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The output gap and expected security returns

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  • Biswas, Anindya

Abstract

This paper analyzes the impact of the output gap on market excess returns. The output gap is usually defined as the deviation of output from potential output that is indicated by the trend output. However, this study departs from the common approach of calculating the output gap based on a simple trend line. It uses a flexible data-driven weighting scheme, and it uses only the available information that corresponds to each forecasting origin to derive the output gap. Overall, the proposed output gap is a strong predictor of U.S. market excess returns.

Suggested Citation

  • Biswas, Anindya, 2014. "The output gap and expected security returns," Review of Financial Economics, Elsevier, vol. 23(3), pages 131-140.
    • Handle: RePEc:eee:revfin:v:23:y:2014:i:3:p:131-140
    DOI: 10.1016/j.rfe.2014.04.001
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    1. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. Ilan Cooper, 2009. "Time-Varying Risk Premiums and the Output Gap," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2601-2633, July.
    4. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    5. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    6. Marquering, Wessel & Verbeek, Marno, 2004. "The Economic Value of Predicting Stock Index Returns and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(2), pages 407-429, June.
    7. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    8. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    9. Jay Choi, Jongmoo & Hauser, Shmuel & Kopecky, Kenneth J., 1999. "Does the stock market predict real activity? Time series evidence from the G-7 countries," Journal of Banking & Finance, Elsevier, vol. 23(12), pages 1771-1792, December.
    10. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    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. Molodtsova, Tanya & Nikolsko-Rzhevskyy, Alex & Papell, David H., 2008. "Taylor rules with real-time data: A tale of two countries and one exchange rate," Journal of Monetary Economics, Elsevier, vol. 55(Supplemen), pages 63-79, October.
    14. Rangvid, Jesper, 2006. "Output and expected returns," Journal of Financial Economics, Elsevier, vol. 81(3), pages 595-624, September.
    15. Tanya Molodtsova & Alex Nikolsko-Rzhevskyy & David H. Papell, 2011. "Taylor Rules and the Euro," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43, pages 535-552, March.
    16. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    17. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    18. 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.
    19. Alper, C. Emre & Fendoglu, Salih & Saltoglu, Burak, 2008. "Forecasting Stock Market Volatilities Using MIDAS Regressions: An Application to the Emerging Markets," MPRA Paper 7460, University Library of Munich, Germany.
    20. Kirstin Hubrich & Kenneth D. West, 2010. "Forecast evaluation of small nested model sets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 574-594.
    21. 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.
    22. 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.
    23. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    24. Anderson, Evan W. & Ghysels, Eric & Juergens, Jennifer L., 2009. "The impact of risk and uncertainty on expected returns," Journal of Financial Economics, Elsevier, vol. 94(2), pages 233-263, November.
    25. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    26. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    27. Ghysels, Eric & Wright, Jonathan H., 2009. "Forecasting Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 504-516.
    28. Dean Croushore & Tom Stark, 2003. "A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 605-617, August.
    29. 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.
    30. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    31. Cochrane, John H, 1991. "Production-Based Asset Pricing and the Link between Stock Returns and Economic Fluctuations," Journal of Finance, American Finance Association, vol. 46(1), pages 209-237, March.
    32. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    33. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
    34. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
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    More about this item

    Keywords

    Market returns predictability; Output gap; Real-time data; MIDAS regression; Beta-weighting scheme;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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