Department of Statistics Unitmark
Dietrich College of Humanities and Social Sciences

Inference for volatility-type objects and implications for hedging

Publication Date

October, 2003

Publication Type

Tech Report

Author(s)

Mykland, P.A. and Zhang, L.

Abstract

The paper studies inference for volatility type objects and its implications for the hedging of options. It considers the nonparametric estimation of volatilities and instantaneous covariations between diffusion type processes. This is then linked to options trading, where we show that our estimates can be used to trade options without reference to the specific model. The new options "delta" becomes an additive modification of the (implied volatility) Black-Scholes delta. The modification, in our example, is both substantial and statistically significant. In the inference problem, explicit expressions are found for asymptotic error distributions, and it is explained why one does not in this case encounter a bias-variance tradeoff, but rather a variance-variance tradeoff. Observation times can be irregular.