TY - JOUR
T1 - Exploring the (Efficient) Frontiers of Portfolio Optimization
AU - Craven, MJ
AU - Graham, DI
PY - 2017/7/18
Y1 - 2017/7/18
N2 - The cardinality-constrained portfolio optimization problem is NP-hard. Its Pareto front (or the Efficient Frontier - EF) is usually calculated by stochastic algorithms, including EAs. However, in certain cases the EF may be decomposed into a union of sub-EFs. In this work we propose a systematic process of excluding sub-EFs dominated by others, enabling us to calculate non-dominated sub-EFs. We then calculate whole EFs to a high degree of accuracy for small cardinalities, providing an alternative to EAs in those cases. We can use also this to provide insight into EAs on the problem.
AB - The cardinality-constrained portfolio optimization problem is NP-hard. Its Pareto front (or the Efficient Frontier - EF) is usually calculated by stochastic algorithms, including EAs. However, in certain cases the EF may be decomposed into a union of sub-EFs. In this work we propose a systematic process of excluding sub-EFs dominated by others, enabling us to calculate non-dominated sub-EFs. We then calculate whole EFs to a high degree of accuracy for small cardinalities, providing an alternative to EAs in those cases. We can use also this to provide insight into EAs on the problem.
UR - https://pearl.plymouth.ac.uk/context/secam-research/article/1859/viewcontent/exploring_efficient_frontiers.pdf
U2 - 10.1145/3067695.3082036
DO - 10.1145/3067695.3082036
M3 - Conference proceedings published in a journal
VL - 0
JO - Default journal
JF - Default journal
IS - 0
T2 - GECCO 2017
Y2 - 15 July 2017 through 19 July 2017
ER -