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Economic Implications of Nonlinear Pricing Kernels

Author

Listed:
  • Caio Almeida

    (FGV/EPGE–Escola Brasileira de Economia e Finanças, Rio de Janeiro, Brazil)

  • René Garcia

    (EDHEC Business School, Nice 06202, France; Département de Sciences Économiques, CIREQ, and CIRANO, Université de Montréal, Montréal, Québec H3C 3J7, Canada)

Abstract

Based on a family of discrepancy functions, we derive nonparametric stochastic discount factor bounds that naturally generalize variance, entropy, and higher-moment bounds. These bounds are especially useful to identify how parameters affect pricing kernel dispersion in asset pricing models. In particular, they allow us to distinguish between models where dispersion comes mainly from skewness from models where kurtosis is the primary source of dispersion. We analyze the admissibility of disaster, disappointment aversion, and long-run risk models with respect to these bounds.

Suggested Citation

  • Caio Almeida & René Garcia, 2017. "Economic Implications of Nonlinear Pricing Kernels," Management Science, INFORMS, vol. 63(10), pages 3361-3380, October.
    • Handle: RePEc:inm:ormnsc:v:63:y:2017:i:10:p:3361-3380
    DOI: 10.1287/mnsc.2016.2498
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    8. Almeida, Caio & Ardison, Kym & Garcia, René, 2020. "Nonparametric assessment of hedge fund performance," Journal of Econometrics, Elsevier, vol. 214(2), pages 349-378.
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