评估商品指数衍生品合约的微观与宏观模型
Evaluating Microscopic and Macroscopic Models for Derivative Contracts on Commodity Indices
AI总结：
本文比较了商品指数衍生品定价的微观与宏观建模方法，通过S&P GSCI原油指数衍生品校准并对比路径依赖期权的定价与敏感性，评估宏观模型在实际定价和对冲中的适用性。
摘要：
在本文中，我们分析了商品指数衍生品合约定价的两种建模方法。第一种是微观方法，即对指数的各个成分分别建模，指数价格由其组合推导得出。第二种是宏观方法，即直接对指数进行建模。虽然微观方法提供了更大的灵活性，但其校准结果更具挑战性，因此实务人员更倾向于采用宏观方法。然而，在宏观模型中，缺乏明确的期货曲线动态，这引发了人们对其能否准确捕捉指数行为及其敏感性的质疑。为了研究这一问题，我们使用S&P GSCI原油超额收益指数的衍生品对两种模型进行校准，并比较它们在路径依赖型期权（如自动赎回合约）上的定价和敏感性。本研究为宏观模型在实际场景中用于定价和对冲目的的适用性提供了见解。
英文摘要：
In this article, we analyze two modeling approaches for the pricing of derivative contracts on a commodity index. The first one is a microscopic approach, where the components of the index are modeled individually, and the index price is derived from their combination. The second one is a macroscopic approach, where the index is modeled directly. While the microscopic approach offers greater flexibility, its calibration results to be more challenging, thus leading practitioners to favor the macroscopic approach. However, in the macroscopic model, the lack of explicit futures curve dynamics raises questions about its ability to accurately capture the behavior of the index and its sensitivities. In order to investigate this, we calibrate both models using derivatives of the S\&P GSCI Crude Oil excess-return index and compare their pricing and sensitivities on path-dependent options, such as autocallable contracts. This research provides insights into the suitability of macroscopic models for pricing and hedging purposes in real scenarios.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
