| Publication type: | Working paper – expertise – study |
| Title: | Hedging goals |
| Authors: | Krabichler, Thomas Wunsch, Marcus |
| et. al: | No |
| Extent: | 28 |
| Issue Date: | 2021 |
| Publisher / Ed. Institution: | arXiv |
| Other identifiers: | arXiv:2105.07915 |
| Language: | English |
| Subject (DDC): | 332.6: Investment |
| Abstract: | Goal-based investing is concerned with reaching a monetary investment goal by a given finite deadline, which differs from mean-variance optimization in modern portfolio theory. In this article, we expand the close connection between goal-based investing and option hedging that was originally discovered in [Bro99b] by allowing for varying degrees of investor risk aversion using lower partial moments of different orders. Moreover, we show that maximizing the probability of reaching the goal (quantile hedging, cf. [FL99]) and minimizing the expected shortfall (efficient hedging, cf. [FL00]) yield, in fact, the same optimal investment policy. We furthermore present an innovative and model-free approach to goal-based investing using methods of reinforcement learning. To the best of our knowledge, we offer the first algorithmic approach to goal-based investing that can find optimal solutions in the presence of transaction costs. |
| URI: | https://arxiv.org/abs/2105.07915 https://digitalcollection.zhaw.ch/handle/11475/24319 |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Management and Law |
| Organisational Unit: | Institute of Wealth & Asset Management (IWA) |
| Appears in collections: | Publikationen School of Management and Law |
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