The classical discrete-time model of proportional transaction costs relies on the assumption that a feasible portfolio process has solvent increments at each step. We extend this setting in two directions, allowing convex transaction costs and assuming that increments of the portfolio process belong to the sum of a solvency set and a family of multivariate acceptable positions, e.g. with respect to a dynamic risk measure. We describe the sets of superhedging prices, formulate several no (risk) arbitrage conditions and explore connections between them. In the special case when multivariate positions are converted into a single fixed asset, our framework turns into the no-good-deals setting. However, in general, the possibilities of assessing the risk with respect to any asset or a basket of assets lead to a decrease of superhedging prices and the no-arbitrage conditions become stronger. The mathematical techniques rely on results for unbounded and possibly non-closed random sets in Euclidean space.

比例交易成本的经典离散时间模型基于这样一个假设，即可行的投资组合过程在每一步都有溶剂增量。我们在两个方向上扩展此设置，允许凸出的交易成本，并假设投资组合过程的增量属于偿付能力集和一系列多元可接受头寸的总和，例如，就动态风险衡量而言。我们描述了套期保值的价格，制定了几种无（风险）套利条件，并探讨了它们之间的联系。在将多元头寸转换为单一固定资产的特殊情况下，我们的框架将变为无效交易设置。但是，总的来说，评估任何资产或一篮子资产的风险的可能性导致对冲价格下降，并且无套利条件变得更加严格。数学技术依赖于欧几里得空间中无界和可能非封闭随机集的结果。