Optimal stopping is the problem of determining when to stop a stochastic system in order to maximize reward. We propose a methodology for optimal stopping based on randomized linear policies, which choose to stop with a probability that is determined by a weighted sum of basis functions. We develop a practical heuristic for solving our randomized policy problem, and numerically show that our approach can substantially outperform state-of-the-art methods.

​​​​A multinational risk averse newsvendor produces goods at home (domestically) and sells both overseas and at home, over multiple periods. ​​We consider ​risks due to uncertain exchange rate as well as uncertain demand and investigate the effectiveness of ​(a) general financial hedging contracts​ and (b) operational hedging, which is to allow production both domestically and overseas. ​W​e evaluate both types of hedging and describe the situations that favor each type of hedging.

Firms can adjust operations based on financial asset price impact on product demand. We develop a model integrating financial risk hedging into pricing decisions. Hedging generally lowers optimal price and service level. The impact of asset price on demand determines the effect on service level. Our model reduces risk without significantly reducing operational profit. Including operational payoff functions reveals when hedging reduces optimal operational levels.