Minimal Variance Hedging In A Discrete Time Market Driven By Markov Process

Abstract

Techniques in stochastic analysis are presented in a continuous time framework.We then review methods in quadratic hedging approaches with focus on minimal variance hedging in a discrete time framework. We also consider specific exercises. We then relate the results obtained in quadratic hedging methods to the case of a discrete time market driven by a Markov process.