IDEAS home Printed from https://ideas.repec.org/a/bla/ecinqu/v47y2009i1p81-97.html
   My bibliography  Save this article

Data Revisions And Out‐Of‐Sample Stock Return Predictability

Author

Listed:
  • HUI GUO

Abstract

It has been found that the consumption‐wealth ratio (cay) constructed from revised data is a strong predictor of stock market returns. This paper shows that its out‐of‐sample forecasting power becomes substantially weaker if cay is estimated using information available at the time of forecast. The difference, which mainly reflects periodic revisions in consumption and labor income data, is consistent with the conjecture that cay is a theoretically motivated variable. That is, revised data outperform real‐time data because the former have smaller measurement errors. Nevertheless, practitioners should be cautious when they need to use real‐time cay as a forecasting variable. (JEL G10, G14)

Suggested Citation

  • Hui Guo, 2009. "Data Revisions And Out‐Of‐Sample Stock Return Predictability," Economic Inquiry, Western Economic Association International, vol. 47(1), pages 81-97, January.
    • Handle: RePEc:bla:ecinqu:v:47:y:2009:i:1:p:81-97
    DOI: 10.1111/j.1465-7295.2008.00169.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1465-7295.2008.00169.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1465-7295.2008.00169.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Lettau, Martin & Ludvigson, Sydney, 2002. "Time-varying risk premia and the cost of capital: An alternative implication of the Q theory of investment," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 31-66, January.
    2. 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.
    3. Guo, Hui & Savickas, Robert, 2006. "Idiosyncratic Volatility, Stock Market Volatility, and Expected Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 43-56, January.
    4. Martin Lettau & Sydney Ludvigson, 2001. "Consumption, Aggregate Wealth, and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 815-849, June.
    5. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    6. Guo, Hui, 2004. "Limited Stock Market Participation and Asset Prices in a Dynamic Economy," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(3), pages 495-516, September.
    7. Andrew Ang & Geert Bekaert, 2007. "Stock Return Predictability: Is it There?," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 651-707.
    8. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    9. John Y. Campbell & John Cochrane, 1999. "Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 107(2), pages 205-251, April.
    10. 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.
    11. Hui Guo, 2006. "On the Out-of-Sample Predictability of Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 79(2), pages 645-670, March.
    12. 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.
    13. Brennan, Michael J. & Xia, Yihong, 2005. "tay's as good as cay," Finance Research Letters, Elsevier, vol. 2(1), pages 1-14, March.
    14. Amit Goyal & Ivo Welch, 2003. "Predicting the Equity Premium with Dividend Ratios," Management Science, INFORMS, vol. 49(5), pages 639-654, May.
    15. Bernanke, Ben & Gertler, Mark, 1989. "Agency Costs, Net Worth, and Business Fluctuations," American Economic Review, American Economic Association, vol. 79(1), pages 14-31, March.
    16. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    17. Bossaerts, Peter & Hillion, Pierre, 1999. "Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?," The Review of Financial Studies, Society for Financial Studies, vol. 12(2), pages 405-428.
    18. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.
    19. Wayne E. Ferson & Sergei Sarkissian & Timothy T. Simin, 2003. "Spurious Regressions in Financial Economics?," Journal of Finance, American Finance Association, vol. 58(4), pages 1393-1414, August.
    20. Merton, Robert C., 1980. "On estimating the expected return on the market : An exploratory investigation," Journal of Financial Economics, Elsevier, vol. 8(4), pages 323-361, December.
    21. Leitch, Gordon & Tanner, J Ernest, 1991. "Economic Forecast Evaluation: Profits versus the Conventional Error Measures," American Economic Review, American Economic Association, vol. 81(3), pages 580-590, June.
    22. Patelis, Alex D, 1997. "Stock Return Predictability and the Role of Monetary Policy," Journal of Finance, American Finance Association, vol. 52(5), pages 1951-1972, December.
    23. Michael Cooper & Roberto C. Gutierrez, Jr. & Bill Marcum, 2005. "On the Predictability of Stock Returns in Real Time," The Journal of Business, University of Chicago Press, vol. 78(2), pages 469-500, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Biswas, Anindya, 2014. "The output gap and expected security returns," Review of Financial Economics, Elsevier, vol. 23(3), pages 131-140.
    2. Stig Vinther Møller & Thomas Pedersen & Erik Christian Montes Schütte & Allan Timmermann, 2024. "Search and Predictability of Prices in the Housing Market," Management Science, INFORMS, vol. 70(1), pages 415-438, January.
    3. Stig V. Møller & Jesper Rangvid, 2012. "End-of-the-year economic growth and time-varying expected returns," CREATES Research Papers 2012-42, Department of Economics and Business Economics, Aarhus University.
    4. Eduard Baitinger & Christian Fieberg & Thorsten Poddig & Armin Varmaz, 2015. "Liquidity-driven approach to dynamic asset allocation: evidence from the German stock market," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 29(4), pages 365-379, November.
    5. Choi, Yongok & Jacewitz, Stefan & Park, Joon Y., 2016. "A reexamination of stock return predictability," Journal of Econometrics, Elsevier, vol. 192(1), pages 168-189.
    6. Della Corte, Pasquale & Sarno, Lucio & Valente, Giorgio, 2010. "A century of equity premium predictability and the consumption-wealth ratio: An international perspective," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 313-331, June.
    7. Møller, Stig V. & Rangvid, Jesper, 2015. "End-of-the-year economic growth and time-varying expected returns," Journal of Financial Economics, Elsevier, vol. 115(1), pages 136-154.

