IDEAS home Printed from https://ideas.repec.org/a/eee/revfin/v35y2017icp1-10.html
   My bibliography  Save this article

Volatility measures as predictors of extreme returns

Author

Listed:
  • Switzer, Lorne N.
  • Tahaoglu, Cagdas
  • Zhao, Yun

Abstract

This paper examines the relationship between volatility and the probability of occurrence of expected extreme returns in the Canadian market. Four measures of volatility are examined: implied volatility from firm option prices, conditional volatility calculated using an EGARCH model, idiosyncratic volatility, and expected shortfall. A significantly positive relationship is observed between a firm's idiosyncratic volatility and the probability of occurrence of an extreme return in the subsequent month for firms. A 10% increase in idiosyncratic volatility in a given month is associated with the probability of an extreme shock in the subsequent month (top or bottom 1.5% of the returns distribution) of 26.4%. Other firm characteristics, including firm age, price, volume and book-to-market ratio, are also shown to be significantly related to subsequent firm extreme returns. The effects of conditional and implied volatility are mixed. The E-GARCH and expected shortfall measures of conditional volatility are consistent with mean reversion: high short term realizations of conditional volatility foreshadow a lower probability of extreme returns.

Suggested Citation

  • Switzer, Lorne N. & Tahaoglu, Cagdas & Zhao, Yun, 2017. "Volatility measures as predictors of extreme returns," Review of Financial Economics, Elsevier, vol. 35(C), pages 1-10.
    • Handle: RePEc:eee:revfin:v:35:y:2017:i:c:p:1-10
    DOI: 10.1016/j.rfe.2017.04.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1058330016301434
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rfe.2017.04.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    2. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    3. Turan G. Bali & Panayiotis Theodossiou, 2008. "Risk Measurement Performance of Alternative Distribution Functions," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(2), pages 411-437, June.
    4. Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
    5. Ang, Andrew & Hodrick, Robert J. & Xing, Yuhang & Zhang, Xiaoyan, 2009. "High idiosyncratic volatility and low returns: International and further U.S. evidence," Journal of Financial Economics, Elsevier, vol. 91(1), pages 1-23, January.
    6. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
    7. Bali, Turan G. & Cakici, Nusret, 2008. "Idiosyncratic Volatility and the Cross Section of Expected Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(1), pages 29-58, March.
    8. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    9. Frazzini, Andrea & Pedersen, Lasse Heje, 2014. "Betting against beta," Journal of Financial Economics, Elsevier, vol. 111(1), pages 1-25.
    10. Bali, Turan G. & Demirtas, K. Ozgur & Levy, Haim, 2009. "Is There an Intertemporal Relation between Downside Risk and Expected Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 883-909, August.
    11. Turan G. Bali, 2007. "An Extreme Value Approach to Estimating Interest-Rate Volatility: Pricing Implications for Interest-Rate Options," Management Science, INFORMS, vol. 53(2), pages 323-339, February.
    12. Barsky, Robert B, 1989. "Why Don't the Prices of Stocks and Bonds Move Together?," American Economic Review, American Economic Association, vol. 79(5), pages 1132-1145, December.
    13. Andy Fodor & Kevin Krieger & Nathan Mauck & Greg Stevenson, 2013. "Predicting Extreme Returns And Portfolio Management Implications," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 36(4), pages 471-492, December.
    14. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    15. Hsu, Stephen D.H. & Murray, Brian M., 2007. "On the volatility of volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 366-376.
    16. Longin, Francois M., 2000. "From value at risk to stress testing: The extreme value approach," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1097-1130, July.
    17. Lorne Switzer & Alan Picard, 2015. "Idiosyncratic Volatility, Momentum, Liquidity, and Expected Stock Returns in Developed and Emerging Markets," Multinational Finance Journal, Multinational Finance Journal, vol. 19(3), pages 169-221, September.
    18. Conrad, Jennifer & Kapadia, Nishad & Xing, Yuhang, 2014. "Death and jackpot: Why do individual investors hold overpriced stocks?," Journal of Financial Economics, Elsevier, vol. 113(3), pages 455-475.
    19. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    20. Wei Huang & Qianqiu Liu & S. Ghon Rhee & Liang Zhang, 2010. "Return Reversals, Idiosyncratic Risk, and Expected Returns," Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 147-168, January.
    21. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    22. Turan G. Bali, 2003. "An Extreme Value Approach to Estimating Volatility and Value at Risk," The Journal of Business, University of Chicago Press, vol. 76(1), pages 83-108, January.
    23. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    24. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    25. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    26. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    27. Li An, 2016. "Asset Pricing When Traders Sell Extreme Winners and Losers," Review of Financial Studies, Society for Financial Studies, vol. 29(3), pages 823-861.
