Travel time derivatives are introduced as financial derivatives based on road travel times - a non-tradable underlying asset. In the transportation area, it is proposed as a more fundamental approach to value pricing because it conduct road pricing based on not only level but also volatility of travel time; in the financial market, it is propose as an innovative hedging instrument against market risk, especially after the recent stress of crypto market and traditional banking sector. The paper addresses (a) the motivation for introducing such derivatives (that is, the demand for hedging), (b) the potential market, and (c) the product design and pricing schemes. Pricing schemes are designed based on the travel time data captured by real time sensors, which are modeled as Ornstein - Uhlenbeck processes and more generally, continuous time auto regression moving average (CARMA) models. The calibration of such model is conducted via a hidden factor model, which described the dynamics of travel time processes. The risk neutral pricing principle is used to generate the derivative price, with reasonably designed procedures to identify the market value of risk.

翻译：行程时间衍生品被引入作为基于道路行程时间（一种不可交易标的资产）的金融衍生品。在交通领域，该衍生品被提出作为一种更基础的价值定价方法，因为它不仅基于行程时间的水平，还基于其波动性进行道路定价；在金融市场中，它被提议作为一种创新的对冲工具，用于防范市场风险，特别是在近期加密货币市场和传统银行业面临压力之后。本文探讨了：（a）引入此类衍生品的动机（即对冲需求），（b）潜在市场，以及（c）产品设计与定价方案。定价方案基于实时传感器采集的行程时间数据设计，这些数据被建模为奥恩斯坦-乌伦贝克过程，以及更一般的连续时间自回归移动平均（CARMA）模型。该模型的校准通过一个描述行程时间动态过程的隐藏因子模型进行。风险中性定价原理被用于生成衍生品价格，并辅以合理设计的程序来识别风险的市场价值。