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The “out-of-sample” performance of long run risk models

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  • Ferson, Wayne
  • Nallareddy, Suresh
  • Xie, Biqin

Abstract

This paper studies the ability of long-run risk models to explain out-of-sample asset returns during 1931–2009. The long-run risk models perform relatively well on the momentum effect.

Suggested Citation

  • Ferson, Wayne & Nallareddy, Suresh & Xie, Biqin, 2013. "The “out-of-sample” performance of long run risk models," Journal of Financial Economics, Elsevier, vol. 107(3), pages 537-556.
  • Handle: RePEc:eee:jfinec:v:107:y:2013:i:3:p:537-556
    DOI: 10.1016/j.jfineco.2012.09.006
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    2. Mathias S. Kruttli, 2016. "From Which Consumption-Based Asset Pricing Models Can Investors Profit? Evidence from Model-Based Priors," Finance and Economics Discussion Series 2016-027, Board of Governors of the Federal Reserve System (U.S.).
    3. Claude Bergeron, 2019. "Recursive preferences, long-run risks, and stock valuation," Economics Bulletin, AccessEcon, vol. 39(2), pages 996-1004.
    4. Kolari, James W. & Huang, Jianhua Z. & Butt, Hilal Anwar & Liao, Huiling, 2022. "International tests of the ZCAPM asset pricing model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    5. Grammig, Joachim & Schaub, Eva-Maria, 2014. "Give me strong moments and time - Combining GMM and SMM to estimate long-run risk asset pricing models," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100607, Verein für Socialpolitik / German Economic Association.
    6. Doron Avramov & Satadru Hore, 2015. "Cross-Sectional Factor Dynamics and Momentum Returns," Supervisory Research and Analysis Working Papers RPA 15-2, Federal Reserve Bank of Boston.
    7. Jean-Yves Pitarakis, 2020. "A Novel Approach to Predictive Accuracy Testing in Nested Environments," Papers 2008.08387, arXiv.org, revised Oct 2023.
    8. Ahmed, Shamim & Tsvetanov, Daniel, 2016. "The predictive performance of commodity futures risk factors," Journal of Banking & Finance, Elsevier, vol. 71(C), pages 20-36.
    9. Weidong Tian & Qing Zhou, 2017. "Asset Pricing Model Uncertainty: A Tradeoff between Bias and Variance," International Review of Finance, International Review of Finance Ltd., vol. 17(2), pages 289-324, June.
    10. Roméo Tédongap, 2015. "Consumption Volatility and the Cross-Section of Stock Returns," Review of Finance, European Finance Association, vol. 19(1), pages 367-405.
    11. Chen, Guojin & Hong, Zhiwu & Ren, Yu, 2016. "Durable consumption and asset returns: Cointegration analysis," Economic Modelling, Elsevier, vol. 53(C), pages 231-244.
    12. Chen, Cathy Yi-Hsuan & Chiang, Thomas C. & Härdle, Wolfgang Karl, 2018. "Downside risk and stock returns in the G7 countries: An empirical analysis of their long-run and short-run dynamics," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 21-32.
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    14. Grammig, Joachim & Schaub, Eva-Maria, 2014. "Give me strong moments and time: Combining GMM and SMM to estimate long-run risk asset pricing," CFR Working Papers 14-05, University of Cologne, Centre for Financial Research (CFR).
    15. Boons, Martijn, 2016. "State variables, macroeconomic activity, and the cross section of individual stocks," Journal of Financial Economics, Elsevier, vol. 119(3), pages 489-511.
    16. Laurinaityte, Nora & Meinerding, Christoph & Schlag, Christian & Thimme, Julian, 2020. "GMM weighting matrices incross-sectional asset pricing tests," Discussion Papers 62/2020, Deutsche Bundesbank.
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    18. Avramov, Doron & Hore, Satadru, 2017. "Cross-sectional factor dynamics and momentum returns," Journal of Financial Markets, Elsevier, vol. 32(C), pages 69-96.
    19. Guofu Zhou & Yingzi Zhu, 2015. "Macroeconomic Volatilities and Long-Run Risks of Asset Prices," Management Science, INFORMS, vol. 61(2), pages 413-430, February.
    20. Samuel M. Hartzmark, 2016. "Economic Uncertainty and Interest Rates," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 6(2), pages 179-220.
    21. Grammig, Joachim & Schaub, Eva-Maria, 2014. "Give me strong moments and time: Combining GMM and SMM to estimate long-run risk asset pricing models," CFS Working Paper Series 479, Center for Financial Studies (CFS).
    22. Marcos Álvarez-Díaz & Rangan Gupta, 2015. "Forecasting the US CPI: Does Nonlinearity Matter?," Working Papers 201512, University of Pretoria, Department of Economics.
    23. Lu, Helen & Jacobsen, Ben, 2016. "Cross-asset return predictability: Carry trades, stocks and commodities," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 62-87.

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    More about this item

    Keywords

    Long-run risk models; Out-of-sample;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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