IDEAS home Printed from https://ideas.repec.org/p/aah/create/2010-50.html

The Risk-Return Tradeoff and Leverage Effect in a Stochastic Volatility-in-Mean Model

Author

Listed:
  • Bent Jesper Christensen

    (Aarhus University, School of Economics and Management, Bartholins Allé 10, Aarhus, Denmark & CREATES)

  • Petra Posedel

    (University of Zagreb)

Abstract

We study the risk premium and leverage effect in the S&P500 market using the stochastic volatility-in-mean model of Barndor¤-Nielsen & Shephard (2001). The Merton (1973, 1980) equilibrium asset pricing condition linking the conditional mean and conditional variance of discrete time returns is reinterpreted in terms of the continuous time model. Tests are performed on the risk-return relation, the leverage effect, and the overidentifying zero intercept restriction in the Merton condition. Results are compared across alternative volatility proxies, in particular, realized volatility from high-frequency (5-minute) returns, implied Black-Scholes volatility backed out from observed option prices, model-free implied volatility (VIX), and staggered bipower variation. Our results are consistent with a positive risk-return relation and a significant leverage effect, whereas an additional overidentifying zero intercept condition is rejected. We also show that these inferences are sensitive to the exact timing of the chosen olatility proxy. Robustness of the conclusions is verified in bootstrap experiments.

Suggested Citation

  • Bent Jesper Christensen & Petra Posedel, 2010. "The Risk-Return Tradeoff and Leverage Effect in a Stochastic Volatility-in-Mean Model," CREATES Research Papers 2010-50, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2010-50
    as

    Download full text from publisher

    File URL: https://repec.econ.au.dk/repec/creates/rp/10/rp10_50.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ole E. Barndorff-Nielsen & Neil Shephard, 2006. "Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation," Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 1-30.
    2. Muller, Ulrich A. & Dacorogna, Michel M. & Olsen, Richard B. & Pictet, Olivier V. & Schwarz, Matthias & Morgenegg, Claude, 1990. "Statistical study of foreign exchange rates, empirical evidence of a price change scaling law, and intraday analysis," Journal of Banking & Finance, Elsevier, vol. 14(6), pages 1189-1208, December.
    3. Blundell,Richard & Newey,Whitney K. & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521871532, January.
    4. Blundell,Richard & Newey,Whitney & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521871549, January.
    5. Blundell,Richard & Newey,Whitney & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521692106, January.
    6. Blundell,Richard & Newey,Whitney K. & Persson,Torsten (ed.), 2007. "Advances in Economics and Econometrics," Cambridge Books, Cambridge University Press, number 9780521692090, January.
    Full references (including those not matched with items on IDEAS)

    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. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    2. Douglas G. Santos & Flavio A. Ziegelmann, 2014. "Volatility Forecasting via MIDAS, HAR and their Combination: An Empirical Comparative Study for IBOVESPA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(4), pages 284-299, July.
    3. Tim Bollerslev & Sophia Zhengzi Li & Viktor Todorov, 2014. "Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns," CREATES Research Papers 2014-48, Department of Economics and Business Economics, Aarhus University.
    4. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
    5. Andersen, Torben G. & Fusari, Nicola & Todorov, Viktor & Varneskov, Rasmus T., 2019. "Unified inference for nonlinear factor models from panels with fixed and large time span," Journal of Econometrics, Elsevier, vol. 212(1), pages 4-25.
    6. Federico M. Bandi & Roberto Reno, 2009. "Nonparametric Stochastic Volatility," Global COE Hi-Stat Discussion Paper Series gd08-035, Institute of Economic Research, Hitotsubashi University.
    7. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
    8. Ole E. Barndorff-Nielsen & Almut E. D. Veraart, 2009. "Stochastic volatility of volatility in continuous time," CREATES Research Papers 2009-25, Department of Economics and Business Economics, Aarhus University.
    9. Ysusi Carla, 2007. "Multipower Variation Under Market Microstructure Effects," Working Papers 2007-13, Banco de México.
    10. Almut Veraart & Luitgard Veraart, 2012. "Stochastic volatility and stochastic leverage," Annals of Finance, Springer, vol. 8(2), pages 205-233, May.
    11. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    12. Ole E. Barndorff-Nielsen & Silja Kinnebrock & Neil Shephard, 2008. "Measuring downside risk - realised semivariance," OFRC Working Papers Series 2008fe01, Oxford Financial Research Centre.
    13. José E. Figueroa-López & Jeffrey Nisen, 2019. "Second-order properties of thresholded realized power variations of FJA additive processes," Statistical Inference for Stochastic Processes, Springer, vol. 22(3), pages 431-474, October.
    14. Qiang Liu & Zhi Liu & Chuanhai Zhang, 2020. "Heteroscedasticity test of high-frequency data with jumps and microstructure noise," Papers 2010.07659, arXiv.org.
    15. Kalnina, Ilze & Linton, Oliver, 2007. "Inference about realized volatility using infill subsampling," LSE Research Online Documents on Economics 4411, London School of Economics and Political Science, LSE Library.
    16. Bent Jesper Christensen & Morten Ørregaard Nielsen, 2007. "The Effect of Long Memory in Volatility on Stock Market Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 684-700, November.
    17. Vetter, Mathias & Podolskij, Mark, 2006. "Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps," Technical Reports 2006,51, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    18. Ysusi Carla, 2006. "Detecting Jumps in High-Frequency Financial Series Using Multipower Variation," Working Papers 2006-10, Banco de México.
    19. Neil Shephard & Kevin Sheppard, 2010. "Realising the future: forecasting with high-frequency-based volatility (HEAVY) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 197-231.
    20. Dimitrios I. Vortelinos, 2015. "The Effect of Macro News on Volatility and Jumps," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 425-447, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • L12 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Monopoly; Monopolization Strategies

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:aah:create:2010-50. 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: the person in charge (email available below). General contact details of provider: http://www.econ.au.dk/afn/ .

    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.