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Asset Pricing Models with Conditional Betas and Alphas: The Effects of Data Snooping and Spurious Regression

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  • Wayne E. Ferson
  • Sergei Sarkissian
  • Timothy Simin

Abstract

This paper studies the estimation of asset pricing model regressions with conditional alphas and betas, focusing on the joint effects of data snooping and spurious regression. We find that the regressions are reasonably well specified for conditional betas, even in settings where simple predictive regressions are severely biased. However, there are biases in estimates of the conditional alphas. When time-varying alphas are suppressed and only time-varying betas are considered, the betas become baised. Previous studies overstate the significance of time-varying alphas.

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  • Wayne E. Ferson & Sergei Sarkissian & Timothy Simin, 2006. "Asset Pricing Models with Conditional Betas and Alphas: The Effects of Data Snooping and Spurious Regression," NBER Working Papers 12658, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:12658
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    Cited by:

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    2. Leite, Paulo & Cortez, Maria Céu, 2014. "Style and performance of international socially responsible funds in Europe," Research in International Business and Finance, Elsevier, vol. 30(C), pages 248-267.
    3. Kang, Hankil & Kang, Jangkoo & Lee, Changjun, 2013. "Do the production-based factors capture the time-varying patterns in stock returns?," Emerging Markets Review, Elsevier, vol. 15(C), pages 122-135.
    4. Andrew J. Patton & Tarun Ramadorai, 2013. "On the High-Frequency Dynamics of Hedge Fund Risk Exposures," Journal of Finance, American Finance Association, vol. 68(2), pages 597-635, April.
    5. Caporin, Massimiliano & Lisi, Francesco, 2013. "A Conditional Single Index model with Local Covariates for detecting and evaluating active portfolio management," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 236-249.
    6. Oueslati, Abdelmonem & Hammami, Yacine & Jilani, Faouzi, 2014. "The timing ability and global performance of Tunisian mutual fund managers: A multivariate GARCH approach," Research in International Business and Finance, Elsevier, vol. 31(C), pages 57-73.
    7. Robert Novy-Marx, 2012. "Pseudo-Predictability in Conditional Asset Pricing Tests: Explaining Anomaly Performance with Politics, the Weather, Global Warming, Sunspots, and the Stars," NBER Working Papers 18063, National Bureau of Economic Research, Inc.
    8. Chen, Yong & Ferson, Wayne & Peters, Helen, 2010. "Measuring the timing ability and performance of bond mutual funds," Journal of Financial Economics, Elsevier, vol. 98(1), pages 72-89, October.
    9. Narayan, Seema & Smyth, Russell, 2015. "The financial econometrics of price discovery and predictability," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 380-393.
    10. Yong Chen & Wayne Ferson & Helen Peters, 2009. "Measuring the Timing Ability and Performance of Bond Mutual Funds," NBER Working Papers 15318, National Bureau of Economic Research, Inc.
    11. Dimitri Kroujiline & Maxim Gusev & Dmitry Ushanov & Sergey V. Sharov & Boris Govorkov, 2015. "Forecasting stock market returns over multiple time horizons," Papers 1508.04332, arXiv.org, revised Mar 2016.
    12. Jiang, Xiaoquan & Lee, Bong-Soo, 2014. "The intertemporal risk-return relation: A bivariate model approach," Journal of Financial Markets, Elsevier, vol. 18(C), pages 158-181.
    13. Lioui, Abraham & Tarelli, Andrea, 2020. "Factor Investing for the Long Run," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    14. Patton, Andrew, 2010. "On the Dynamics of Hedge Fund Risk Exposures," CEPR Discussion Papers 7780, C.E.P.R. Discussion Papers.
    15. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2013. "Conditional alphas and realized betas," Textos para discussão 341, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    16. Dimitri Kroujiline & Maxim Gusev & Dmitry Ushanov & Sergey V. Sharov & Boris Govorkov, 2016. "Forecasting stock market returns over multiple time horizons," Quantitative Finance, Taylor & Francis Journals, vol. 16(11), pages 1695-1712, November.
    17. Grauer, Robert R. & Janmaat, Johannus A., 2009. "On the power of cross-sectional and multivariate tests of the CAPM," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 775-787, May.
    18. Francesco Lisi, 2011. "Dicing with the market: randomized procedures for evaluation of mutual funds," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 163-172.
    19. Kroujiline, Dimitri & Gusev, Maxim & Ushanov, Dmitry & Sharov, Sergey V. & Govorkov, Boris, 2015. "Forecasting stock market returns over multiple time horizons," MPRA Paper 66175, University Library of Munich, Germany.
    20. Badrinath, S.G. & Gubellini, S., 2011. "On the characteristics and performance of long-short, market-neutral and bear mutual funds," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1762-1776, July.
    21. Stefano Gubellini, 2014. "Conditioning information and cross-sectional anomalies," Review of Quantitative Finance and Accounting, Springer, vol. 43(3), pages 529-569, October.
    22. Amihud, Yakov & Noh, Joonki, 2021. "The pricing of the illiquidity factor’s conditional risk with time-varying premium," Journal of Financial Markets, Elsevier, vol. 56(C).
    23. Roberto Violi, 2011. "Optimal active portolio management and relative performance drivers: theory and evidence," BIS Papers chapters, in: Bank for International Settlements (ed.), Portfolio and risk management for central banks and sovereign wealth funds, volume 58, pages 187-209, Bank for International Settlements.

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