Abstract
In general, a portfolio problem minimizes risk (or negative utility) of a portfolio of financial assets with respect to portfolio weights subject to a budget constraint. The inverse portfolio problem then arises when an investor assumes that his/her risk preferences have a numerical representation in the form of a certain class of functionals, e.g. in the form of expected utility, coherent risk measure or mean-deviation functional, and aims to identify such a functional, whose minimization results in a portfolio, e.g. a market index, that he/she is most satisfied with. In this work, the portfolio risk is determined by a coherent risk measure, and the rate of return of investor's preferred portfolio is assumed to be known. The inverse portfolio problem then recovers investor's coherent risk measure either through finding a convex set of feasible probability measures (risk envelope) or in the form of either mixed CVaR or negative Yaari's dual utility. It is solved in single-period and multi-period formulations and is demonstrated in a case study with the FTSE 100 index.
| Original language | English |
|---|---|
| Pages (from-to) | 740-750 |
| Number of pages | 11 |
| Journal | European Journal of Operational Research |
| Volume | 249 |
| Issue number | 2 |
| DOIs | |
| State | Published - 1 Mar 2016 |
Keywords
- Coherent risk measure
- Decision making under risk
- Inverse portfolio problem
- Portfolio optimization
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