Abstract
Quantitative finance uses mathematical models to analyse problems in finance. One of the central topics in quantitative finance is portfolio choice, a field that focuses on making investment decisions under uncertainty. Portfolio choice models consist of two main components: an objective and a representation of the financial market. The objective captures an investor’s preferences, while the financial market model describes how investments evolve over time.
Portfolio choice lies at the heart of this thesis as it focuses on three problems arising in the field. The first paper studies a portfolio choice problem in the pension domain, with a focus on partner pensions, which are payments made to a surviving spouse after the death of their partner. The second paper adopts a fintech perspective, studying a portfolio choice problem from the viewpoint of a robo-advisor that provides personalised financial advice, taking into account the time variation and potential mismeasurement of a client’s risk preferences. The final paper focuses on learning risk preferences, which is an important input parameter not only for the first two papers but for almost all portfolio choice problems.
Portfolio choice lies at the heart of this thesis as it focuses on three problems arising in the field. The first paper studies a portfolio choice problem in the pension domain, with a focus on partner pensions, which are payments made to a surviving spouse after the death of their partner. The second paper adopts a fintech perspective, studying a portfolio choice problem from the viewpoint of a robo-advisor that provides personalised financial advice, taking into account the time variation and potential mismeasurement of a client’s risk preferences. The final paper focuses on learning risk preferences, which is an important input parameter not only for the first two papers but for almost all portfolio choice problems.
| Original language | English |
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| Qualification | Doctor of Philosophy |
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| Award date | 26 May 2026 |
| Place of Publication | Tilburg |
| Publisher | |
| Print ISBNs | 978 90 5668 7953 |
| DOIs | |
| Publication status | Published - 2026 |
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