IDEAS home Printed from https://ideas.repec.org/a/eee/empfin/v22y2013icp30-51.html
   My bibliography  Save this article

Understanding industry betas

Author

Listed:
  • Baele, Lieven
  • Londono, Juan M.

Abstract

This paper models and explains the dynamics of market betas for 30 US industry portfolios between 1970 and 2009. We use DCC–MIDAS and kernel regression techniques as alternatives to the standard ex-post measures. We find betas to exhibit substantial persistence, time variation, ranking variability, and heterogeneity in their business cycle exposure. While we find only a limited amount of structural breaks in the betas of individual industries, we do identify a common structural break in March 1998. We propose two practical applications to understand the economic significance of these results. We find the cross-sectional dispersion in industry betas to be countercyclical and negatively related to future market returns. We also find DCC–MIDAS betas to outperform other beta measures in terms of limiting the downside risk and ex-post market exposure of a market-neutral minimum-variance strategy.

Suggested Citation

  • Baele, Lieven & Londono, Juan M., 2013. "Understanding industry betas," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 30-51.
    • Handle: RePEc:eee:empfin:v:22:y:2013:i:c:p:30-51
    DOI: 10.1016/j.jempfin.2013.02.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927539813000108
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jempfin.2013.02.003?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    2. Ang, Andrew & Kristensen, Dennis, 2012. "Testing conditional factor models," Journal of Financial Economics, Elsevier, vol. 106(1), pages 132-156.
    3. repec:bla:jfinan:v:43:y:1988:i:2:p:309-25 is not listed on IDEAS
    4. Boudoukh, Jacob & Richardson, Matthew & Whitelaw, Robert F, 1994. "Industry Returns and the Fisher Effect," Journal of Finance, American Finance Association, vol. 49(5), pages 1595-1615, December.
    5. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    6. Bernanke, Ben S & Parkinson, Martin L, 1991. "Procyclical Labor Productivity and Competing Theories of the Business Cycle: Some Evidence from Interwar U.S. Manufacturing Industries," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 439-459, June.
    7. Tobias Adrian & Joshua Rosenberg, 2008. "Stock Returns and Volatility: Pricing the Short‐Run and Long‐Run Components of Market Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2997-3030, December.
    8. Fama, Eugene F. & French, Kenneth R., 1997. "Industry costs of equity," Journal of Financial Economics, Elsevier, vol. 43(2), pages 153-193, February.
    9. Jonathan B. Berk & Richard C. Green & Vasant Naik, 1999. "Optimal Investment, Growth Options, and Security Returns," Journal of Finance, American Finance Association, vol. 54(5), pages 1553-1607, October.
    10. Ferson, Wayne E & Harvey, Campbell R, 1991. "The Variation of Economic Risk Premiums," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 385-415, April.
    11. Tano Santos & Pietro Veronesi, 2004. "Conditional Betas," NBER Working Papers 10413, National Bureau of Economic Research, Inc.
    12. Zhongjun Qu & Pierre Perron, 2007. "Estimating and Testing Structural Changes in Multivariate Regressions," Econometrica, Econometric Society, vol. 75(2), pages 459-502, March.
    13. Jacquier, Eric & Titman, Sheridan & YalçIn, Atakan, 2010. "Predicting systematic risk: Implications from growth options," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 991-1005, December.
    14. repec:bla:jfinan:v:59:y:2004:i:6:p:2577-2603 is not listed on IDEAS
    15. Chernov, Mikhail & Ronald Gallant, A. & Ghysels, Eric & Tauchen, George, 2003. "Alternative models for stock price dynamics," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 225-257.
    16. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    17. Pietro Veronesi & Tano Santos, 2004. "Conditional Betas," 2004 Meeting Papers 24, Society for Economic Dynamics.
    18. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    19. Joao Gomes & Leonid Kogan & Lu Zhang, 2003. "Equilibrium Cross Section of Returns," Journal of Political Economy, University of Chicago Press, vol. 111(4), pages 693-732, August.
    20. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    21. Lewellen, Jonathan & Nagel, Stefan, 2006. "The conditional CAPM does not explain asset-pricing anomalies," Journal of Financial Economics, Elsevier, vol. 82(2), pages 289-314, November.
    22. Matías Braun & Borja Larrain, 2005. "Finance and the Business Cycle: International, Inter‐Industry Evidence," Journal of Finance, American Finance Association, vol. 60(3), pages 1097-1128, June.
    23. Stivers, Chris & Sun, Licheng, 2010. "Cross-Sectional Return Dispersion and Time Variation in Value and Momentum Premiums," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 987-1014, August.
    24. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    25. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    26. Ferson, Wayne E & Harvey, Campbell R, 1993. "The Risk and Predictability of International Equity Returns," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 527-566.
    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. González, Mariano & Nave, Juan & Rubio, Gonzalo, 2018. "Macroeconomic determinants of stock market betas," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 26-44.
    2. Naeem, Muhammad Abubakr & Balli, Faruk & Shahzad, Syed Jawad Hussain & de Bruin, Anne, 2020. "Energy commodity uncertainties and the systematic risk of US industries," Energy Economics, Elsevier, vol. 85(C).
    3. Sakemoto, Ryuta, 2023. "The long-run risk premium in the intertemporal CAPM: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    4. Fang, Libing & Yu, Honghai & Li, Lei, 2017. "The effect of economic policy uncertainty on the long-term correlation between U.S. stock and bond markets," Economic Modelling, Elsevier, vol. 66(C), pages 139-145.
    5. Anirut Pisedtasalasai, 2021. "Hedging Stocks in Crises and Market Downturns with Gold and Bonds: Industry Analysis," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 11(1), pages 1-16, January.
    6. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou & Weining Wang, 2017. "Long- and Short-Run Components of Factor Betas: Implications for Equity Pricing," CREATES Research Papers 2017-34, Department of Economics and Business Economics, Aarhus University.
    7. Rapheedah Musneh & Mohd. Rahimie Abdul Karim & Caroline Geetha A/P Arokiadasan Baburaw, 2021. "Liquidity risk and stock returns: empirical evidence from industrial products and services sector in Bursa Malaysia," Future Business Journal, Springer, vol. 7(1), pages 1-10, December.
    8. Pedro Antonio Martín-Cervantes & María del Carmen Valls Martínez, 2023. "Unraveling the relationship between betas and ESG scores through the Random Forests methodology," Risk Management, Palgrave Macmillan, vol. 25(3), pages 1-29, September.
    9. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2021. "Long- and short-run components of factor betas: Implications for stock pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    10. Tang, Guohao & Wu, Yiyong & Lou, Guanyu, 2024. "Extrapolation beyond peers: An asset pricing perspective," Journal of International Money and Finance, Elsevier, vol. 148(C).
    11. Lioui, Abraham & Tarelli, Andrea, 2020. "Factor Investing for the Long Run," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    12. Yu, Honghai & Fang, Libing & Du, Donglei & Yan, Panpan, 2017. "How EPU drives long-term industry beta," Finance Research Letters, Elsevier, vol. 22(C), pages 249-258.

