Abstract

Option prices provide a great deal of information regarding the market’s expectations of future asset price dynamics. But, the implied dynamics are under the risk-neutral measure rather than the physical measure under which the price of the underlying asset itself evolves. This article demonstrates new techniques for joint analysis of the physical and risk-neutral models using data from both the underlying asset and options. While much of the prior work in this area has focused on affine and affine-jump models because of their analytical tractability, the techniques used in this article are straightforward to apply to a broad class of models of potential interest. The techniques are based on evaluating various integrals of interest using Monte Carlo sums over simulated volatility paths. In an application using S&P 500 index data, we find that log volatility models perform dramatically better than affine models, but that some evidence of misspecification remains.

Disciplines

Finance

Included in

Finance Commons

Share

COinS
 

URL: http://digitalcommons.calpoly.edu/fin_fac/12