结构化产品的时不变投资组合策略,保证最小的股权敞口

IF 1.3 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Luca Di Persio, D. Mancinelli, Immacolata Oliva, K. Wallbaum
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引用次数: 0

摘要

我们引入了一种新的外来期权,用于结构性产品,以解决标准时不变投资组合保护的一个关键缺点:众所周知的现金锁定风险。我们的方法建议通过在分配机制中包括一个阈值来丰富框架,以便在任何时间点都确保有保证的最低股本敞口(GMEE)。为了能够提供这样一个仍然具有硬资本保护的解决方案,我们应用了一个基于期权的结构,并以动态分配逻辑为基础。我们在假设heston - vasicek型金融市场模型的情况下,对这些新的奇异期权的价格进行了深入分析,并将我们的结果与结构性产品中使用的其他期权进行了比较。我们的方法为投资者提供了一个有趣的选择,旨在通过定常投资组合保护策略减少保护,同时也害怕经历由市场动荡引发的现金锁定事件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Time-invariant portfolio strategies in structured products with guaranteed minimum equity exposure

Time-invariant portfolio strategies in structured products with guaranteed minimum equity exposure

We introduce a new exotic option to be used within structured products to address a key disadvantage of standard time-invariant portfolio protection: the well-known cash-lock risk. Our approach suggests enriching the framework by including a threshold in the allocation mechanism so that a guaranteed minimum equity exposure (GMEE) is ensured at any point in time. To be able to offer such a solution still with hard capital protection, we apply an option-based structure with a dynamic allocation logic as underlying. We provide an in-depth analysis of the prices of such new exotic options, assuming a Heston–Vasicek-type financial market model, and compare our results with other options used within structured products. Our approach represents an interesting alternative for investors aiming at downsizing protection via time-invariant portfolio protection strategies, meanwhile being also afraid to experience a cash-lock event triggered by market turmoils.

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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
67
审稿时长
>12 weeks
期刊介绍: ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process. The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.
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