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.
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