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Does persistence in idiosyncratic risk proxy return-reversals?

Author

Listed:
  • Harmindar B. Nath

    (Department of Econometrics and Business Statistics, Monash University, Caulfield East 3145, Australia)

  • Vasilis Sarafidis

    (Department of Econometrics and Business Statistics, Monash University, Caulfield East 3145, Australia)

Abstract

Understanding the return-reversal phenomenon observed to generate large abnormal profits under some stock market trading strategies is of considerable interest in finance. There is also much debate over the use of idiosyncratic risk as a predictor in asset pricing models when it is persistent. This paper, using the Australian data, presents new empirical evidence of return-reversals at the firm level and the existence of an equilibrium state based on robust econometric methodology of panel error-correction model. The method exploits the persistence in idiosyncratic risk and builds on its cointegration with the returns series. Our results reveal the tendency of long-run returns to restore equilibrium, reversals in short-run returns, a slower recovery to equilibrium by small stocks, and while the short-run responses of returns to changes in log book-to-market ratios are positive, their reaction to persistence in idiosyncratic volatility causes the reversal process. The pattern in quantile dependent coeffi cients of short-run idiosyncratic risk-return relationship suggests that (i) the changes in idiosyncratic volatility risk adversely affects the short-run returns of low performing stocks but investments in high performing stocks benefi t from such changes; (ii) the increasing trend in the coeffi cients implies a quadratic relationship in the levels of the two series. The signifi cant marginal effects of changes in idiosyncratic volatility and its one period lagged values on changes in returns at many quantiles support the impact being due to persistence in idiosyncratic risk, and their reversing signs provide an evidence of reversion in short-run returns.

Suggested Citation

  • Harmindar B. Nath & Vasilis Sarafidis, 2017. "Does persistence in idiosyncratic risk proxy return-reversals?," Journal of Banking and Financial Economics, University of Warsaw, Faculty of Management, vol. 2(8), pages 27-53, October.
  • Handle: RePEc:sgm:jbfeuw:v:2:y:2017:i:8:p:27-53
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    References listed on IDEAS

    as
    1. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    2. Xiaoquan Jiang & Bong‐Soo Lee, 2006. "The Dynamic Relation Between Returns and Idiosyncratic Volatility," Financial Management, Financial Management Association International, vol. 35(2), pages 43-65, June.
    3. William L. Beedles & Peter Dodd & R. R. Officer, 1988. "Regularities in Australian Share Returns," Australian Journal of Management, Australian School of Business, vol. 13(1), pages 1-29, June.
    4. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    5. Kuan, Tsung-Han & Li, Chu-Shiu & Liu, Chwen-Chi, 2012. "Corporate governance and cash holdings: A quantile regression approach," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 303-314.
    6. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(3), pages 597-625, June.
    7. Joakim Westerlund, 2007. "Testing for Error Correction in Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(6), pages 709-748, December.
    8. 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.
    9. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    10. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    11. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    12. Jegadeesh, Narasimhan, 1990. "Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    13. Merton, Robert C., 1971. "Optimum consumption and portfolio rules in a continuous-time model," Journal of Economic Theory, Elsevier, vol. 3(4), pages 373-413, December.
    14. Kumar, Saten & Rao, B. Bhaskara, 2012. "Error-correction based panel estimates of the demand for money of selected Asian countries with the extreme bounds analysis," Economic Modelling, Elsevier, vol. 29(4), pages 1181-1188.
    15. Jiang, George J. & Xu, Danielle & Yao, Tong, 2009. "The Information Content of Idiosyncratic Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(1), pages 1-28, February.
    16. Robert Connolly & Chris Stivers, 2003. "Momentum and Reversals in Equity‐Index Returns During Periods of Abnormal Turnover and Return Dispersion," Journal of Finance, American Finance Association, vol. 58(4), pages 1521-1556, August.
    17. Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
    18. Gilbert W. Bassett Jr. & Hsiu-Lang Chen, 2001. "Portfolio style: Return-based attribution using quantile regression," Empirical Economics, Springer, vol. 26(1), pages 293-305.
    19. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    20. repec:bla:jfinan:v:58:y:2003:i:3:p:975-1008 is not listed on IDEAS
    21. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    22. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    23. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2005. "Evidence on the speed of convergence to market efficiency," Journal of Financial Economics, Elsevier, vol. 76(2), pages 271-292, May.
    24. 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.
    25. Angelidis, Timotheos & Tessaromatis, Nikolaos, 2008. "Idiosyncratic volatility and equity returns: UK evidence," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 539-556, June.
    26. Doron Avramov & Tarun Chordia & Amit Goyal, 2006. "Liquidity and Autocorrelations in Individual Stock Returns," Journal of Finance, American Finance Association, vol. 61(5), pages 2365-2394, October.
    27. Xiaoquan Jiang & Bong-Soo Lee, 2006. "The Dynamic Relation Between Returns and Idiosyncratic Volatility," Financial Management, Financial Management Association, vol. 35(2), Summer.
    28. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    29. Matteo P. Arena & K. Stephen Haggard & Xuemin (Sterling) Yan, 2008. "Price Momentum and Idiosyncratic Volatility," The Financial Review, Eastern Finance Association, vol. 43(2), pages 159-190, May.
    30. Michelle L. Barnes & Anthony W. Hughes, 2002. "A quantile regression analysis of the cross section of stock market returns," Working Papers 02-2, Federal Reserve Bank of Boston.
    31. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    32. 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.
    33. repec:bla:jfinan:v:53:y:1998:i:1:p:267-284 is not listed on IDEAS
    34. Tim Brailsford & Clive Gaunt & Michael A O’Brien, 2012. "Size and book-to-market factors in Australia," Australian Journal of Management, Australian School of Business, vol. 37(2), pages 261-281, August.
    35. Levy, Haim, 1978. "Equilibrium in an Imperfect Market: A Constraint on the Number of Securities in the Portfolio," American Economic Review, American Economic Association, vol. 68(4), pages 643-658, September.
    36. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    37. Nath, Harmindar B. & Brooks, Robert D., 2015. "Assessing the idiosyncratic risk and stock returns relation in heteroskedasticity corrected predictive models using quantile regression," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 94-111.
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    More about this item

    Keywords

    Return reversals; idiosyncratic risk; panel cointegration; panel ECM; quantile regression;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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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