We study robust notions of good-deal hedging and valuation under combined uncertainty about the drifts and volatilities of asset prices. Good-deal bounds are determined by a subset of risk-neutral pricing measures such that not only opportunities for arbitrage are excluded but also deals that are too good, by restricting instantaneous Sharpe ratios. A non-dominated multiple priors approach to model uncertainty (ambiguity) leads to worst-case good-deal bounds. Corresponding hedging strategies arise as minimizers of a suitable coherent risk measure. Good-deal bounds and hedges for measurable claims are characterized by solutions to second-order backward stochastic differential equations whose generators are non-convex in the volatility. These hedging strategies are robust with respect to uncertainty in the sense that their tracking errors satisfy a supermartingale property under all a-priori valuation measures, uniformly over all priors.

中文翻译：

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在漂移和波动性综合不确定性的情况下进行很好的套期保值和估值

在资产价格的波动和波动性的综合不确定性下，我们研究了良好的套期保值和估值的强有力的概念。好的交易范围是由风险中性定价措施的子集确定的，这样不仅可以限制套利机会，而且可以通过限制即时Sharpe比率来排除交易太好的交易。对模型不确定性（模棱两可）采用非主导的多重先验方法会导致最坏情况下的良好交易界限。相应的对冲策略是适当连贯风险度量的最小化方法。可衡量索赔的良好交易范围和对冲的特征在于二阶后向随机微分方程的解，其生成器的波动性不为凸。