# Robust Portfolio Optimisation with Specified Competitors

## TL;DR

This paper introduces a flexible robust portfolio optimization framework that allows portfolios to optimize their distance to benchmarks and choose between different regret measures and constraints, improving practical applicability.

## Contribution

It extends existing models by incorporating benchmark distance optimization, alternative regret calculations, and constraint-based approaches, enhancing real-world portfolio management.

## Key findings

- Improved alignment with market practices in regret measurement
- Enhanced flexibility in portfolio optimization constraints
- Successful application to equity portfolios across regions

## Abstract

We extend Relative Robust Portfolio Optimisation models to allow portfolios to optimise their distance to a set of benchmarks. Portfolio managers are also given the option of computing regret in a way which is more in line with market practices than other approaches suggested in the literature. In addition, they are given the choice of simply adding an extra constraint to their optimisation problem instead of outright changing the objective function, as is commonly suggested in the literature. We illustrate the benefits of this approach by applying it to equity portfolios in a variety of regions.