The authors describe the knowledge representation used to develop a prototype expert system for financial hedging. This representation captures the deep domain knowledge that experts use to reason about hedging decisions. It allows for reasoning qualitatively based on first principles using the fundamental quantitative valuation models that characterize each financial instrument. It also uses object-oriented concepts and inheritance to minimize the effort needed to set up the knowledge base and keep it current. It includes a calculus for derivation of qualitative knowledge of one-dimensional-order, which allows it to solve problems where optimality constraints are qualitative. It is flexible enough to reason in terms of the basic principles of risk assessment.