Option market trading activity and the estimation of the pricing kernel: A Bayesian approach

Giovanni Barone-Adesi, Nicola Fusari, Antonietta Mira, C. Sala

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7 Cites (Scopus)

Resum

We propose a nonparametric Bayesian approach for the estimation of the pricing kernel. Historical stock returns and option market data are combined through the Dirichlet Process (DP) to construct an option-adjusted physical measure. The precision parameter of the DP process is calibrated to the amount of trading activity in deep-out-of-the-money options. We use the option-adjusted physical measure to construct an option-adjusted pricing kernel. An empirical investigation on the S&P 500 Index from 2002 to 2015 shows that the option-adjusted pricing kernel is consistently monotonically decreasing, regardless of the level of volatility, thus providing an explanation to the well known U-shaped pricing kernel puzzle.

Idioma originalAnglès
Pàgines (de-a)430-449
Nombre de pàgines20
RevistaJournal of Econometrics
Volum216
Número2
DOIs
Estat de la publicacióPublicada - de juny 2020
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