JD(M)J模型下欧式期权最优复制策略的贝叶斯定价

M. Kostrzewski
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引用次数: 2

摘要

在不完全市场中,复制策略可能不存在,衍生品的定价也不是一件容易的事。本文介绍了Bertsimas、Kogan和Lo算法在确定最优复制策略中的一个应用。在默顿模型中,似然函数是无穷多个成分混合的产物。在本文中,假设这个数字等于一个固定值M+1。为了确定最优策略,我们需要估计未知参数。为此,我们采用贝叶斯估计技术。本文通过实证研究对所提出的方法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayesian Pricing of the Optimal-Replication Strategy for European Option in the JD(M)J Model †
In incomplete markets replication strategies may not exist and pricing of derivatives is not an easy task. This paper presents an application of Bertsimas, Kogan and Lo’s algorithm of determining an optimal-replication strategy. In the Merton model the likelihood function is a product of a mixture of infinite number of components. In the paper this number is assumed to be equal to a fixed value M+1. To determine the optimal strategy, we should estimate unknown parameters. To this end we resort to Bayesian estimation techniques. The presented methodology is exemplified by an empirical research.
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