Recovering Probabilistic Information From Options Prices and the Underlying

Departmental Working Papers from Rutgers University, Department of Economics

Abstract: This paper examines a variety of methods for extracting implied probability distributions from option prices and the underlying. The paper first explores non-parametric procedures for reconstructing densities directly from options market data. I then consider local volatility functions, both through implied volatility trees and volatility interpolation. I then turn to alternative specifications of the stochastic process for the underlying. I estimate a mixture of log normals model, apply it to exchange rate data, and illustrate how to conduct forecast comparisons. I finally turn to the estimation of jump risk by extracting bipower variation.

Keywords: options; implied probability densities; volatility smile; jump risk; bipower variation (search for similar items in EconPapers)
JEL-codes: G12 G14 F31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: Written 2007-01-19
View list of references

Forthcoming in Cheng-few Lee and Alice C. Lee (eds.), Handbook of Quantitative Finance

Downloads: (external link)
ftp://snde.rutgers.edu/Rutgers/wp/2007-02.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Access Statistics for this paper

More papers in Departmental Working Papers from Rutgers University, Department of Economics
Contact information at EDIRC.
Series data maintained by ().