), pages 2165-2211, December.
    5. Ait-Sahalia, Yacine & Duarte, Jefferson, 2003. "Nonparametric option pricing under shape restrictions," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 9-47.
    6. Longstaff, Francis A., 2000. "The term structure of very short-term rates: New evidence for the expectations hypothesis," Journal of Financial Economics, Elsevier, vol. 58(3), pages 397-415, December.
    7. Durlauf, Steven N., 1991. "Spectral based testing of the martingale hypothesis," Journal of Econometrics, Elsevier, vol. 50(3), pages 355-376, December.
    8. Deo, Rohit S., 2000. "Spectral tests of the martingale hypothesis under conditional heteroscedasticity," Journal of Econometrics, Elsevier, vol. 99(2), pages 291-315, December.
    9. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
    10. Benjamin Yibin Zhang & Hao Zhou & Haibin Zhu, 2009. "Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5099-5131, December.
    11. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    12. Yongmiao Hong & Haitao Li & Feng Zhao, 2004. "Out-of-Sample Performance of Discrete-Time Spot Interest Rate Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 457-473, October.
    13. Gurdip Bakshi & Nikunj Kapadia & Dilip Madan, 2003. "Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options," The Review of Financial Studies, Society for Financial Studies, vol. 16(1), pages 101-143.
    14. Andrew Ang & Geert Bekaert, 2007. "Stock Return Predictability: Is it There?," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 651-707.
    15. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    16. Kraus, Alan & Litzenberger, Robert H, 1976. "Skewness Preference and the Valuation of Risk Assets," Journal of Finance, American Finance Association, vol. 31(4), pages 1085-1100, September.
    17. 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.
    18. Wright, Jonathan H. & Zhou, Hao, 2009. "Bond risk premia and realized jump risk," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2333-2345, December.
    19. Escanciano, Juan Carlos & Mayoral, Silvia, 2010. "Data-driven smooth tests for the martingale difference hypothesis," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 1983-1998, August.
    20. Cremers, Martijn & Weinbaum, David, 2010. "Deviations from Put-Call Parity and Stock Return Predictability," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 335-367, April.
    21. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    22. Hong, Yongmiao & Lin, Hai & Wu, Chunchi, 2012. "Are corporate bond market returns predictable?," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2216-2232.
    23. George J. Jiang & Yisong S. Tian, 2005. "The Model-Free Implied Volatility and Its Information Content," The Review of Financial Studies, Society for Financial Studies, vol. 18(4), pages 1305-1342.
    24. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    25. Paolo Angelini & Andrea Nobili & Cristina Picillo, 2011. "The Interbank Market after August 2007: What Has Changed, and Why?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 923-958, August.
    26. Peter Carr & Liuren Wu, 2009. "Variance Risk Premiums," The Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1311-1341, March.
    27. Sanjiv Ranjan Das & Rangarajan K. Sundaram, 1997. "Taming the Skew: Higher-Order Moments in Modeling Asset Price Processes in Finance," NBER Working Papers 5976, National Bureau of Economic Research, Inc.
    28. Longstaff, Francis A, 1995. "Option Pricing and the Martingale Restriction," The Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 1091-1124.
    29. Xin Huang & George Tauchen, 2005. "The Relative Contribution of Jumps to Total Price Variance," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 456-499.
    30. Jian Yang & Yinggang Zhou & Zijun Wang, 2010. "Conditional Coskewness in Stock and Bond Markets: Time-Series Evidence," Management Science, INFORMS, vol. 56(11), pages 2031-2049, November.
    31. Manuel Dominguez & Ignacio Lobato, 2003. "Testing the Martingale Difference Hypothesis," Econometric Reviews, Taylor & Francis Journals, vol. 22(4), pages 351-377.
    32. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    33. Yongmiao Hong & Tae-Hwy Lee, 2003. "Inference on Predictability of Foreign Exchange Rates via Generalized Spectrum and Nonlinear Time Series Models," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1048-1062, November.
    34. Suzanne S. Lee & Per A. Mykland, 2008. "Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics," The Review of Financial Studies, Society for Financial Studies, vol. 21(6), pages 2535-2563, November.
    35. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    36. Kraus, Alan & Litzenberger, Robert, 1983. "On the Distributional Conditions for a Consumption-Oriented Three Moment CAPM," Journal of Finance, American Finance Association, vol. 38(5), pages 1381-1391, December.
    37. George J. Jiang & Yisong S. Tian, 2012. "A random walk down the options market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(6), pages 505-535, June.
    38. Carr, Peter & Madan, Dilip B., 2005. "A note on sufficient conditions for no arbitrage," Finance Research Letters, Elsevier, vol. 2(3), pages 125-130, September.
    39. Xing, Yuhang & Zhang, Xiaoyan & Zhao, Rui, 2010. "What Does the Individual Option Volatility Smirk Tell Us About Future Equity Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(3), pages 641-662, June.
    40. McPherson, Matthew Q. & Palardy, Joseph, 2007. "Are international stock returns predictable?: An examination of linear and non-linear predictability using generalized spectral tests," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(5), pages 452-464, December.
    41. Rubinstein, Mark E., 1973. "The Fundamental Theorem of Parameter-Preference Security Valuation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 8(1), pages 61-69, January.
    42. Yang, Jian & Su, Xiaojing & Kolari, James W., 2008. "Do Euro exchange rates follow a martingale? Some out-of-sample evidence," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 729-740, May.
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    1. Zhang, Huiming & Watada, Junzo, 2019. "An analysis of the arbitrage efficiency of the Chinese SSE 50ETF options market," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 474-489.

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    More about this item

    Keywords

    Model-Free Forward Variance; Spectral density test; Index jump; Market efficiency;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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