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Learning and forecasts on option returns through the volatility risk premium

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journal contribution
posted on 2023-06-09, 13:03 authored by Bernales Alejandro, Louisa ChenLouisa Chen, Marcela Valenzuela
We use learning in an equilibrium model to explain the puzzling predictive power of the volatility risk premium (VRP) for option returns. In the model, a representative agent follows a rational Bayesian learning process in an economy under incomplete information with the objective of pricing options. We show that learning induces dynamic differences between probability measuresP and Q, which produces predictability patterns from the VRP for option returns. The forecasting features of the VRP for option returns, obtained through our model, exhibit the same behaviour as those observed in an empirical analysis with S&P 500 index options.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Journal of Economic Dynamics and Control

ISSN

0165-1889

Publisher

Elsevier

Volume

82

Page range

312 -330

Department affiliated with

  • Business and Management Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2018-04-25

First Open Access (FOA) Date

2019-07-13

First Compliant Deposit (FCD) Date

2018-04-25

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