    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. Londono Yarce, J.M., 2011. "Essays on asset pricing," Other publications TiSEM 744a2ac5-7ada-4fa8-a7aa-e, Tilburg University, School of Economics and Management.
    2. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2021. "Long- and short-run components of factor betas: Implications for stock pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    3. Cosemans, M. & Frehen, R.G.P. & Schotman, P.C. & Bauer, R.M.M.J., 2009. "Efficient Estimation of Firm-Specific Betas and its Benefits for Asset Pricing Tests and Portfolio Choice," MPRA Paper 23557, University Library of Munich, Germany.
    4. Ang, Andrew & Chen, Joseph, 2007. "CAPM over the long run: 1926-2001," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 1-40, January.
    5. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou & Weining Wang, 2017. "Long- and Short-Run Components of Factor Betas: Implications for Equity Pricing," CREATES Research Papers 2017-34, Department of Economics and Business Economics, Aarhus University.
    6. González, Mariano & Nave, Juan & Rubio, Gonzalo, 2018. "Macroeconomic determinants of stock market betas," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 26-44.
    7. Boguth, Oliver & Carlson, Murray & Fisher, Adlai & Simutin, Mikhail, 2011. "Conditional risk and performance evaluation: Volatility timing, overconditioning, and new estimates of momentum alphas," Journal of Financial Economics, Elsevier, vol. 102(2), pages 363-389.
    8. Sakemoto, Ryuta, 2023. "The long-run risk premium in the intertemporal CAPM: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    9. Cenesizoglu, Tolga & Reeves, Jonathan J., 2018. "CAPM, components of beta and the cross section of expected returns," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 223-246.
    10. Belén Nieto & Alfonso Novales & Gonzalo Rubio, 2015. "Macroeconomic and Financial Determinants of the Volatility of Corporate Bond Returns," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 5(04), pages 1-41, December.
    11. Ang, Andrew & Kristensen, Dennis, 2012. "Testing conditional factor models," Journal of Financial Economics, Elsevier, vol. 106(1), pages 132-156.
    12. Fernando D. Chague, 2013. "Conditional Betas and Investor Uncertainty," Working Papers, Department of Economics 2013_04, University of São Paulo (FEA-USP).
    13. 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.
    14. Tano Santos & Pietro Veronesi, 2005. "Cash-Flow Risk, Discount Risk, and the Value Premium," NBER Working Papers 11816, National Bureau of Economic Research, Inc.
    15. Chauvet, Marcelle & Senyuz, Zeynep & Yoldas, Emre, 2015. "What does financial volatility tell us about macroeconomic fluctuations?," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 340-360.
    16. Ai, Hengjie & Kiku, Dana, 2013. "Growth to value: Option exercise and the cross section of equity returns," Journal of Financial Economics, Elsevier, vol. 107(2), pages 325-349.
    17. Connor, Gregory & Suurlaht, Anita, 2013. "Dynamic stock market covariances in the Eurozone," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 353-370.
    18. Girardin, Eric & Joyeux, Roselyne, 2013. "Macro fundamentals as a source of stock market volatility in China: A GARCH-MIDAS approach," Economic Modelling, Elsevier, vol. 34(C), pages 59-68.
    19. Adrian, Tobias & Crump, Richard K. & Moench, Emanuel, 2015. "Regression-based estimation of dynamic asset pricing models," Journal of Financial Economics, Elsevier, vol. 118(2), pages 211-244.
    20. Tano Santos & Pietro Veronesi, 2004. "Conditional Betas," NBER Working Papers 10413, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    Industry betas; Component models; DCC–MIDAS; Dispersion in betas; Stock return predictability; Minimum variance strategies;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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:eee:empfin:v:22:y:2013:i:c:p:30-51. 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/jempfin .

    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.