Imperial College London


Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor of Signal Processing



+44 (0)20 7594 6271d.mandic Website




Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267




813Electrical EngineeringSouth Kensington Campus






BibTex format

author = {Dees, BS and Stankovic, L and Constantinides, AG and Mandic, DP},
doi = {10.1109/ICASSP40776.2020.9054371},
pages = {8454--8458},
title = {Portfolio Cuts: A Graph-Theoretic Framework to Diversification},
url = {},
year = {2020}

RIS format (EndNote, RefMan)

AB - © 2020 IEEE. Investment returns naturally reside on irregular domains, however, standard multivariate portfolio optimization methods are agnostic to data structure. To this end, we investigate ways for domain knowledge to be conveniently incorporated into the analysis, by means of graphs. Next, to relax the assumption of the completeness of graph topology and to equip the graph model with practically relevant physical intuition, we introduce the portfolio cut paradigm. Such a graph-theoretic portfolio partitioning technique is shown to allow the investor to devise robust and tractable asset allocation schemes, by virtue of a rigorous graph framework for considering smaller, computationally feasible, and economically meaningful clusters of assets, based on graph cuts. In turn, this makes it possible to fully utilize the asset returns covariance matrix for constructing the portfolio, even without the requirement for its inversion. The advantages of the proposed framework over traditional methods are demonstrated through numerical simulations based on real-world price data.
AU - Dees,BS
AU - Stankovic,L
AU - Constantinides,AG
AU - Mandic,DP
DO - 10.1109/ICASSP40776.2020.9054371
EP - 8458
PY - 2020///
SN - 1520-6149
SP - 8454
TI - Portfolio Cuts: A Graph-Theoretic Framework to Diversification
UR -
ER -