Portfolio optimisation with options
Fuente:
arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2021
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| _version_ | 1866912018258198528 |
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| author | Chan, Jonathan Raimana Huckle, Thomas Jacquier, Antoine Muguruza, Aitor |
| author_facet | Chan, Jonathan Raimana Huckle, Thomas Jacquier, Antoine Muguruza, Aitor |
| contents | We develop a new analysis for portfolio optimisation with options, tackling the three fundamental issues with this problem: asymmetric options' distributions, high dimensionality and dependence structure. To do so, we propose a new dependency matrix, built upon conditional probabilities between options' payoffs, and show how it can be computed in closed form given a copula structure of the underlying asset prices. The empirical evidence we provide highlights that this approach is efficient, fast and easily scalable to large portfolios of (mixed) options. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2111_12658 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Portfolio optimisation with options Chan, Jonathan Raimana Huckle, Thomas Jacquier, Antoine Muguruza, Aitor Portfolio Management Mathematical Finance 46N10, 62H20, 91G10 We develop a new analysis for portfolio optimisation with options, tackling the three fundamental issues with this problem: asymmetric options' distributions, high dimensionality and dependence structure. To do so, we propose a new dependency matrix, built upon conditional probabilities between options' payoffs, and show how it can be computed in closed form given a copula structure of the underlying asset prices. The empirical evidence we provide highlights that this approach is efficient, fast and easily scalable to large portfolios of (mixed) options. |
| title | Portfolio optimisation with options |
| topic | Portfolio Management Mathematical Finance 46N10, 62H20, 91G10 |
| url | https://arxiv.org/abs/2111.12658 |