IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/3105.html

Measuring and Modelling Variation in the Risk-Return Trade-off

Author

Listed:
  • Lettau, Martin
  • Ludvigson, Sydney

Abstract

Are excess stock market returns predictable over time and, if so, at what horizons and with which economic indicators? Can stock return predictability be explained by changes in stock market volatility? How does the mean return per unit risk change over time? This chapter reviews what is known about the time-series evolution of the risk-return tradeoff for stock market investment, and presents some new empirical evidence using a proxy for the log consumption-aggregate wealth ratio as a predictor of both the mean and volatility of excess stock market returns. We characterize the risk-return tradeoff as the conditional expected excess return on a broad stock market index divided by its conditional standard deviation, a quantity commonly known as the Sharpe ratio. Our own investigation suggests that variation in the equity risk-premium is strongly negatively linked to variation in market volatility, at odds with leading asset pricing models. Since the conditional volatility and conditional mean move in opposite directions, the degree of countercyclicality in the Sharpe ratio that we document here is far more dramatic than that produced by existing equilibrium models of financial market behaviour, which completely miss the sheer magnitude of variation in the price of stock market risk.

Suggested Citation

  • Lettau, Martin & Ludvigson, Sydney, 2001. "Measuring and Modelling Variation in the Risk-Return Trade-off," CEPR Discussion Papers 3105, Centre for Economic Policy Research.
  • Handle: RePEc:cpr:ceprdp:3105
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP3105
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lettau, Martin & Ludvigson, Sydney, 2002. "Time-varying risk premia and the cost of capital: An alternative implication of the Q theory of investment," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 31-66, January.
    2. Cochrane, John H., 1991. "Volatility tests and efficient markets : A review essay," Journal of Monetary Economics, Elsevier, vol. 27(3), pages 463-485, 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. Brandt, Michael W. & Kang, Qiang, 2004. "On the relationship between the conditional mean and volatility of stock returns: A latent VAR approach," Journal of Financial Economics, Elsevier, vol. 72(2), pages 217-257, May.
    2. Rangvid, Jesper, 2002. "Output and Expected Returns - a multicountry study," Working Papers 2002-8, Copenhagen Business School, Department of Finance.
    3. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je & Gau, Yin-Feng, 2022. "Risk-return trade-off in the Australian Securities Exchange: Accounting for overnight effects, realized higher moments, long-run relations, and fractional cointegration," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 384-401.
    4. Tan, Zhengxun & Xiao, Binuo & Huang, Yilong & Zhou, Li, 2021. "Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

    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. Tuomo Vuolteenaho, 2002. "What Drives Firm‐Level Stock Returns?," Journal of Finance, American Finance Association, vol. 57(1), pages 233-264, February.
    2. Campbell, John Y., 2001. "Why long horizons? A study of power against persistent alternatives," Journal of Empirical Finance, Elsevier, vol. 8(5), pages 459-491, December.
    3. David Gruen, 1995. "Financial Market Volatility and the World-wide Fall in Inflation," RBA Research Discussion Papers rdp9513, Reserve Bank of Australia.
    4. Nathan S. Balke & Mark E. Wohar, 2006. "What Drives Stock Prices? Identifying the Determinants of Stock Price Movements," Southern Economic Journal, John Wiley & Sons, vol. 73(1), pages 55-78, July.
    5. Wang, Yuming & Ma, Jinpeng, 2014. "Excess volatility and the cross-section of stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 27(C), pages 1-16.
    6. Xiaoji Lin & Fan Yang & Frederico Belo, 2014. "External Equity Financing Costs, Financial Flows, and Asset Prices," 2014 Meeting Papers 863, Society for Economic Dynamics.
    7. Javier Gómez Pineda, 2004. "Inflation Targeting, Sudden Stops and the Cost of Fear of Floating," Borradores de Economia 276, Banco de la Republica de Colombia.
    8. Guo, Hui & Savickas, Robert, 2008. "Forecasting foreign exchange rates using idiosyncratic volatility," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1322-1332, July.
    9. repec:rim:rimwps:19-01 is not listed on IDEAS
    10. Simon Price, 2004. "UK investment and the return to equity: Q redux," Money Macro and Finance (MMF) Research Group Conference 2004 87, Money Macro and Finance Research Group.
    11. Kewei Hou & Haitao Mo & Chen Xue & Lu Zhang, 2019. "Which Factors?," Review of Finance, European Finance Association, vol. 23(1), pages 1-35.
    12. Xiaoji Lin & Ding Luo & Andres Donangelo & Frederico Belo, 2017. "Labor Hiring, Aggregate Dividends, and Return Predictability in the Time Series," 2017 Meeting Papers 885, Society for Economic Dynamics.
    13. Ekaterini Panopoulou & Nikitas Pittis & Sarantis Kalyvitis, 2010. "Looking far in the past: revisiting the growth-returns nexus with non-parametric tests," Empirical Economics, Springer, vol. 38(3), pages 743-766, June.
    14. 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.
    15. Bernard Dumas & Alexander Kurshev & Raman Uppal, 2005. "What Can Rational Investors Do About Excessive Volatility and Sentiment Fluctuations?," NBER Working Papers 11803, National Bureau of Economic Research, Inc.
    16. Tim Bollerslev & Robert J. Hodrick, 1992. "Financial Market Efficiency Tests," NBER Working Papers 4108, National Bureau of Economic Research, Inc.
    17. Huifeng Chang & Adrien D'Avernas & Andrea L. Eisfeldt, 2024. "Bonds versus Equities: Information for Investment," Journal of Finance, American Finance Association, vol. 79(6), pages 3893-3941, December.
    18. Mendieta-Muñoz Ivan, 2024. "Time-varying Investment Dynamics in the USA," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 18(1), pages 1-18.
    19. Yen-Hsiao Chen & Patricia Fraser, 2010. "What drives stock prices? Fundamentals, bubbles and investor behaviour," Applied Financial Economics, Taylor & Francis Journals, vol. 20(18), pages 1461-1477.
    20. Binswanger, Mathias, 2004. "How important are fundamentals?--Evidence from a structural VAR model for the stock markets in the US, Japan and Europe," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 185-201, April.
    21. Javier G�mez, 2004. "Inflation Targeting and Sudden Stops," Borradores de Economia 2854, Banco de la Republica.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:cpr:ceprdp:3105. 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: CEPR (email available below). General contact details of provider: https://cepr.org/ .

    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.