Integrating Operational and Financial Hedging in Commodity Risk Management

Project: Research

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Managing commodity risks represents one of the key challenges for raw materialssourcing and procurement in supply chain management. A key characteristic of wellfunctioningand liquid commodity markets is coexistence of spot markets and contractmarkets for physical delivery and financial markets which provide derivatives for riskmanagement. Hence, it is important to integrate physical operations and financialhedging in the raw material commodity supply management.This project aims to study the integrated operational and financial hedging problem forraw material commodities in a dynamic setting. In particular, we will investigate theinteractive roles of long-term contract with volumetric flexibility as an operationalhedge, spot trading and financial hedging. It is known that the dynamic hedgingproblems are generally analytically challenging.We will develop a modeling framework and methodology to analyze the integratedoperational and financial hedging problem for raw material commodities in a dynamicsetting. We take a portfolio view and adopt the well-established mean-varianceframework from the financial literature. Under a time-consistent policy, we formulatethe problem into a dynamic programming model with two levels of recursion which isvery complex compared to traditional inventory models. Tackling such a challenge willallow us to have an in-depth understanding on the role of different operational (such asinventory and long-term contract) and financial (such as futures and options)instruments in managing the commodity risks and the strategy to manage them. Findingan effective optimal solution for such a problem requires new insights and newanalytical methods, which allows us to make a significant methodological contribution tosupply chain management area. We will also implement the model using real world datato provide practical insights and promote analytics as the commodity prices and financialderivatives prices can be readily accessed. The managerial implications of this study willcertainly help supply chain managers to improve their commodity risk managementstrategies.The PI has been working on dynamic inventory problems for many years and also hasbeen working on related models for a few years, which offers a fresh direction for takingup the challenges proposed here.


Project number9042565
Grant typeGRF
Effective start/end date1/10/1729/09/21