Abstract

Quadratic hedging of option payoffs generates the variance optimal martingale measure. When an option features an exercise policy and its cash flows are hedged according to this approach, it may be tempting to optimize such a policy under this measure. Because the variance optimal martingale measure may not be an equivalent probability measure, focusing on American options we show that the resulting exercise policy may be unappealing. This drawback can sometimes be remedied by imposing time consistency on exercise policies, but in general persists even in this case, which compounds the familiar issue that valuing an option using this measure may not result in an arbitrage free value. An alternative and known approach bypasses both of these pitfalls by optimizing option exercise policies under any given equivalent martingale measure and anchoring quadratic hedging to the resulting value of this policy. Additional research may assess on realistic applications the magnitude of the limitations associated with optimizing option exercise policies based on the variance optimal martingale measure.

Thought-leadership in Supply Chain Finance and Risk Management

This monograph contains six thought-leading contributions on various topics related to supply chain finance and risk management. The issue culminated out of a recent (May 14-16, 2021) mini-conference on “Supply Chain Finance and Risk Management” organized by The Boeing Center for Supply Chain Innovation (BCSCI), Olin Business School, Washington University in St. Louis.

In “Quadratic Hedging and Optimization of Option Exercise Policies”, Nicola Secomandi explores a model for optimizing option exercise policies under any given equivalent martingale measure and anchoring quadratic hedging to the resulting value of the policy. In “Operations Revenue Insurance”, Paolo Guiotto, Andrea Roncoroni and Roméo Tédongap propose a new framework for the optimal design of a financial instrument to hedge nonclaimable risk embedded by business and operating revenues. In “Crowdfunding Adoption in the Presence of Word-of-Mouth Communication”, Fasheng Xu, Xiaomeng Guo, Guang Xiao and Fuqiang Zhang investigate a firm’s optimal funding choice when launching a product in the market with word-of-mouth communication. In “Data Sharing in Innovations”, Zhi Chen and Jussi Keppo discuss how the success of data-driven products depends on a firm’s access to big data and the challenges of data collection and sharing in innovations using the autonomous vehicle industry as an example. In “Coordination Problems in Platform Markets Under Uncertainty”, Hamed Ghoddusi presents a dynamic coordination problem under uncertainty that is common in platform markets and provides novel insights on this problem between two sides of a platform under uncertainty. In “Value Games”, Matthew J. Sobel shows that insights and algorithms based on sequential games with a profit criterion and negligible bankruptcy risk can be adapted to maximize value.