    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. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    2. Hui Guo, 2006. "On the Out-of-Sample Predictability of Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 79(2), pages 645-670, March.
    3. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.
    4. Neil Kellard & John Nankervis & Fotis Papadimitriou, 2007. "Predicting the UK Equity Premium with Dividend Ratios: An Out-Of-Sample Recursive Residuals Graphical Approach," Money Macro and Finance (MMF) Research Group Conference 2006 129, Money Macro and Finance Research Group.
    5. Guo, Hui & Savickas, Robert & Wang, Zijun & Yang, Jian, 2009. "Is the Value Premium a Proxy for Time-Varying Investment Opportunities? Some Time-Series Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(1), pages 133-154, February.
    6. João M. Sousa & Ricardo M. Sousa, 2019. "Asset Returns Under Model Uncertainty: Evidence from the Euro Area, the US and the UK," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 139-176, June.
    7. Yufeng Han, 2010. "On the Economic Value of Return Predictability," Annals of Economics and Finance, Society for AEF, vol. 11(1), pages 1-33, May.
    8. Schrimpf, Andreas, 2010. "International stock return predictability under model uncertainty," Journal of International Money and Finance, Elsevier, vol. 29(7), pages 1256-1282, November.
    9. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
    10. Hui Guo & Robert Savickas, 2003. "On the cross section of conditionally expected stock returns," Working Papers 2003-043, Federal Reserve Bank of St. Louis.
    11. John Y. Campbell, 2008. "Viewpoint: Estimating the equity premium," Canadian Journal of Economics, Canadian Economics Association, vol. 41(1), pages 1-21, February.
    12. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    13. 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.
    14. Michael Cooper & Huseyin Gulen, 2006. "Is Time-Series-Based Predictability Evident in Real Time?," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1263-1292, May.
    15. 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.
    16. Hai Lin & Daniel Quill & Henk Berkman, 2016. "Information diffusion and the predictability of New Zealand stock market returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(3), pages 749-785, September.
    17. Della Corte, Pasquale & Sarno, Lucio & Valente, Giorgio, 2010. "A century of equity premium predictability and the consumption-wealth ratio: An international perspective," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 313-331, June.
    18. Puneet Handa, 2006. "Does Stock Return Predictability Imply Improved Asset Allocation and Performance? Evidence from the U.S. Stock Market (1954–2002)," The Journal of Business, University of Chicago Press, vol. 79(5), pages 2423-2468, September.
    19. Guo, Hui & Savickas, Robert, 2006. "Idiosyncratic Volatility, Stock Market Volatility, and Expected Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 43-56, January.
    20. Kirt Butler & Katsushi Okada, 2009. "The relative contribution of conditional mean and volatility in bivariate returns to international stock market indices," Applied Financial Economics, Taylor & Francis Journals, vol. 19(1), pages 1-15.

    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:bla:ecinqu:v:47:y:2009:i:1:p:81-97. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/weaaaea.html .

    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.