IDEAS home Printed from https://ideas.repec.org/a/bis/bisqtr/0306g.html
   My bibliography  Save this article

What drives investor risk aversion? Daily evidence from the German equity market

Author

Listed:
  • Martin Scheicher

Abstract

Stock prices move as corporate earnings prospects change but they also move as investors change their aversion to risk. Aversion to risk gives rise to a risk premium, which consists of an expected extra return that investors require to be compensated for the risk of holding stocks. Option prices are a unique source of information for the estimation of risk premia. The way strike prices in option contracts distinguish between outcomes that are relatively favourable to investors and those that are relatively unfavourable allows an estimate of risk aversion to be extracted from observed option prices. This is done by comparing what is implied in option prices with the probabilities of various outcomes from a purely statistical point of view. The purpose of this special feature is to explain daily movements in the risk aversion of investors in the German stock market as reflected in option prices.2 We focus on the main German index, the Dax, which summarises the stock prices of 30 major German companies. Our data on Dax option prices consist of daily observations from December 1995 to May 2002. To explain movements in our measure of risk aversion, we examine indicators of expectations about economic growth, market volatility, credit risk premia and negative news events. We find that investors in the German equity market seem to have become increasingly risk-averse since 1998. In addition, we note that movements in US stock prices have a strong impact on this risk aversion. We complement the study of Tarashev et al (also in this Quarterly Review) in three respects. First, we analyse risk aversion at a higher frequency: we examine daily movements, while they examine monthly movements. Second, we measure risk aversion in a slightly different way – particularly in estimating statistical probabilities – thus allowing a comparison of two measures and potentially providing a sense of the robustness of option-based measures. Finally, we go a step further by attempting to identify factors that would explain the changes in risk aversion from one day to the next.

Suggested Citation

  • Martin Scheicher, 2003. "What drives investor risk aversion? Daily evidence from the German equity market," BIS Quarterly Review, Bank for International Settlements, June.
  • Handle: RePEc:bis:bisqtr:0306g
    as

    Download full text from publisher

    File URL: https://www.bis.org/publ/qtrpdf/r_qt0306g.pdf
    Download Restriction: no

    File URL: https://www.bis.org/publ/qtrpdf/r_qt0306g.htm
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. De Santis, Giorgio & Gerard, Bruno, 1997. "International Asset Pricing and Portfolio Diversification with Time-Varying Risk," Journal of Finance, American Finance Association, vol. 52(5), pages 1881-1912, December.
    2. Beber, Alessandro & Brandt, Michael W., 2006. "The effect of macroeconomic news on beliefs and preferences: Evidence from the options market," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1997-2039, November.
    3. Jackwerth, Jens Carsten, 1999. "Option Implied Risk-Neutral Distributions and Implied Binomial Trees: A Literature Review," MPRA Paper 11634, University Library of Munich, Germany.
    4. Glatzer, Ernst & Scheicher, Martin, 2003. "Modelling the implied probability of stock market movements," Working Paper Series 212, European Central Bank.
    5. Ait-Sahalia, Yacine & Wang, Yubo & Yared, Francis, 2001. "Do option markets correctly price the probabilities of movement of the underlying asset?," Journal of Econometrics, Elsevier, vol. 102(1), pages 67-110, May.
    6. Melick, William R. & Thomas, Charles P., 1997. "Recovering an Asset's Implied PDF from Option Prices: An Application to Crude Oil during the Gulf Crisis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(1), pages 91-115, March.
    7. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
    8. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June.
    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. Paun, Cristian & Brasoveanu, Iulian & Musetescu, Radu, 2007. "Absolute Risk Aversion on the Romanian Capital Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 4(4), pages 77-87, December.
    2. Yasuo Nishiyama, 2006. "The Asian Financial Crisis and Investors’ Risk Aversion," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 13(3), pages 181-205, September.
    3. Bekaert, Geert & Hoerova, Marie, 2016. "What do asset prices have to say about risk appetite and uncertainty?," Journal of Banking & Finance, Elsevier, vol. 67(C), pages 103-118.
    4. Jose Fique & Frank Page, 2013. "Rollover risk and endogenous network dynamics," Computational Management Science, Springer, vol. 10(2), pages 213-230, June.
    5. Prasanna Gai & Nicholas Vause, 2006. "Measuring Investors' Risk Appetite," International Journal of Central Banking, International Journal of Central Banking, vol. 2(1), March.
    6. Cristian PAUN & Radu MUSETESCU & Iulian BRASOVEANU & Alina DRAGHICI, 2008. "Empirical evidence on risk aversion for individual romanian capital market investors," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 1, pages 91-101, December.
    7. Marini, François, 2011. "Financial intermediation in the theory of the risk-free rate," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1663-1668, July.
    8. Coudert, Virginie & Gex, Mathieu, 2008. "Does risk aversion drive financial crises? Testing the predictive power of empirical indicators," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 167-184, March.
    9. Bian, Timothy Yang & Wang, Tianyi & Zhou, Zipeng, 2021. "Measuring investors’ risk aversion in China’s stock market," Finance Research Letters, Elsevier, vol. 42(C).
    10. Coudert, V. & Gex, M., 2006. "Can risk aversion indicators anticipate financial crises?," Financial Stability Review, Banque de France, issue 9, pages 67-87, December.

