IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v27yi2p543-560.html
   My bibliography  Save this article

Are VIX futures prices predictable? An empirical investigation

Author

Listed:
  • Konstantinidi, Eirini
  • Skiadopoulos, George

Abstract

This paper investigates whether volatility futures prices per se can be forecasted by studying the fast-growing VIX futures market. To this end, alternative model specifications are employed. Point and interval out-of-sample forecasts are constructed and evaluated under various statistical metrics. Next, the economic significance of the forecasts obtained is also assessed by performing trading strategies. Only weak evidence of statistically predictable patterns in the evolution of volatility futures prices is found. No trading strategy yields economically significant profits. Hence, the hypothesis that the VIX volatility futures market is informationally efficient cannot be rejected.

Suggested Citation

  • Konstantinidi, Eirini & Skiadopoulos, George, 2011. "Are VIX futures prices predictable? An empirical investigation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 543-560, April.
  • Handle: RePEc:eee:intfor:v:27:y::i:2:p:543-560
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169-2070(10)00008-7
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ser-Huang Poon & Peter, F. Pope, 2000. "Trading volatility spreads: a test of index option market efficiency," European Financial Management, European Financial Management Association, vol. 6(2), pages 235-260.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. Taylor, Stephen J, 1992. "Rewards Available to Currency Futures Speculators: Compensation for Risk or Evidence of Inefficient Pricing?," The Economic Record, The Economic Society of Australia, vol. 0(0), pages 105-116, Supplemen.
    4. Bessembinder, Hendrik & Chan, Kalok, 1992. "Time-varying risk premia and forecastable returns in futures markets," Journal of Financial Economics, Elsevier, vol. 32(2), pages 169-193, October.
    5. Bakshi, Gurdip & Cao, Charles & Chen, Zhiwu, 2000. "Do Call Prices and the Underlying Stock Always Move in the Same Direction?," Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 549-584.
    6. Andrea Coppola, 2008. "Forecasting oil price movements: Exploiting the information in the futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(1), pages 34-56, January.
    7. Pascual, Lorenzo & Romo, Juan & Ruiz, Esther, 2001. "Effects of parameter estimation on prediction densities: a bootstrap approach," International Journal of Forecasting, Elsevier, vol. 17(1), pages 83-103.
    8. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data-Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
    9. Jisoo Yoo & G. S. Maddala, 1991. "Risk premia and price volatility in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 11(2), pages 165-177, April.
    10. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    11. Jonathan Kearns & Phil Manners, 2004. "The Profitability of Speculators in Currency Futures Markets," RBA Research Discussion Papers rdp2004-07, Reserve Bank of Australia.
    12. Wang, Changyun, 2004. "Futures trading activity and predictable foreign exchange market movements," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1023-1041, May.
    13. Miffre, Joelle, 2001. "Economic activity and time variation in expected futures returns," Economics Letters, Elsevier, vol. 73(1), pages 73-79, October.
    14. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    15. Robert Jarrow & Haitao Li & Feng Zhao, 2007. "Interest Rate Caps "Smile" Too! But Can the LIBOR Market Models Capture the Smile?," Journal of Finance, American Finance Association, vol. 62(1), pages 345-382, February.
    16. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    17. Estrella, Arturo & Hardouvelis, Gikas A, 1991. " The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    18. Wayne E. Ferson & Sergei Sarkissian & Timothy T. Simin, 2003. "Spurious Regressions in Financial Economics?," Journal of Finance, American Finance Association, vol. 58(4), pages 1393-1414, August.
    19. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
    20. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-1153, December.
    21. Joëlle Miffre, 2001. "Efficiency in the Pricing of the FTSE 100 Futures Contract," European Financial Management, European Financial Management Association, vol. 7(1), pages 9-22.
