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Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Decision Theory Matters for Financial Advice |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | Computational Economics |
| Publisher | Springer |
| Geographical Reach | international |
| ISSN | 0927-7099 |
| Volume | 52 |
| Number | 1 |
| Page Range | 195 - 226 |
| Date | 2018 |
| Abstract Text | We show that the optimal asset allocation for an investor depends crucially on the decision theory with which the investor is modeled. For the same market data and the same client data different theories lead to different portfolios. The market data we consider is standard asset allocation data. The client data is determined by a standard risk profiling question and the theories we apply are mean–variance analysis, expected utility analysis and cumulative prospect theory. For testing the robustness of our results, we carry out the comparisons for alternative data sets and also for variants of the risk profiling question. |
| Digital Object Identifier | 10.1007/s10614-017-9668-6 |
| Other Identification Number | merlin-id:14697 |
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