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Break Risk
[Maximum likelihood estimation of the equity premium]

Author

Listed:
  • Simon C Smith
  • Allan Timmermann
  • Stijn Van Nieuwerburgh

Abstract

We develop a new approach to modeling and predicting stock returns in the presence of breaks that simultaneously affect a large cross-section of stocks. Exploiting information in the cross-section enables us to detect breaks in return prediction models with little delay and to generate out-of-sample return forecasts that are significantly more accurate than those from existing approaches. To identify the economic sources of breaks, we explore the asset pricing restrictions implied by a present value model which links breaks in return predictability to breaks in the cash flow growth and discount rate processes.

Suggested Citation

  • Simon C Smith & Allan Timmermann & Stijn Van Nieuwerburgh, 2021. "Break Risk [Maximum likelihood estimation of the equity premium]," The Review of Financial Studies, Society for Financial Studies, vol. 34(4), pages 2045-2100.
  • Handle: RePEc:oup:rfinst:v:34:y:2021:i:4:p:2045-2100.
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    File URL: http://hdl.handle.net/10.1093/rfs/hhaa084
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    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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