This paper proposes an approach to compute the implied transition matrices from observations of market data on financial derivatives, when the price of the underlying originates from a structural model and the payoffs are received over a period of time. The structural price model involves a price formation mechanism which computes the price based on a set of Markovian inputs and constrained optimization processes. The developed inference method relies on a linear description of the derivative values in terms of occupation measures of the payoff duration. We establish closed-form expressions between occupation measures and state transitions, which then enable us to characterize implied state transition probabilities consistent with the market data on the derivative values. We develop methods to solve the optimization problem with the resulting nonlinear occupation measure equation. Numerical illustrations of the approach are presented for financial derivatives on network capacities. By applying the method to an electric network, we investigate the relation between financial transmission correct contract values and a range of implied probabilities of congestion in the network.

本文提出了一种方法，通过观察金融衍生品的市场数据来计算隐含转移矩阵，当标的物的价格源自结构模型并且收益是在一段时间内收到时。结构价格模型涉及一种价格形成机制，该机制根据一组马尔可夫输入和受约束的优化过程计算价格。所开发的推理方法依赖于根据收益持续时间的占用度量对衍生值的线性描述。我们在占领措施和状态转换之间建立封闭形式的表达式，然后使我们能够表征与衍生值的市场数据一致的隐含状态转换概率。我们开发了使用由此产生的非线性占用度量方程来解决优化问题的方法。针对网络容量的金融衍生品，给出了该方法的数值说明。通过将该方法应用于电网，我们研究了金融传输正确的合同价值与网络拥塞的一系列隐含概率之间的关系。