    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. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    2. Vahamaa, Sami, 2005. "Option-implied asymmetries in bond market expectations around monetary policy actions of the ECB," Journal of Economics and Business, Elsevier, vol. 57(1), pages 23-38.
    3. Jukka Sihvonen & Sami Vähämaa, 2014. "Forward‐Looking Monetary Policy Rules and Option‐Implied Interest Rate Expectations," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(4), pages 346-373, April.
    4. Christoffersen, Peter & Jacobs, Kris & Chang, Bo Young, 2013. "Forecasting with Option-Implied Information," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 581-656, Elsevier.
    5. G. C. Lim & G. M. Martin & V. L. Martin, 2005. "Parametric pricing of higher order moments in S&P500 options," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(3), pages 377-404, March.
    6. Ben R. Craig & Ernst Glatzer & Joachim G. Keller & Martin Scheicher, 2003. "The forecasting performance of German stock option densities," Working Papers (Old Series) 0312, Federal Reserve Bank of Cleveland.
    7. Daniel Giamouridis, 2005. "Inferring option-implied investors' risk preferences," Applied Financial Economics, Taylor & Francis Journals, vol. 15(7), pages 479-488.
    8. Luiz Vitiello & Ser-Huang Poon, 2014. "Non-monotonic pricing kernel and an extended class of mixture of distributions for option pricing," Review of Derivatives Research, Springer, vol. 17(2), pages 241-259, July.
    9. Francisco Alonso & Roberto Blanco & Gonzalo Rubio, 2009. "Option-implied preferences adjustments, density forecasts, and the equity risk premium," Spanish Economic Review, Springer;Spanish Economic Association, vol. 11(2), pages 141-164, June.
    10. Mo, Henry & Wu, Liuren, 2007. "International capital asset pricing: Evidence from options," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 465-498, September.
    11. Bondarenko, Oleg, 2003. "Estimation of risk-neutral densities using positive convolution approximation," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 85-112.
    12. Glatzer, Ernst & Scheicher, Martin, 2003. "Modelling the implied probability of stock market movements," Working Paper Series 212, European Central Bank.
    13. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    14. Barone-Adesi, Giovanni & Fusari, Nicola & Mira, Antonietta & Sala, Carlo, 2020. "Option market trading activity and the estimation of the pricing kernel: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 216(2), pages 430-449.
    15. Carvalho, Augusto & Guimaraes, Bernardo, 2018. "State-controlled companies and political risk: Evidence from the 2014 Brazilian election," Journal of Public Economics, Elsevier, vol. 159(C), pages 66-78.
    16. Bollerslev, Tim & Gibson, Michael & Zhou, Hao, 2011. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Journal of Econometrics, Elsevier, vol. 160(1), pages 235-245, January.
    17. Kitsul, Yuriy & Wright, Jonathan H., 2013. "The economics of options-implied inflation probability density functions," Journal of Financial Economics, Elsevier, vol. 110(3), pages 696-711.
    18. David Backus & Mikhail Chernov & Ian Martin, 2011. "Disasters Implied by Equity Index Options," Journal of Finance, American Finance Association, vol. 66(6), pages 1969-2012, December.
    19. Chen, Ren-Raw & Hsieh, Pei-lin & Huang, Jeffrey, 2018. "Crash risk and risk neutral densities," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 162-189.
    20. Algieri, Bernardina & Leccadito, Arturo & Tunaru, Diana, 2021. "Risk premia in electricity derivatives markets," Energy Economics, Elsevier, vol. 100(C).

    More about this item

    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:bis:bisqtr:0306g. 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: Christian Beslmeisl (email available below). General contact details of provider: https://edirc.repec.org/data/bisssch.html .

    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.