IDEAS home Printed from https://ideas.repec.org/a/wsi/rpbfmp/v22y2019i03ns0219091519500188.html
   My bibliography  Save this article

Are All Forecasts Made Equal? Conditioning Models on Fit to Improve Accuracy

Author

Listed:
  • David Newton

    (Department of Finance, Concordia University, 1450 Guy street, Montreal, Quebec H3H 0A1, Canada)

Abstract

We present a parsimonious method of improving forecasts and show that fit, the discrepancy between model forecasts and realized values, is persistent for individual stocks. Conditioning on fit profoundly affects the forecast error for future and out-of-sample returns. Forecasts of stock price direction with the best (worst) decile of historical fit are correct 63.6% (49.2%) of the time and are significantly different from the unconditioned model’s 56% accuracy. We find that superior factor forecasts are essential to profit from model conditioning and conclude that analysts who possess superior factor estimates can dramatically improve their forecasts through the technique we present.

Suggested Citation

  • David Newton, 2019. "Are All Forecasts Made Equal? Conditioning Models on Fit to Improve Accuracy," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-32, September.
  • Handle: RePEc:wsi:rpbfmp:v:22:y:2019:i:03:n:s0219091519500188
    DOI: 10.1142/S0219091519500188
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219091519500188
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219091519500188?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Han, Bong H & Manry, David & Shaw, Wayne, 2001. "Improving the Precision of Analysts' Earnings Forecasts by Adjusting for Predictable Bias," Review of Quantitative Finance and Accounting, Springer, vol. 17(1), pages 81-98, July.
    2. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    3. Kris Jacobs & Kevin Q. Wang, 2004. "Idiosyncratic Consumption Risk and the Cross Section of Asset Returns," Journal of Finance, American Finance Association, vol. 59(5), pages 2211-2252, October.
    4. Frazzini, Andrea & Lamont, Owen A., 2008. "Dumb money: Mutual fund flows and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 88(2), pages 299-322, May.
    5. Eric Ghysels, 1998. "On Stable Factor Structures in the Pricing of Risk: Do Time-Varying Betas Help or Hurt?," Journal of Finance, American Finance Association, vol. 53(2), pages 549-573, April.
    6. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    7. Ferson, Wayne E & Harvey, Campbell R, 1991. "The Variation of Economic Risk Premiums," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 385-415, April.
    8. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    9. 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.
    10. Harry Mamaysky & Matthew Spiegel & Hong Zhang, 2007. "Improved Forecasting of Mutual Fund Alphas and Betas," Review of Finance, European Finance Association, vol. 11(3), pages 359-400.
    11. Ron Giammarino & Murray Carlson & Adlai Fisher, 2004. "Corporate Investment and Asset Price Dynamics: Implications for Post-SEO Performance," 2004 Meeting Papers 812, Society for Economic Dynamics.
    12. Hsiao-Tien Pao & Yao-Yu Chih, 2005. "Comparison of Linear and Nonlinear Models for Panel Data Forecasting: Debt Policy in Taiwan," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 8(03), pages 525-541.
    13. Kazuhiko Nishina & Nabil Maghrebi & Mark J. Holmes, 2012. "Nonlinear Adjustments of Volatility Expectations to Forecast Errors: Evidence from Markov-Regime Switches in Implied Volatility," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 1-23.
    14. 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.
    15. Murray Carlson & Adlai Fisher & Ron Giammarino, 2004. "Corporate Investment and Asset Price Dynamics: Implications for the Cross-section of Returns," Journal of Finance, American Finance Association, vol. 59(6), pages 2577-2603, December.
    16. Ferson, Wayne E & Korajczyk, Robert A, 1995. "Do Arbitrage Pricing Models Explain the Predictability of Stock Returns?," The Journal of Business, University of Chicago Press, vol. 68(3), pages 309-349, July.
    17. Huong Higgins, 2011. "Forecasting stock price with the residual income model," Review of Quantitative Finance and Accounting, Springer, vol. 36(4), pages 583-604, May.
    18. Kim, Yongtae & Lobo, Gerald J. & Song, Minsup, 2011. "Analyst characteristics, timing of forecast revisions, and analyst forecasting ability," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 2158-2168, August.
    19. Henderson, Brian J. & Marks, Joseph M., 2013. "Predicting forecast errors through joint observation of earnings and revenue forecasts," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4265-4277.
    20. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    21. Martin Lettau & Sydney Ludvigson, 2001. "Resurrecting the (C)CAPM: A Cross-Sectional Test When Risk Premia Are Time-Varying," Journal of Political Economy, University of Chicago Press, vol. 109(6), pages 1238-1287, December.
    22. 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.
    23. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
    24. John M. Griffin & Jin Xu, 2009. "How Smart Are the Smart Guys? A Unique View from Hedge Fund Stock Holdings," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2331-2370, July.
    25. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    26. Lily Fang & Joel Peress, 2009. "Media Coverage and the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 64(5), pages 2023-2052, October.
    27. 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.
    28. Eugene F. Fama & Kenneth R. French, 2016. "Dissecting Anomalies with a Five-Factor Model," The Review of Financial Studies, Society for Financial Studies, vol. 29(1), pages 69-103.
    29. Lee, Cheng-Few & Liaw, K. Thomas & Wu, Chunchi, 1992. "Forecasting accuracy of alternative dividend models," International Review of Economics & Finance, Elsevier, vol. 1(3), pages 261-270.
    30. Harrison Hong & Jeffrey D. Kubik, 2003. "Analyzing the Analysts: Career Concerns and Biased Earnings Forecasts," Journal of Finance, American Finance Association, vol. 58(1), pages 313-351, February.
    31. Ferson, Wayne E & Harvey, Campbell R, 1993. "The Risk and Predictability of International Equity Returns," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 527-566.
    Full references (including those not matched with items on IDEAS)

