Learning and forecasts about option returns through the volatility risk premium
Author
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Bernales Silva, Alejandro
Author
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Chen, Louisa
Author
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Valenzuela Bravo, Marcela
Admission date
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2018-06-25T19:20:37Z
Available date
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2018-06-25T19:20:37Z
Publication date
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2017
Cita de ítem
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Journal of Economic Dynamics & Control 82 (2017) 312–330
es_ES
Identifier
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http://dx.doi.org/10.1016/j.jedc.2017.06.007
Identifier
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https://repositorio.uchile.cl/handle/2250/149176
Abstract
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We use learning in an equilibrium model to explain the puzzling predictive power of the volatility risk premium ( V RP) for option returns. In the model, a representative agent fol- lows 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 measures P 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.
es_ES
Patrocinador
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Fondecyt project #11140628. Institute for Research in Market Imperfections and Public Policy (ICM IS130 0 02)