TY - GEN
T1 - Metaheuristics for Index-Tracking with Cardinality Constraints
AU - Yuen, Man Chung
AU - Ng, Sin Chun
AU - Leung, Man Fai
AU - Che, Hangjun
N1 - Funding Information:
This work was supported in part by National Natural Science Foundation of China (Grant No. 62003281), and in part by the Fundamental Research Funds for the Central Universities (Grant No.SWU020006), and in part by the Open University of Hong Kong Research Grant (No. 2020/1.4).
Publisher Copyright:
© 2021 IEEE.
PY - 2021/5/21
Y1 - 2021/5/21
N2 - As one of the passive investment strategies, index-tracking aims to replicate market indexes to reproduce market performance. It is widely used for long-term investment. Full replication and partial index-tracking are common approaches for index-tracking problems. Although full replication tracks the chosen market index perfectly, the transaction cost is relatively high in practice. Therefore, partial index-tracking is desired that can reduce the transaction cost and avoid illiquid assets. The partial index-tracking approach selects the subset of a benchmark index and applies restrictions for the numbers of stocks with cardinality constraints. The constrained problem is converted into an unconstrained problem by adding the penalty term. This paper is concerned with the sparse index-tracking problem with cardinality constraints by various metaheuristics. Various metaheuristics are used to deal with the sparse index-tracking problem, and their performances are compared. Also, various penalty values are adopted to test the performance of the compared algorithm.
AB - As one of the passive investment strategies, index-tracking aims to replicate market indexes to reproduce market performance. It is widely used for long-term investment. Full replication and partial index-tracking are common approaches for index-tracking problems. Although full replication tracks the chosen market index perfectly, the transaction cost is relatively high in practice. Therefore, partial index-tracking is desired that can reduce the transaction cost and avoid illiquid assets. The partial index-tracking approach selects the subset of a benchmark index and applies restrictions for the numbers of stocks with cardinality constraints. The constrained problem is converted into an unconstrained problem by adding the penalty term. This paper is concerned with the sparse index-tracking problem with cardinality constraints by various metaheuristics. Various metaheuristics are used to deal with the sparse index-tracking problem, and their performances are compared. Also, various penalty values are adopted to test the performance of the compared algorithm.
KW - cardinality constraints
KW - constrained optimization
KW - Index-tracking
KW - metaheuristics
UR - http://www.scopus.com/inward/record.url?scp=85107923439&partnerID=8YFLogxK
U2 - 10.1109/ICIST52614.2021.9440584
DO - 10.1109/ICIST52614.2021.9440584
M3 - Conference contribution
AN - SCOPUS:85107923439
T3 - 2021 11th International Conference on Information Science and Technology, ICIST 2021
SP - 646
EP - 651
BT - 2021 11th International Conference on Information Science and Technology, ICIST 2021
T2 - 11th International Conference on Information Science and Technology, ICIST 2021
Y2 - 21 May 2021 through 23 May 2021
ER -