用整数策略超级对冲任意数量欧式期权的简短说明

IF 1.6 3区 数学 Q2 MATHEMATICS, APPLIED
Dorsaf Cherif, Meriam El Mansour, Emmanuel Lepinette
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引用次数: 0

摘要

金融学中通常的资产定价理论假定金融策略(即投资风险资产的数量)是实值的,因此它们一般不是整数值的,例如参见布莱克和斯科尔斯模型。这显然与现实世界中可能发生的情况相反。令人惊讶的是,除了有限数量的状态之外,文献中在这方面的贡献似乎并不多。在本文中,对于任意的 \(\Omega \),我们证明了在离散时间中,当我们把自己限制在整数值策略时,是有可能评估最小超级对冲价格的。为此,我们只考虑基础资产的连续片断仿射函数的终端索赔。我们提出了一种动态编程原理,该原理可以直接在历史数据上实现,而且还能提供最优整数值策略。一般报酬的问题仍未解决,但也可以用同样的方法解决。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Short Note on Super-Hedging an Arbitrary Number of European Options with Integer-Valued Strategies

A Short Note on Super-Hedging an Arbitrary Number of European Options with Integer-Valued Strategies

The usual theory of asset pricing in finance assumes that the financial strategies, i.e. the quantity of risky assets to invest, are real-valued so that they are not integer-valued in general, see the Black and Scholes model for instance. This is clearly contrary to what it is possible to do in the real world. Surprisingly, it seems that there are not many contributions in that direction in the literature, except for a finite number of states. In this paper, for arbitrary \(\Omega \), we show that, in discrete-time, it is possible to evaluate the minimal super-hedging price when we restrict ourselves to integer-valued strategies. To do so, we only consider terminal claims that are continuous piecewise affine functions of the underlying asset. We formulate a dynamic programming principle that can be directly implemented on historical data and which also provides the optimal integer-valued strategy. The problem with general payoffs remains open but should be solved with the same approach.

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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
149
审稿时长
9.9 months
期刊介绍: The Journal of Optimization Theory and Applications is devoted to the publication of carefully selected regular papers, invited papers, survey papers, technical notes, book notices, and forums that cover mathematical optimization techniques and their applications to science and engineering. Typical theoretical areas include linear, nonlinear, mathematical, and dynamic programming. Among the areas of application covered are mathematical economics, mathematical physics and biology, and aerospace, chemical, civil, electrical, and mechanical engineering.
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