Hedging under generalized good-deal bounds and model uncertainty

Dirk Becherer () and Klebert Kentia ()
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Dirk Becherer: Humboldt-Universität
Klebert Kentia: Goethe-Universität

Mathematical Methods of Operations Research, 2017, vol. 86, issue 1, No 7, 214 pages

Abstract: Abstract 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.

Keywords: Good-deal bounds; Good-deal hedging; Model uncertainty; Incomplete markets; Multiple priors; Backward stochastic differential equations (search for similar items in EconPapers)
JEL-codes: C61 D80 G11 G13 G17 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00186-017-0588-y

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