If a financial asset’s price movement impacts a firm’s product demand, the firm can respond to the impact by adjusting its operational decisions. For example, in the auto-motive industry, automakers decrease the selling prices of fuel-inefficient cars when the oil price rises. Meanwhile, the firm can implement a risk-hedging strategy using the financial asset jointly with its operational decisions. Motivated by this, we develop and solve a gen-eral risk-management model integrating risk hedging into a price-setting newsvendor. The optimal hedging strategy is calculated analytically, which leads to an explicit objective function for optimizing price and “virtual production quantity” (VPQ). (The latter deter-mines the service level—that is, the demand-fulfillment probability.) We find that hedging generally reduces the optimal price when the firm sets the target mean return as its production-only maximum expected profit. With the same condition on the target mean return, hedging also reduces the optimal VPQ when the asset price trend positively impacts product demand; meanwhile, it may increase the VPQ by a small margin when the impact is negative. We construct the return-risk efficient frontier that characterizes the optimal return-risk trade-off. Our numerical study using data from a prominent automo-tive manufacturer shows that the markdowns in price and reduction in VPQ are small under our model and that the hedging strategy substantially reduces risk without materi-ally reducing operational profit.
Bibliographical noteFinancial support from the Hong Kong Research Grants Council [General Research Fund 17200521] is gratefully acknowledged.
- risk hedging
- mean-variance framework