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Multi-factor volatility and stock returns

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  • He, Zhongzhi (Lawrence)
  • Zhu, Jie
  • Zhu, Xiaoneng

Abstract

In light of inconclusive evidence on the relation between market volatility and stock returns, this paper proposes a multi-factor volatility model and examines its impact on cross-sectional pricing. We also evaluate the out-of-sample performance and economic significance of multi-factor volatility. We find that conditional variances of the size and value dynamic factor earn significant and positive variance risk premia. In addition, multi-factor volatility can significantly improve the out-of-sample return predictability with a positive economic gain in asset allocation.

Suggested Citation

  • He, Zhongzhi (Lawrence) & Zhu, Jie & Zhu, Xiaoneng, 2015. "Multi-factor volatility and stock returns," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 132-149.
    • Handle: RePEc:eee:jbfina:v:61:y:2015:i:s2:p:s132-s149
    DOI: 10.1016/j.jbankfin.2015.09.013
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    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. repec:bla:jfinan:v:59:y:2004:i:4:p:1743-1776 is not listed on IDEAS
    3. Jun Tu, 2010. "Is Regime Switching in Stock Returns Important in Portfolio Decisions?," Management Science, INFORMS, vol. 56(7), pages 1198-1215, July.
    4. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    5. Hui Guo & Robert F. Whitelaw, 2006. "Uncovering the Risk–Return Relation in the Stock Market," Journal of Finance, American Finance Association, vol. 61(3), pages 1433-1463, June.
    6. 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.
    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. Richardson, Scott A. & Sloan, Richard G. & Soliman, Mark T. & Tuna, Irem, 2005. "Accrual reliability, earnings persistence and stock prices," Journal of Accounting and Economics, Elsevier, vol. 39(3), pages 437-485, September.
    9. 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.
    10. Kang, Jangkoo & Kim, Tong Suk & Lee, Changjun & Min, Byoung-Kyu, 2011. "Macroeconomic risk and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3158-3173.
    11. Lewellen, Jonathan & Nagel, Stefan & Shanken, Jay, 2010. "A skeptical appraisal of asset pricing tests," Journal of Financial Economics, Elsevier, vol. 96(2), pages 175-194, May.
    12. Ludvigson, Sydney C. & Ng, Serena, 2007. "The empirical risk-return relation: A factor analysis approach," Journal of Financial Economics, Elsevier, vol. 83(1), pages 171-222, January.
    13. Ferreira, Miguel A. & Santa-Clara, Pedro, 2011. "Forecasting stock market returns: The sum of the parts is more than the whole," Journal of Financial Economics, Elsevier, vol. 100(3), pages 514-537, June.
    14. Christensen, Bent Jesper & Nielsen, Morten Ørregaard & Zhu, Jie, 2010. "Long memory in stock market volatility and the volatility-in-mean effect: The FIEGARCH-M Model," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 460-470, June.
    15. Harvey, Andrew & Ruiz, Esther & Sentana, Enrique, 1992. "Unobserved component time series models with Arch disturbances," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 129-157.
    16. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    17. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    18. Kent Daniel & Sheridan Titman, 2006. "Market Reactions to Tangible and Intangible Information," Journal of Finance, American Finance Association, vol. 61(4), pages 1605-1643, August.
    19. 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.
    20. Kewei Hou & Chen Xue & Lu Zhang, 2015. "Editor's Choice Digesting Anomalies: An Investment Approach," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 650-705.
    21. 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.
    22. Jeffrey Pontiff & Artemiza Woodgate, 2008. "Share Issuance and Cross‐sectional Returns," Journal of Finance, American Finance Association, vol. 63(2), pages 921-945, April.
    23. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    24. Henkel, Sam James & Martin, J. Spencer & Nardari, Federico, 2011. "Time-varying short-horizon predictability," Journal of Financial Economics, Elsevier, vol. 99(3), pages 560-580, March.
    25. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    26. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    27. 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.
    28. 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.
    29. Chabi-Yo, Fousseni, 2011. "Explaining the idiosyncratic volatility puzzle using Stochastic Discount Factors," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1971-1983, August.
    30. Zhu, Xiaoneng & Zhu, Jie, 2013. "Predicting stock returns: A regime-switching combination approach and economic links," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4120-4133.
    31. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    32. Shanken, Jay, 1992. "On the Estimation of Beta-Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 5(1), pages 1-33.
    33. He, Zhongzhi (Lawrence) & Zhu, Jie & Zhu, Xiaoneng, 2015. "Dynamic factors and asset pricing: International and further U.S. evidence," Pacific-Basin Finance Journal, Elsevier, vol. 32(C), pages 21-39.
    34. Jeff Fleming & Chris Kirby & Barbara Ostdiek, 2001. "The Economic Value of Volatility Timing," Journal of Finance, American Finance Association, vol. 56(1), pages 329-352, February.
    35. Lo, Andrew W & MacKinlay, A Craig, 1990. "Data-Snooping Biases in Tests of Financial Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 431-467.
    36. Ralitsa Petkova, 2006. "Do the Fama–French Factors Proxy for Innovations in Predictive Variables?," Journal of Finance, American Finance Association, vol. 61(2), pages 581-612, April.
    37. Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
    38. Itamar Drechsler & Amir Yaron, 2011. "What's Vol Got to Do with It," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 1-45.
    39. He, Zhongzhi (Lawrence) & Huh, Sahn-Wook & Lee, Bong-Soo, 2010. "Dynamic Factors and Asset Pricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(3), pages 707-737, June.
    40. Simin, Timothy, 2008. "The Poor Predictive Performance of Asset Pricing Models," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(2), pages 355-380, June.
    41. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    42. 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.
    43. Titman, Sheridan & Wei, K. C. John & Xie, Feixue, 2004. "Capital Investments and Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(4), pages 677-700, December.
    44. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
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    More about this item

    Keywords

    Multi-factor volatility; Cross-sectional returns; Out-of-sample predictability; Asset allocation;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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