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Generalized recovery

Author

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  • Jensen, Christian Skov
  • Lando, David
  • Pedersen, Lasse Heje

Abstract

We characterize when physical probabilities, marginal utilities, and the discount rate can be recovered from observed state prices for several future time periods. We make no assumptions of the probability distribution, thus generalizing the time-homogeneous stationary model of Ross (2015). Recovery is feasible when the number of maturities with observable prices is higher than the number of states of the economy (or the number of parameters characterizing the pricing kernel). When recovery is feasible, our model allows a closed-form linearized solution. We implement our model empirically, testing the predictive power of the recovered expected return and other recovered statistics.

Suggested Citation

  • Jensen, Christian Skov & Lando, David & Pedersen, Lasse Heje, 2019. "Generalized recovery," Journal of Financial Economics, Elsevier, vol. 133(1), pages 154-174.
    • Handle: RePEc:eee:jfinec:v:133:y:2019:i:1:p:154-174
    DOI: 10.1016/j.jfineco.2018.12.003
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    Cited by:

    1. Dillschneider, Yannick & Maurer, Raimond, 2019. "Functional Ross recovery: Theoretical results and empirical tests," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
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    3. Martin, Ian W. R. & Ross, Stephen A., 2019. "Notes on the yield curve," Journal of Financial Economics, Elsevier, vol. 134(3), pages 689-702.
    4. Kevin C. Smith & Eric C. So, 2022. "Measuring Risk Information," Journal of Accounting Research, Wiley Blackwell, vol. 60(2), pages 375-426, May.
    5. Sirio Aramonte & Mohammad R. Jahan-Parvar & Samuel Rosen & John W. Schindler, 2022. "Firm-Specific Risk-Neutral Distributions with Options and CDS," Management Science, INFORMS, vol. 68(9), pages 7018-7033, September.
    6. Akira Yamazaki, 2022. "Recovering subjective probability distributions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1234-1263, July.
    7. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    8. Sanford, Anthony, 2024. "Information content of option prices: Comparing analyst forecasts to option-based forecasts," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    9. Jackwerth, Jens Carsten & Menner, Marco, 2020. "Does the Ross recovery theorem work empirically?," Journal of Financial Economics, Elsevier, vol. 137(3), pages 723-739.

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    More about this item

    Keywords

    Recovery; Asset pricing; Pricing kernel; Predicting returns;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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