Hedging under generalized good-deal bounds and model uncertainty

We study a notion of good‐deal hedging, that corresponds to good‐deal valuation and is described by a uniform supermartingale property for the tracking errors of hedging strategies. For generalized good‐deal constraints, defined in terms of correspondences for the Girsanov kernels of pricing measures, constructive results on good‐deal hedges and valuations are derived from backward stochastic differential equations, including new examples with explicit formulas. Under model uncertainty about the market prices of risk of hedging assets, a robust approach leads to a reduction or even elimination of a speculative component in good‐deal hedging, which is shown to be equivalent to a global risk minimization in the sense of Föllmer and Sondermann (1986) if uncertainty is sufficiently large.