HEDGING BY SEQUENTIAL REGRESSIONS REVISITED

Almost 20 years ago Foellmer and Schweizer (1989) suggested a simple and influential scheme for the computation of hedging strategies in an incomplete market. Their approach of local risk minimization results in a sequence of one-period least squares regressions running recursively backwards in time. In the meantime there have been significant developments in the global risk minimization theory for semimartingale price processes. In this paper we revisit hedging by sequential regression in the context of global risk minimization, in the light of recent results obtained by Cerny and Kallsen (2007). A number of illustrative numerical examples is given.

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