Back to Search
Start Over
Quantile-based optimal portfolio selection
- Source :
- Computational Management Science. 18:299-324
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- In this paper the concept of quantile-based optimal portfolio selection is introduced and a specific portfolio connected to it, the conditional value-of-return (CVoR) portfolio, is proposed. The CVoR is defined as the mean excess return or the conditional value-at-risk (CVaR) of the return distribution. The portfolio selection consists solely of quantile-based risk and return measures. Financial institutions that work in the context of Basel 4 use CVaR as a risk measure. In this regulatory framework sufficient and necessary conditions for optimality of the CVoR portfolio are provided under a general distributional assumption. Moreover, it is shown that the CVoR portfolio is mean-variance efficient when the returns are assumed to follow an elliptically contoured distribution. Under this assumption the closed-form expression for the weights and characteristics of the CVoR portfolio are obtained. Finally, the introduced methods are illustrated in an empirical study based on monthly data of returns on stocks included in the S&P index. It is shown that the new portfolio selection strategy outperforms several alternatives in terms of the final investor wealth.
- Subjects :
- 021103 operations research
Index (economics)
CVAR
Risk measure
05 social sciences
0211 other engineering and technologies
Context (language use)
Risk–return spectrum
02 engineering and technology
Management Information Systems
0502 economics and business
Econometrics
Portfolio
050203 business & management
Selection (genetic algorithm)
Information Systems
Mathematics
Quantile
Subjects
Details
- ISSN :
- 16196988 and 1619697X
- Volume :
- 18
- Database :
- OpenAIRE
- Journal :
- Computational Management Science
- Accession number :
- edsair.doi...........e9d195fc67267b3542b36091f42f46cf
- Full Text :
- https://doi.org/10.1007/s10287-021-00395-8