Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-15T03:53:02.805Z Has data issue: false hasContentIssue false
  • English
  • Français

On the Relation between EGARCH Idiosyncratic Volatility and Expected Stock Returns

Published online by Cambridge University Press:  30 January 2014

Hui Guo ,
Haimanot Kassa  and
Michael F. Ferguson
Hui Guo
Affiliation:
hui.guo@uc.edu, Lindner College of Business, University of Cincinnati, PO Box 210195, Cincinnati, OH 45221
Haimanot Kassa
Affiliation:
kassah@miamioh.edu, Farmer School of Business, Miami University, 800 E High St, Oxford, OH 45056.
Michael F. Ferguson
Affiliation:
michael.ferguson@uc.edu, Lindner College of Business, University of Cincinnati, PO Box 210195, Cincinnati, OH 45221
Get access Rights & Permissions [Opens in a new window]

Abstract

A spurious positive relation between exponential generalized autoregressive conditional heteroskedasticity (EGARCH) estimates of expected month t idiosyncratic volatility and month t stock returns arises when the month t return is included in estimation of model parameters. We illustrate via simulations that this look-ahead bias is problematic for empirically observed degrees of stock return skewness and typical monthly return time series lengths. Moreover, the empirical idiosyncratic risk-return relation becomes negligible when expected month t idiosyncratic volatility is estimated using returns only up to month t − 1.

Type
Research Articles
Information
Journal of Financial and Quantitative Analysis , Volume 49 , Issue 1 , February 2014 , pp. 271 - 296
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Amihud, Y. “Illiquidity and Stock Returns.” Journal of Financial Markets, 5 (2002), 31–56.Google Scholar
Amihud, Y., and Mendelson, H.. “Dealership Market: Market-Making with Inventory.” Journal of Financial Economics, 8 (1980), 31–53.Google Scholar
Ang, A.; Hodrick, R.; Xing, Y.; and Zhang, X.. “The Cross-Section of Volatility and Expected Returns.” Journal of Finance, 61 (2006), 259–299.Google Scholar
Ang, A.; Hodrick, R.; Xing, Y.; and Zhang, X.. “High Idiosyncratic Volatility and Low Returns: International and Further U.S. Evidence.” Journal of Financial Economics, 91 (2009), 1–23.Google Scholar
Asparouhova, E.; Bessembinder, H.; and Kalcheva, I.. “Noisy Prices and Inference Regarding Returns.” Journal of Finance, 68 (2013), 665–714.Google Scholar
Bali, T., and Cakici, N.. “Idiosyncratic Volatility and the Cross-Section of Expected Returns.” Journal of Financial and Quantitative Analysis, 43 (2008), 29–58.Google Scholar
Bali, T.; Cakici, N.; and Whitelaw, R.. “Maxing Out: Stocks as Lotteries and the Cross-Section of Expected Returns.” Journal of Financial Economics, 99 (2011), 427–446.Google Scholar
Bali, T.; Cakici, N.; Yan, X.; and Zhang, Z.. “Does Idiosyncratic Volatility Really Matter?” Journal of Finance, 60 (2005), 905–929.Google Scholar
Bali, T.; Scherbina, A.; and Tang, Y.. “Unusual News Events and the Cross-Section of Stock Returns.” Working Paper, Baruch College (2010).CrossRefGoogle Scholar
Blume, M., and Friend, I.. “The Asset Structure of Individual Portfolios and Some Implications of Utility Functions.” Journal of Finance, 30 (1975), 585–603.Google Scholar
Boyer, B.; Mitton, T.; and Vorkink, K.. “Expected Idiosyncratic Skewness.” Review of Financial Studies, 23 (2010), 169–202.Google Scholar
Brockman, P., and Schutte, M.. “Is Idiosyncratic Volatility Priced? The International Evidence.” Working Paper, University of Missouri–Columbia (2007).Google Scholar
Duffee, G. “Stock Returns and Volatility: A Firm-Level Analysis.” Journal of Financial Economics, 37 (1995), 399–420.CrossRefGoogle Scholar
Fama, E., and French, K.. “Multifactor Explanations of Asset Pricing Anomalies.” Journal of Finance, 51 (1996), 55–84.Google Scholar
Fama, E., and MacBeth, J.. “Risk, Return, and Equilibrium: Empirical Tests.” Journal of Political Economy, 71 (1973), 607–636.CrossRefGoogle Scholar
Fink, J.; Fink, K.; and He, H.. “Idiosyncratic Volatility Measures and Expected Return.” Financial Management, 41 (2012), 519–553.Google Scholar
Fleishman, A. I. “A Method for Simulating Non-Normal Distributions.” Psychometrika, 43 (1978), 521–532.Google Scholar
Fu, F. “Idiosyncratic Risk and the Cross-Section of Expected Stock Returns.” Journal of Financial Economics, 91 (2009), 24–37.Google Scholar
Goetzmann, W., and Kumar, A.. “Equity Portfolio Diversification.” Review of Finance, 12 (2008), 433–463.Google Scholar
Han, Y., and Lesmond, D.. “Liquidity Biases and the Pricing of Cross-Sectional Idiosyncratic Volatility.” Review of Financial Studies, 24 (2011), 1590–1629.Google Scholar
Huang, W.; Liu, Q.; Rhee, S.; and Zhang, L.. “Return Reversals, Idiosyncratic Risk and Expected Returns.” Review of Financial Studies, 23 (2010), 147–168.Google Scholar
Jiang, G.; Xu, D.; and Yao, T.. “The Information Content of Idiosyncratic Volatility.” Journal of Financial and Quantitative Analysis, 44 (2009), 1–28.Google Scholar
Levy, H. “Equilibrium in an Imperfect Market: a Constraint on the Number of Securities in the Portfolio.” American Economic Review, 68 (1978), 643–658.Google Scholar
Lundblad, C. “The Risk Return Tradeoff in the Long Run: 1836–2003.” Journal of Financial Economics, 85 (2007), 123–150.Google Scholar
Malkiel, B., and Xu, Y.. “Idiosyncratic Risk and Security Returns.” Working Paper, University of Texas at Dallas (2002).Google Scholar
Merton, R. “A Simple Model of Capital Market Equilibrium with Incomplete Information.” Journal of Finance, 42 (1987), 483–510.Google Scholar
Newey, W., and West, K.. “A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix.” Econometrica, 55 (1987), 703–708.Google Scholar
Peterson, D., and Smedema, A.. “The Return Impact of Realized and Expected Idiosyncratic Volatility.” Journal of Banking and Finance, 35 (2011), 2547–2558.Google Scholar
Ramberg, J. S., and Schmeiser, B.. “An Approximate Method for Generating Asymmetric Random Variables.” Communications of the ACM, 17 (1974), 78–82.Google Scholar
Scruggs, J. “Resolving the Puzzling Intertemporal Relation between the Market Risk Premium and Conditional Market Variance: A Two-Factor Approach.” Journal of Finance, 53 (1998), 575–603.Google Scholar
Spiegel, M., and Wang, X.. “Cross-Sectional Variation in Stock Returns: Liquidity and Idiosyncratic Risk.” Working Paper, Yale University (2005).Google Scholar