Optimal Design of Multi-Asset Options

The combination of stochastic derivative pricing models and downside risk measures often leads to the paradox (risk, return) = (−infinity, +infinity) in a portfolio choice problem. The construction of a portfolio of derivatives with high expected returns and very negative downside risk (henceforth “golden strategy”) has only been studied if all the involved derivatives have the same underlying asset. This paper also considers multi-asset derivatives, gives practical methods to build multi-asset golden strategies for both the expected shortfall and the expectile risk measure, and shows that the use of multi-asset options makes the performance of the obtained golden strategy more efficient. Practical rules are given under the Black–Scholes–Merton multi-dimensional pricing model.

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Publication Details

Journal
Risks
Published
2025-01-16
DOI
https://doi.org/10.3390/risks13010016
Citations
1
Primary Topic
Risk and Portfolio Optimization
Type
article
Field-Weighted Citation Impact
2.11

Funders

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article

Optimal Design of Multi-Asset Options

Raquel Balbás, Alejandro Balbás, Beatriz Balbás
1 citations
Risks
Risk and Portfolio Optimization
2.11
article

Optimal Design of Multi-Asset Options

Raquel Balbás, Alejandro Balbás, Beatriz Balbás
article en
1 citations

Abstract

The combination of stochastic derivative pricing models and downside risk measures often leads to the paradox (risk, return) = (−infinity, +infinity) in a portfolio choice problem. The construction of a portfolio of derivatives with high expected returns and very negative downside risk (henceforth “golden strategy”) has only been studied if all the involved derivatives have the same underlying asset. This paper also considers multi-asset derivatives, gives practical methods to build multi-asset golden strategies for both the expected shortfall and the expectile risk measure, and shows that the use of multi-asset options makes the performance of the obtained golden strategy more efficient. Practical rules are given under the Black–Scholes–Merton multi-dimensional pricing model.

RisksVol. 13(1)
Universidad Complutense de Madrid (ES), Universidad de Alcalá (ES), Universidad Carlos III de Madrid (ES)
Ministerio de Ciencia e Innovación
Openalex Percentile: Top 17%
Risk and Portfolio Optimization
2.11
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