Working Papers 2003 – Abstracts
Implicit Bayesian Inference Using Option Prices
Gael M Martin, Catherine S Forbes and Vance L Martin
A Bayesian approach to option pricing is presented, in which posterior
inference about the underlying returns process is conducted implicitly
via observed option prices. A range of models allowing for conditional
leptokurtosis, skewness and time-varying volatility in returns are considered,
with posterior parameter distributions and model probabilities backed
out from the option prices. Models are ranked according to several criteria,
including out-of-sample fit, predictive and hedging performance. The methodology
accommodates heteroscedasticity and autocorrelation in the option pricing
errors, as well as regime shifts across contract groups. The method is
applied to intraday option price data on the S&P500 stock index for 1995.
Whilst the results provide support for models which accommodate leptokurtosis,
no one model dominates according to all criteria considered.
Keywords: Bayesian Option Pricing; Leptokurtosis; Skewness; GARCH
Option Pricing; Option Price Prediction; Hedging Errors.
Next Abstract