    28. Lorne N. Switzer & Jun Wang & Seungho Lee, 2017. "Extreme risk and small investor behavior in developed markets," Journal of Asset Management, Palgrave Macmillan, vol. 18(6), pages 457-475, October.
    29. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    30. Turan Bali & Panayiotis Theodossiou, 2007. "A conditional-SGT-VaR approach with alternative GARCH models," Annals of Operations Research, Springer, vol. 151(1), pages 241-267, April.
    31. Fu, Fangjian, 2009. "Idiosyncratic risk and the cross-section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 91(1), pages 24-37, January.
    32. Duffee, Gregory R., 1995. "Stock returns and volatility A firm-level analysis," Journal of Financial Economics, Elsevier, vol. 37(3), pages 399-420, March.
    33. Yufeng Han & David Lesmond, 2011. "Liquidity Biases and the Pricing of Cross-sectional Idiosyncratic Volatility," Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1590-1629.
    34. Levy, Haim, 1978. "Equilibrium in an Imperfect Market: A Constraint on the Number of Securities in the Portfolio," American Economic Review, American Economic Association, vol. 68(4), pages 643-658, September.
    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. Masahiro Inoguchi, 2021. "The impact of foreign capital flows on long‐term interest rates in emerging and advanced economies," Review of International Economics, Wiley Blackwell, vol. 29(2), pages 268-295, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bai, Jennie & Bali, Turan G. & Wen, Quan, 2021. "Is there a risk-return tradeoff in the corporate bond market? Time-series and cross-sectional evidence," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1017-1037.
    2. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, June.
    3. Aboulamer, Anas & Kryzanowski, Lawrence, 2016. "Are idiosyncratic volatility and MAX priced in the Canadian market?," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 20-36.
    4. Zhong, Angel, 2018. "Idiosyncratic volatility in the Australian equity market," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 105-125.
    5. Guo, Hui & Qiu, Buhui, 2014. "Options-implied variance and future stock returns," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 93-113.
    6. Yunting Liu, 2022. "The Short-Run and Long-Run Components of Idiosyncratic Volatility and Stock Returns," Management Science, INFORMS, vol. 68(2), pages 1573-1589, February.
    7. Jennie Bai & Turan G. Bali & Quan Wen, 2019. "Is There a Risk-Return Tradeoff in the Corporate Bond Market? Time-Series and Cross-Sectional Evidence," NBER Working Papers 25995, National Bureau of Economic Research, Inc.
    8. Tariq Aziz & Valeed Ahmad Ansari, 2017. "Idiosyncratic volatility and stock returns: Indian evidence," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1420998-142, January.
    9. Zhaobo Zhu & Wenjie Ding & Yi Jin & Dehua Shen, 2023. "Dissecting the Idiosyncratic Volatility Puzzle: A Fundamental Analysis Approach," Post-Print hal-04194180, HAL.
    10. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    11. Miffre, Joëlle & Brooks, Chris & Li, Xiafei, 2013. "Idiosyncratic volatility and the pricing of poorly-diversified portfolios," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 78-85.
    12. Su, Zhi & Shu, Tengjia & Yin, Libo, 2018. "The pricing effect of the common pattern in firm-level idiosyncratic volatility: Evidence from A-Share stocks of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 218-235.
    13. Ayadi, Mohamed A. & Cao, Xu & Lazrak, Skander & Wang, Yan, 2019. "Do idiosyncratic skewness and kurtosis really matter?," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    14. Son, Nguyen Truong & Nguyen, Nhat Minh, 2019. "Prospect theory value and idiosyncratic volatility: Evidence from the Korean stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 21(C), pages 113-122.
    15. Ali, Syed Riaz Mahmood & Hasan, Mohammad Nurul & Östermark, Ralf, 2020. "Are idiosyncratic risk and extreme positive return priced in the Indian equity market?," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 530-545.
    16. Atilgan, Yigit & Bali, Turan G. & Demirtas, K. Ozgur & Gunaydin, A. Doruk, 2020. "Left-tail momentum: Underreaction to bad news, costly arbitrage and equity returns," Journal of Financial Economics, Elsevier, vol. 135(3), pages 725-753.
    17. Bali, Turan G. & Gunaydin, A. Doruk & Jansson, Thomas & Karabulut, Yigitcan, 2023. "Do the rich gamble in the stock market? Low risk anomalies and wealthy households," Journal of Financial Economics, Elsevier, vol. 150(2).
    18. Ji Cao & Marc Oliver Rieger & Lei Zhao, 2019. "Safety First, Loss Probability, and the Cross Section of Expected Stock Returns," Working Paper Series 2019-02, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    19. Wang, Jianqiu & Wu, Ke & Pan, Jiening & Jiang, Ying, 2023. "Disagreement, speculation, and the idiosyncratic volatility," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 232-250.
    20. Ciciretti, Rocco & Dalò, Ambrogio & Dam, Lammertjan, 2023. "The contributions of betas versus characteristics to the ESG premium," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 104-124.

    More about this item

    Keywords

    Extreme returns; Implied volatility; Conditional volatility; Idiosyncratic volatility; Expected shortfall;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    Statistics

    Access and download statistics

    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:revfin:v:35:y:2017:i:c:p:1-10. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620170 .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.