Recovering Probabilistic Information From Options Prices and the Underlying

Bruce Mizrach ()

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

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Persistent link: http://EconPapers.repec.org/RePEc:rut:rutres:200702

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