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Simpler Better Market Betas

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  • Ivo Welch

Abstract

This paper proposes a robust one-pass estimator that is easy to code: Justified by the market-model itself and using a prior that market-betas should not be less than –2 and more than +4, the market-model is run on daily stock rates of return that have first been winsorized at –2 and +4 times the contemporaneous market rate of return. The resulting “slope-winsorized” estimates outperform (all) other known estimators in predicting the future OLS market-beta (on R² metrics). Adding reasonable age decay, suggesting a half-life of about 3 to 5 months, to observations entering the market-model further improves it. The estimates outpredict the Vasicek estimates by about half as much as the Vasicek estimates outpredict the OLS estimates.

Suggested Citation

  • Ivo Welch, 2019. "Simpler Better Market Betas," NBER Working Papers 26105, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:26105
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    References listed on IDEAS

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    1. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    2. 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.
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    Cited by:

    1. Miguel C. Herculano, 2024. "Betting Against (Bad) Beta," Papers 2409.00416, arXiv.org.
    2. Novy-Marx, Robert & Velikov, Mihail, 2022. "Betting against betting against beta," Journal of Financial Economics, Elsevier, vol. 143(1), pages 80-106.
    3. Baoqing Gan, 2020. "Does Social Media Sentiment Trump News?," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2020, January-A.
    4. Baba-Yara, Fahiz & Boons, Martijn & Tamoni, Andrea, 2024. "Persistent and transitory components of firm characteristics: Implications for asset pricing," Journal of Financial Economics, Elsevier, vol. 154(C).
    5. Hollstein, Fabian & Prokopczuk, Marcel, 2022. "Testing Factor Models in the Cross-Section," Journal of Banking & Finance, Elsevier, vol. 145(C).
    6. Campello, Murillo & Connolly, Robert A. & Kankanhalli, Gaurav & Steiner, Eva, 2022. "Do real estate values boost corporate borrowing? Evidence from contract-level data," Journal of Financial Economics, Elsevier, vol. 144(2), pages 611-644.
    7. Han, Xing & Li, Kai & Li, Youwei, 2020. "Investor overconfidence and the security market line: New evidence from China," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    8. Iachan, Felipe S. & Silva, Dejanir & Zi, Chao, 2022. "Under-diversification and idiosyncratic risk externalities," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1227-1250.

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    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies

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