    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. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    2. Stefan Nagel, 2013. "Empirical Cross-Sectional Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 5(1), pages 167-199, November.
    3. Stefano Gubellini, 2014. "Conditioning information and cross-sectional anomalies," Review of Quantitative Finance and Accounting, Springer, vol. 43(3), pages 529-569, October.
    4. Constantinos Antoniou & John A. Doukas & Avanidhar Subrahmanyam, 2016. "Investor Sentiment, Beta, and the Cost of Equity Capital," Management Science, INFORMS, vol. 62(2), pages 347-367, February.
    5. 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.
    6. Avanidhar Subrahmanyam, 2010. "The Cross†Section of Expected Stock Returns: What Have We Learnt from the Past Twenty†Five Years of Research?," European Financial Management, European Financial Management Association, vol. 16(1), pages 27-42, January.
    7. Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015. "Aggregate volatility expectations and threshold CAPM," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
    8. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, September.
    9. De Moor, Lieven & Sercu, Piet, 2013. "The smallest firm effect: An international study," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 129-155.
    10. Chabi-Yo, Fousseni & Ruenzi, Stefan & Weigert, Florian, 2018. "Crash Sensitivity and the Cross Section of Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1059-1100, June.
    11. Yan Li & Liangjun Su & Yuewu Xu, 2015. "A Combined Approach to the Inference of Conditional Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 203-220, April.
    12. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    13. Campbell R. Harvey & Yan Liu & Heqing Zhu, 2014. ". . . and the Cross-Section of Expected Returns," NBER Working Papers 20592, National Bureau of Economic Research, Inc.
    14. Jegadeesh, Narasimhan & Noh, Joonki & Pukthuanthong, Kuntara & Roll, Richard & Wang, Junbo, 2019. "Empirical tests of asset pricing models with individual assets: Resolving the errors-in-variables bias in risk premium estimation," Journal of Financial Economics, Elsevier, vol. 133(2), pages 273-298.
    15. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021.
    16. Bai, Jennie & Bali, Turan G. & Wen, Quan, 2021. "Is there a risk-return tradeoff in the corporate bond market? Time-series and cross-sectional evidence," Journal of Financial Economics, Elsevier, vol. 142(3), pages 1017-1037.
    17. Zaremba, Adam & Cakici, Nusret & Bianchi, Robert J. & Long, Huaigang, 2023. "Interest rate changes and the cross-section of global equity returns," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    18. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2020. "Beta uncertainty," Journal of Banking & Finance, Elsevier, vol. 116(C).
    19. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    20. repec:gnv:wpaper:unige:76321 is not listed on IDEAS
    21. Nader Virk & Hilal Butt, 2016. "Specification errors of asset-pricing models for a market characterized by few large capitalization firms," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 40(1), pages 68-84, January.

    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:wsi:rpbfmp:v:22:y:2019:i:03:n:s0219091519500188. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/rpbfmp/rpbfmp.shtml .

    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.