Add to ORKGConsidering mean-variance portfolio problems with uncertain model parameters, we contrast the classical absolute robust optimization approach with the relative robust approach based on a maximum regret function. Although the latter problems are NP-hard in general, we show that tractable inner and outer approximations exist in several cases that are of central interest in asset management
Portfolio optimization models aim to optimally distribute capital among selected stocks, bonds and o...
01 Abstract: This thesis is concerned with the robust methods in portfolio theory. Different risk me...
Abstract In this paper, we consider the robust portfolio selection problem which has a data uncertai...
Considering mean-variance portfolio problems with uncertain model parameters, we contrast the classi...
This paper presents new models which seek to optimize the first and second moments of asset returns ...
In this paper, a new methodology for computing relative-robust portfolios based on minimax regret is...
Many financial optimization problems involve future values of security prices, interest rates and ex...
A robust optimization has emerged as a powerful tool for managing un- certainty in many optimization...
Many financial optimization problems involve future values of security prices, interest rates and ex...
We extend Relative Robust Portfolio Optimization models to allow portfolios to optimize their perfor...
Using optimization techniques in portfolio selection has attracted significant attention in financia...
The Markowitz mean-variance portfolio optimization is a well known and also widely used investment t...
Many optimization problems involve parameters which are not known in advance, but can only be foreca...
We extend Relative Robust Portfolio Optimization models to allow portfolios to optimize their perfor...
Portfolio Optimization is based on the efficient allocation of several assets, which can get heavily...
Portfolio optimization models aim to optimally distribute capital among selected stocks, bonds and o...
01 Abstract: This thesis is concerned with the robust methods in portfolio theory. Different risk me...
Abstract In this paper, we consider the robust portfolio selection problem which has a data uncertai...
Considering mean-variance portfolio problems with uncertain model parameters, we contrast the classi...
This paper presents new models which seek to optimize the first and second moments of asset returns ...
In this paper, a new methodology for computing relative-robust portfolios based on minimax regret is...
Many financial optimization problems involve future values of security prices, interest rates and ex...
A robust optimization has emerged as a powerful tool for managing un- certainty in many optimization...
Many financial optimization problems involve future values of security prices, interest rates and ex...
We extend Relative Robust Portfolio Optimization models to allow portfolios to optimize their perfor...
Using optimization techniques in portfolio selection has attracted significant attention in financia...
The Markowitz mean-variance portfolio optimization is a well known and also widely used investment t...
Many optimization problems involve parameters which are not known in advance, but can only be foreca...
We extend Relative Robust Portfolio Optimization models to allow portfolios to optimize their perfor...
Portfolio Optimization is based on the efficient allocation of several assets, which can get heavily...
Portfolio optimization models aim to optimally distribute capital among selected stocks, bonds and o...
01 Abstract: This thesis is concerned with the robust methods in portfolio theory. Different risk me...
Abstract In this paper, we consider the robust portfolio selection problem which has a data uncertai...