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Stock Return Dynamics Under Earnings Management

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  • Xiaotong Wang
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    Abstract

    This paper explores how earnings management influences asset returns and return volatility via real economic activity. In the model, firms smooth earnings via the costly and economically suboptimal intertemporal transfer of assets and liabilities. As a result, the firm's stock return follows a process that conforms to an EGARCH-like statistical model. The key idea is that real earnings management generates an unobservable cost, and the market has to infer the underlying wealth of the firm from the smoothed reported earnings series. This framework may help explain why asset returns underreact to good news and overreact to bad news, while no news is always good news to the market. Empirical evidence that earnings innovations impact future return volatility, in line with the model's predictions, is found in the data.

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    File URL: http://icfpub.som.yale.edu/publications/2633
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    Bibliographic Info

    Paper provided by Yale School of Management in its series Yale School of Management Working Papers with number amz2633.

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    Date of creation: 01 Dec 2005
    Date of revision: 01 Jul 2006
    Handle: RePEc:ysm:somwrk:amz2633

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    Web page: http://icf.som.yale.edu/
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    Related research

    Keywords: Earnings managment; EGARCH Working Paper Series;

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    1. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    2. Paul Gompers & Joy Ishii & Andrew Metrick, 2003. "Corporate Governance And Equity Prices," The Quarterly Journal of Economics, MIT Press, vol. 118(1), pages 107-155, February.
    3. Harvey,Andrew C., 1990. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521321969, October.
    4. Graham, John R. & Harvey, Campbell R. & Rajgopal, Shiva, 2005. "The economic implications of corporate financial reporting," Journal of Accounting and Economics, Elsevier, vol. 40(1-3), pages 3-73, December.
    5. Engle III, Robert F., 2003. "Risk and Volatility: Econometric Models and Financial Practice," Nobel Prize in Economics documents 2003-4, Nobel Prize Committee.
    6. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
    7. Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
    8. Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
    9. Timothy C. Johnson, 2001. "Return Dynamics when Persistence is Unobservable," Mathematical Finance, Wiley Blackwell, vol. 11(4), pages 415-445.
    10. Brennan, Michael J. & Subrahmanyam, Avanidhar, 1995. "Investment analysis and price formation in securities markets," Journal of Financial Economics, Elsevier, vol. 38(3), pages 361-381, July.
    11. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    12. Geert Bekaert & Guojun Wu, 1997. "Asymmetric Volatility and Risk in Equity Markets," NBER Working Papers 6022, National Bureau of Economic Research, Inc.
    13. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    14. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    15. Veronesi, Pietro, 1999. "Stock Market Overreaction to Bad News in Good Times: A Rational Expectations Equilibrium Model," Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 975-1007.
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