Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 44 min ago
Peer-reviewedCC BY 4.0Mathematics

A Multi-Period MILP Model for Dynamic Index Tracking

  • Yanzhe Dong1
  • Binwei Xu2
  • Yujia Liu3
  • Liang Wu2
  1. 1School of Economics, Peking University, Beijing 100871, China
  2. 2Bay Area International Business School, Beijing Normal University, Zhuhai 519087, China
  3. 3School of Economics, Sichuan University, Chengdu 610065, China
Open at sourceDOICite

Abstract

This study extends an existing single-period mixed-integer linear programming (MILP) formulation to a multi-period index-tracking problem. The proposed model allows the tracking portfolio to be rebalanced at predetermined times while limiting the associated transaction costs. Two benchmark strategies are considered: a fixed portfolio with no rebalancing and a portfolio reselected under a large transaction-cost limit intended to approximate unrestricted rebalancing. The models are evaluated using constituent data for the SSE 50 and CSI 100 indices. Tracking performance is measured in-sample and out-of-sample for different portfolio cardinalities, sample lengths, and transaction-cost limits. Among the parameter values examined, at least one multi-period specification produces a lower out-of-sample root-mean-square error (RMSE) than both benchmarks in seven of the eight reported configurations. However, the optimal transaction-cost limit varies across configurations, indicating that tracking performance is sensitive to the permitted degree of rebalancing.

Related

  1. The p-local topologoical period-index problem in dimensions 2p+2 and below
    Diarmuid Crowley, Xing Gu
    arXivPreprintarXiv licenceFull textGeometry & topologyarXiv
  2. Minimal Trivializing Isogenies of 𝔾m-gerbes over Abelian Varieties and Period-Index Problem
    Ruoxi Li
    arXivPreprintarXiv licenceFull textAlgebra & number theoryarXiv
  3. Counterexamples to O'Neil's Period-Index Problem on Elliptic Curves
    Xiaoguang Shang, Cheng Niu
    arXivPreprintCC BY 4.0Full textAlgebra & number theoryarXiv
  4. The period-index conjecture is false for motivic reasons
    Alexander Perry
    arXivPreprintarXiv licenceFull textAlgebra & number theoryarXiv
  5. Fundamental Limits of Dynamic Tracking and Communication: A Stationary Policy Formulation
    Mohammadreza Bakhshizadeh Mohajer, Luca Barletta, Alex Dytso +1
    arXivPreprintCC BY 4.0Full textGeneral mathematicsarXiv

Cite

BibTeXRIS
BibTeX
@article{dong2026multiperiod,
  title = {{A Multi-Period MILP Model for Dynamic Index Tracking}},
  author = {Yanzhe Dong and Binwei Xu and Yujia Liu and Liang Wu},
  journal = {Mathematics},
  year = {2026},
  month = oct,
  doi = {10.3390/math14203836},
  url = {https://www.mdpi.com/2227-7390/14/20/3836},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - A Multi-Period MILP Model for Dynamic Index Tracking
AU  - Yanzhe Dong
AU  - Binwei Xu
AU  - Yujia Liu
AU  - Liang Wu
PY  - 2026
DA  - 2026/10/21
JO  - Mathematics
DO  - 10.3390/math14203836
UR  - https://www.mdpi.com/2227-7390/14/20/3836
AB  - This study extends an existing single-period mixed-integer linear programming (MILP) formulation to a multi-period index-tracking problem. The proposed model allows the tracking portfolio to be rebalanced at predetermined times while limiting the associated transaction costs. Two benchmark strategies are considered: a fixed portfolio with no rebalancing and a portfolio reselected under a large transaction-cost limit intended to approximate unrestricted rebalancing. The models are evaluated using constituent data for the SSE 50 and CSI 100 indices. Tracking performance is measured in-sample and out-of-sample for different portfolio cardinalities, sample lengths, and transaction-cost limits. Among the parameter values examined, at least one multi-period specification produces a lower out-of-sample root-mean-square error (RMSE) than both benchmarks in seven of the eight reported configurations. However, the optimal transaction-cost limit varies across configurations, indicating that tracking performance is sensitive to the permitted degree of rebalancing.
SN  - 2227-7390
ER  -