在包含市场利率、现货价格波动率和期权期限三个重要期权定价影响因素的逆向主导型供应链期权协作模型基础上,通过对模型决策优化机制的分析和灵敏度分析的方法,借助Matlab软件工具,研究市场利率和现货价格波动率对期权定价和供应链绩效的影响.通过数值仿真分析,进一步计算市场利率和现货价格波动率对期权定价和供应链绩效影响的规律和临界值.获得对企业制定供应链期权契约具有指导意义的研究结论.%Companies are increasingly constructing customer-centric supply chains in order to cope with the unrelenting pressure of cost reduction. The customer-centric supply chain strategy emphasizes improvement of key factors such as market rates, volatility and option pricing terms via the coordination of supply chain partners. A review of literature on supply chain management shows that other factors,such as product production cost, product selling price and the relationship between supply chain partners, have been considered.Globalization requires that companies be more flexible and adaptive to the changes of market environment because of increased factor mobility and market access. Therefore, a company needs to consider many relevant factors, such as the cost of funds, the opportunity cost of scheduled capacity and the uncertainty risk of product price fluctuations, when constructing a customer-centric supply chain. This study proposes an option pricing optimization model to help a company manage its customer-centric supply chains. This option pricing optimization model considers the importance of market interest rates, product price volatility and option deadline. As a result,instead of managing supply chains from supplier's perspectives this model offers the possibility of managing supply chains from customer's perspectives. Our work places emphasis on the synergy of a B-S option pricing model and supply chain operation mechanisms. Market interest rates, price volatility and option deadlines are three factors programmed into our decision-making model for the management of customer-centric supply chains. After including these three factors, business benefits can be optimized for all supply chain partners and are aligned with the B-S option pricing model. Our proposed model can better meet the actual needs of supply chain operations. Moreover, the combination of a supplier-centric supply chain and B-S option pricing models can be recalculated for each use to fit a new circumstance. This operational flexibility enables our proposed model to be applicable to a variety of situations. We wrote applications using Matlab software based on the proposed option pricing optimization model. The primary goals of these applications are to benefit both suppliers and retailers. Suppliers can use our program to calculate their optimal production volume.Retailers can calculate the combination of option pricing and optimal ordering volume. We entered data into the applications and found that the option price and exercise pricing computed using our option pricing optimization model are convergent. The option price can not only comply with the regulations of exchange marketplace, but also optimize supply chain profits for business partners. In addition, our proposed model can increase the transparency of decision-making processes for suppliers and buyers to make informed decisions. After controlling the option exercise price to be the same, our model shows two potential results. The first result is that the option price is greater than the option price in the exchange marketplace. The option price in the exchange marketplace will have a greater appeal to buyers. On the contrary, the option price is less than the option price in the exchange marketplace. The option price in the exchange price will lose its attractiveness to potential buyers and reduce profits for suppliers. Our model provides these two alternative interpretations for the option pricing method. Supply chain optimization can thusly be achieved after incorporating interest rates, price volatility and option deadline into the proposed model. This model can better represent the actual needs of supply chain operations. The quantitative analysis results also indicate that suppliers and retailers can maximize their profits if they can coordinate with each other in a decentralized fashion. Suppliers tend to increase option price and decrease exercise price. In contrast, retailers tend to decrease option price and increase exercise price. The entire supply chain can maximize their profits if the reverse trends converge. This study proposes an option pricing optimization model to help maximize profit for the entire supply chain. This customer-centric model differs from supplier-centric models by taking into consideration interest rates, price volatility and option deadline. This model is particularly applicable to understanding the market where option contracts and option pricing in the exchange marketplace are common practices.
展开▼
