This grant provides funding for the development of stochastic models and computational tools to analyze customer default risk and to design risk mitigation strategies in a manufacturing enterprise producing heavy equipment that requires long-term financing, such as aircraft, ships, factory equipment, construction equipment, electric power generators, rail stock, trucks and truck trailers. The project focuses on aircraft manufacturing as a representative industry through collaboration with Boeing. Aircraft sales require long-term financing. The manufacturer retains exposure to the risk of default by its customers. If the customer defaults on its lease or loan, the manufacturer will have to resell the used equipment in the secondary market. The manufacturer is thus exposed to the risk of declining prices for used equipment. The manufacturer is also exposed to the interest rate risk. The three risks, the customer default risk, equipment price risk, and interest rate risk, are correlated. The research goal is to develop a theoretically consistent stochastic modeling framework and its computational implementation to evaluate manufacturer-customer transactions requiring financing, including leases, loans, forward commitments and guarantees, with regard to these risks and their interdependence.
If successful, the results of this research will lead to improved understanding of the impact of these risks on product pricing strategies, production planning strategies, and risk mitigation strategies in a manufacturing enterprise and will lead to the development of industry-wide risk management best practices for the aircraft manufacturing industry. In addition to the impact on the aircraft manufacturing industry, this research will help other manufacturing industries of heavy equipment that require long-term financing and as such expose the manufacturer to the risk of customer default. This research has the potential to contribute to increased competitiveness of the U.S. manufacturing sector through improved risk management that will translate into more competitive product pricing for customers.
