How to Keep Your Portfolio Close in Risk and Diversification to a Desired Benchmark

Argimiro Arratia (), Henryk Gzyl () and Silvia Mayoral ()
Additional contact information
Argimiro Arratia: Universitat Politécnica de Catalunya
Silvia Mayoral: Universidad Carlos III de Madrid

Computational Economics, 2024, vol. 64, issue 3, No 6, 1489-1505

Abstract: Abstract The standard approach to portfolio management consists of determining the best trade-off between risk and return. This usually results in portfolios concentrated in a small collection of the available assets. To offset this one can start with a well-diversified portfolio, to be regarded as a benchmark, then search for a portfolio that improves upon its return. The main issue is that the search has to be carried out in a neighborhood in which diversification is maintained and the risk is under control. Here we examine three ways of defining the neighborhood of the well-diversified portfolio, and see that the nature of the optimal portfolio within that neighborhood changes considerably. As there is no universal choice for the distance between portfolios, this poses an interesting and hard problem for the portfolio manager.

Keywords: Well diversified portfolio; Benchmark tracking; Risk controlled optimal portfolio; Maximum entropy in mean for linear programming problems (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-023-10485-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:compec:v:64:y:2024:i:3:d:10.1007_s10614-023-10485-1

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-023-10485-1

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().