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Return Predictability under Equilibrium Constraints on the Equity Premium

Author

Listed:
  • Davide Pettenuzzo

    (Department of Economics, Brandeis University)

  • Allan G. Timmermann

    (Rady School of Management, University of California, San Diego)

  • Rossen I. Valkanov

    (Rady School of Management, University of California, San Diego)

Abstract

This paper proposes a new approach for incorporating theoretical constraints on return forecasting models such as non-negativity of the conditional equity premium and sign restrictions on the coefficients linking state variables to the equity premium. Our approach makes use of Bayesian methods that update the estimated parameters at each point in time in a way that optimally exploits information in these constraints. Using a variety of predictor variables from the literature on predictability of stock returns, we find that theoretical constraints have an important effect on the coefficient estimates and can significantly reduce biases and estimation errors in these. In out-of-sample forecasting experiments we find that models that exploit the theoretical restrictions produce better forecasts than unconstrained models.

Suggested Citation

  • Davide Pettenuzzo & Allan G. Timmermann & Rossen I. Valkanov, 2008. "Return Predictability under Equilibrium Constraints on the Equity Premium," Working Papers 37, Brandeis University, Department of Economics and International Businesss School.
  • Handle: RePEc:brd:wpaper:37
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    File URL: http://www.brandeis.edu/economics/RePEc/brd/doc/Brandeis_WP37.pdf
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    References listed on IDEAS

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    Cited by:

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    More about this item

    Keywords

    Return Predictability; Constraints; Out-of-Sample Forecasts;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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