供应链动态套期保值与契约设计联合决策研究

Due to the economy globalization and business environment volatility, it is not uncommon that the price of various commodities can greatly vary within a short time period. The growing commodity price volatility has been one of the major challenges for the manufacturing firms. And the emerging trend of the financialization of commodity markets makes the situation even worse. Under today’s volatile business environment, the traditional operations tools may not work well any more. Therefore, this project aims at investigating how the manufacturing supply chain members could best control their risk exposure using the combination of financial instruments and operations tools. Specifically, theory of stochastic processes will be employed to model the evolution of the random demand and price of the raw materials and the corresponding financial derivatives. The project will also provide a framework to construct the price risk sharing mechanism with financial hedging. The effectiveness and robustness of the strategy developed by the project can be tested using Monte Carlo simulation. It is worth noting that the values of parameters embedded in the commodity price processes will be estimated based on the data collected from China commodity markets using Kalman Filtering. It is expected that the output of this project will provide new effective ways for the manufacturing firms to manage its risk exposure to the uncertain procurement cost and provide theory support for the incorporation of the financial instruments to improve the manufacturing supply chain risk management system.

在金融全球化和商品金融化的背景下，大宗商品价格的巨幅波动给制造业带来了巨大的市场风险，通过传统运营手段控制成本波动的方法已不能满足现代制造企业的需要，金融工具和运营手段相结合的新型风险控制方法势在必行。鉴于此，本项目针对制造业供应链中同时存在的“原材料价格波动”和“需求随机变化”所带来的价格和需求风险并存的问题，运用随机过程相关理论，深入分析市场需求变化、原材料及其金融衍生品的价格波动规律，构建基于随机优化的套期保值模型和基于博弈论的供应链风险分担模型，研究供应链如何协调运用金融衍生品工具（如商品期货）和运营手段（契约设计）来管理价格波动和需求不确定的风险。本项目进一步通过基于卡尔曼滤波的方法根据实际数据给出金融衍生品价格随机过程的参数估计，采用蒙特卡洛模拟检验本项目提出的策略的有效性和稳健性。本项目成果将丰富制造业供应链控制风险的手段，为升级我国制造业供应链风险管理体系提供理论支撑。

在金融全球化和商品金融化的背景下，大宗商品价格的巨幅波动给制造业带来了巨大的市场风险。本项目针对制造业供应链中同时存在的“原材料价格波动”和“需求随机变化”所带来的价格和需求风险并存的问题，探讨将金融工具和运营手段相结合的新型风险控制方法，为传统运营制造业控制成本波动提供了新思路。为了更好的预测大宗商品原材料的价格波动，本项目创新的将GARCH模型与深度学习模型（LSTM和ANN）相结合，显著的提高了预测精度。基于对大宗商品价格不确定性的理解，进而设计了有效的供应链采购契约以及套期保值机制。最后，在前面研究的基础上探讨了资金约束和需求依赖天气供应链的契约设计问题，为后续深入研究奠定了基础。本课题研究基本达到了预期的研究目标,目前已在国际权威 SCI期刊发表学术论文5篇，另外，课题组有2篇工作论文进入匿名评审。项目成果丰富了制造业供应链控制风险的手段，有助于我国制造业供应链风险管理体系的升级。