Travel time derivatives are financial instruments that derive their value from road travel times, serving as an underlying asset that cannot be directly traded. Within the transportation domain, these derivatives are proposed as a more comprehensive approach to value pricing. They enable road pricing based not only on the level of travel time but also its volatility. In the financial market, travel time derivatives are introduced as innovative hedging instruments to mitigate market risk, particularly in light of recent stress experienced by the crypto market and traditional banking sector. The paper focuses on three main aspects: (1) the motivation behind the introduction of these derivatives, driven by the demand for hedging; (2) exploring the potential market for these instruments; and (3) delving into the product design and pricing schemes associated with them. The pricing schemes are devised by utilizing real-time travel time data captured by sensors. These data are modeled using Ornstein-Uhlenbeck processes and, more broadly, continuous time autoregressive moving average (CARMA) models. The calibration of these models is achieved through a hidden factor model, which describes the dynamics of travel time processes. The risk-neutral pricing principle is then employed to determine the prices of the derivatives, employing well-designed procedures to identify the market value of risk.

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