Details
| Original language | English |
|---|---|
| Pages (from-to) | 295-314 |
| Number of pages | 20 |
| Journal | SIAM Journal on Financial Mathematics |
| Volume | 15 |
| Issue number | 1 |
| Publication status | Published - 2024 |
Abstract
We study mean-risk optimal portfolio problems where risk is measured by recovery average value at risk, a prominent example in the class of recovery risk measures. We establish existence results in the situation where the joint distribution of portfolio assets is known as well as in the situation where it is uncertain and only assumed to belong to a set of mixtures of benchmark distributions (mixture uncertainty) or to a cloud around a benchmark distribution (box uncertainty). The comparison with the classical average value at risk shows that portfolio selection under its recovery version enables financial institutions to exert better control on the recovery on liabilities while still allowing for tractable computations.
Keywords
- average value at risk, distribution uncertainty, efficient frontier, mean-risk optimal portfolios, mean-risk portfolio selection, recovery average at risk, risk measures, robust portfolio management
ASJC Scopus subject areas
- Mathematics(all)
- Numerical Analysis
- Economics, Econometrics and Finance(all)
- Finance
- Mathematics(all)
- Applied Mathematics
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In: SIAM Journal on Financial Mathematics, Vol. 15, No. 1, 2024, p. 295-314.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Robust Portfolio Selection under Recovery Average Value at Risk
AU - Munari, Cosimo
AU - Pluckebaum, Justin
AU - Weber, Stefan
N1 - Publisher Copyright: © 2024 Society for Industrial and Applied Mathematics Publications. All rights reserved.
PY - 2024
Y1 - 2024
N2 - We study mean-risk optimal portfolio problems where risk is measured by recovery average value at risk, a prominent example in the class of recovery risk measures. We establish existence results in the situation where the joint distribution of portfolio assets is known as well as in the situation where it is uncertain and only assumed to belong to a set of mixtures of benchmark distributions (mixture uncertainty) or to a cloud around a benchmark distribution (box uncertainty). The comparison with the classical average value at risk shows that portfolio selection under its recovery version enables financial institutions to exert better control on the recovery on liabilities while still allowing for tractable computations.
AB - We study mean-risk optimal portfolio problems where risk is measured by recovery average value at risk, a prominent example in the class of recovery risk measures. We establish existence results in the situation where the joint distribution of portfolio assets is known as well as in the situation where it is uncertain and only assumed to belong to a set of mixtures of benchmark distributions (mixture uncertainty) or to a cloud around a benchmark distribution (box uncertainty). The comparison with the classical average value at risk shows that portfolio selection under its recovery version enables financial institutions to exert better control on the recovery on liabilities while still allowing for tractable computations.
KW - average value at risk
KW - distribution uncertainty
KW - efficient frontier
KW - mean-risk optimal portfolios
KW - mean-risk portfolio selection
KW - recovery average at risk
KW - risk measures
KW - robust portfolio management
UR - http://www.scopus.com/inward/record.url?scp=85190334052&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2303.01167
DO - 10.48550/arXiv.2303.01167
M3 - Article
AN - SCOPUS:85190334052
VL - 15
SP - 295
EP - 314
JO - SIAM Journal on Financial Mathematics
JF - SIAM Journal on Financial Mathematics
SN - 1945-497X
IS - 1
ER -