    22. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    23. Konstantinidi, Eirini & Skiadopoulos, George & Tzagkaraki, Emilia, 2008. "Can the evolution of implied volatility be forecasted? Evidence from European and US implied volatility indices," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2401-2411, November.
    24. Dotsis, George & Psychoyios, Dimitris & Skiadopoulos, George, 2007. "An empirical comparison of continuous-time models of implied volatility indices," Journal of Banking & Finance, Elsevier, vol. 31(12), pages 3584-3603, December.
    25. Hartzmark, Michael L, 1987. "Returns to Individual Traders of Futures: Aggregate Results," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1292-1306, December.
    26. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    27. Yueh‐Neng Lin, 2007. "Pricing VIX futures: Evidence from integrated physical and risk‐neutral probability measures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(12), pages 1175-1217, December.
    28. Feng Zhao & Robert Jarrow & Haitao Li, 2004. "Interest Rate Caps Smile Too! But Can the LIBOR Market Models Capture It?," Econometric Society 2004 North American Winter Meetings 431, Econometric Society.
    29. Jin E. Zhang & Yingzi Zhu, 2006. "VIX futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(6), pages 521-531, June.
    30. Neil Kellard & Paul Newbold & Tony Rayner & Christine Ennew, 1999. "The relative efficiency of commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(4), pages 413-432, June.
    31. Bong-Chan, Kho, 1996. "Time-varying risk premia, volatility, and technical trading rule profits: Evidence from foreign currency futures markets," Journal of Financial Economics, Elsevier, vol. 41(2), pages 249-290, June.
    32. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    33. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    34. Hartzmark, Michael L, 1991. "Luck versus Forecast Ability: Determinants of Trader Performance in Futures Markets," The Journal of Business, University of Chicago Press, vol. 64(1), pages 49-74, January.
    35. Fama, Eugene F & French, Kenneth R, 1987. "Commodity Futures Prices: Some Evidence on Forecast Power, Premiums,and the Theory of Storage," The Journal of Business, University of Chicago Press, vol. 60(1), pages 55-73, January.
    36. Grunbichler, Andreas & Longstaff, Francis A., 1996. "Valuing futures and options on volatility," Journal of Banking & Finance, Elsevier, vol. 20(6), pages 985-1001, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dunis, Christian & Kellard, Neil M. & Snaith, Stuart, 2013. "Forecasting EUR–USD implied volatility: The case of intraday data," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4943-4957.
    2. Imlak Shaikh & Puja Padhi, 2014. "The forecasting performance of implied volatility index: evidence from India VIX," Economic Change and Restructuring, Springer, vol. 47(4), pages 251-274, November.
    3. Gloria Gonzalez-Rivera & Joao Henrique Mazzeu & Esther Ruiz & Helena Veiga, 2017. "A Bootstrap Approach for Generalized Autocontour Testing. Implications for VIX Forecast Densities," Working Papers 201709, University of California at Riverside, Department of Economics.
    4. Psaradellis, Ioannis & Sermpinis, Georgios, 2016. "Modelling and trading the U.S. implied volatility indices. Evidence from the VIX, VXN and VXD indices," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1268-1283.
    5. Juliusz Jablecki & Robert Slepaczuk & Ryszard Kokoszczynski & Pawel Sakowski & Piotr Wojcik, 2014. "Does historical VIX term structure contain valuable information for predicting VIX futures?," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 14, pages 5-28.
    6. Goulas, Lambros & Skiadopoulos, George, 2012. "Are freight futures markets efficient? Evidence from IMAREX," International Journal of Forecasting, Elsevier, vol. 28(3), pages 644-659.
    7. Cheng, Jun & Ibraimi, Meriton & Leippold, Markus & Zhang, Jin E., 2012. "A remark on Lin and Chang's paper ‘Consistent modeling of S&P 500 and VIX derivatives’," Journal of Economic Dynamics and Control, Elsevier, vol. 36(5), pages 708-715.
    8. Gonzalez-Perez, Maria T., 2015. "Model-free volatility indexes in the financial literature: A review," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 141-159.
    9. Cathy Chen & Shu-Yu Chen & Sangyeol Lee, 2013. "Bayesian Unit Root Test in Double Threshold Heteroskedastic Models," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 471-490, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:intfor:v:27:y::i:2:p:543-560. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.