Signal-Wise Performance Attribution for Constrained Portfolio Optimisation

Cardinality Constrained Portfolio Optimisation

The traditional quadratic programming approach to portfolio optimisation is difficult to implement when there are cardinality constraints. Recent approaches to resolving this have used heuristic algorithms to search for points on the cardinality constrained frontier. However, these can be computationally expensive when the practitioner does not know a priori exactly how many assets they may des...

Heuristics for cardinality constrained portfolio optimisation

In this paper we consider the problem of "nding the e$cient frontier associated with the standard mean}variance portfolio optimisation model. We extend the standard model to include cardinality constraints that limit a portfolio to have a speci"ed number of assets, and to impose limits on the proportion of the portfolio held in a given asset (if any of the asset is held). We illustrate the di!e...

Total Portfolio Performance Attribution Methodology

Solving norm constrained portfolio optimization via coordinate-wise descent algorithms

In this paper we demonstrate that coordinate-wise descent algorithms can be used to solve portfolio selection problems in which asset weights are constrained by l q norms for 1 ≤ q ≤ 2. A special case of the such problems is when q = 1. The l 1 norm constraint promotes zero values for the weight vector, leading to an automatic asset selection for the portfolio. We first consider the case of min...

Constrained Portfolio Optimisation: The State-of-the-Art Markowitz Models

This paper studies the state-of-art constrained portfolio optimisation models, using exact solver to identify the optimal solutions or lower bound for the benchmark instances at the OR-library with extended constraints. The effects of pre-assignment, round-lot, and class constraints based on the quantity and cardinality constrained Markowitz model are firstly investigated to gain insights of in...