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Empirical Asset Pricing with Many Test Assets

Author

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  • Rasmus Lönn
  • Peter C Schotman

Abstract

We formulate the problem of estimating risk prices in a stochastic discount factor (SDF) model as an instrumental variables regression. The IV estimator allows efficient estimation for models with non-traded factors and many test assets. Optimal instruments are constructed using a regularized sparse first stage regression. In a simulation study, the IV estimator is close to the infeasible GMM estimator in a setting with many assets. In an empirical application, the tracking portfolio for consumption growth appears strongly correlated with consumption news. It implies that consumption is a priced factor for the cross-section of excess equity returns. A similar regularized regression, projecting the SDF on test assets, leads to an estimate of the Hansen–Jagannathan distance, and identifies portfolios that maximally violate the pricing implications of the model.

Suggested Citation

  • Rasmus Lönn & Peter C Schotman, 2024. "Empirical Asset Pricing with Many Test Assets," Journal of Financial Econometrics, Oxford University Press, vol. 22(5), pages 1236-1263.
    • Handle: RePEc:oup:jfinec:v:22:y:2024:i:5:p:1236-1263.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbae002
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    More about this item

    Keywords

    asset pricing tests; Hansen–Jagannathan distance; instrumental variables; L2-boosting;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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