Index Tracking Based on Dynamic Time Warping and Constrained k-medoids Clustering

Ran Zhang; Hongzong Li; Jun Wang

doi:10.1109/ICICIP53388.2021.9642192

Index Tracking Based on Dynamic Time Warping and Constrained k-medoids Clustering

Ran Zhang
, Hongzong Li
, Jun Wang

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

7 Citations (Scopus)

Abstract

Index tracking is a passive investment strategy by replicating a financial market index using its constituents. In this paper, index tracking is addressed based on k-medoids clustering. k-medoids clustering is formulated as a valuation-constrained k-median problem to cluster index constituents. The dissimilarity coefficients among stocks are measured by using dynamic time warping. Experimental results of index tracking on four major indices are elaborated to demonstrate that the tracking performance of the proposed method with dynamic time warping is superior to that with Pearson correlation coefficients.

Original language	English
Title of host publication	2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)
Publisher	IEEE
Pages	352-359
ISBN (Electronic)	978-1-6654-2515-5
DOIs	https://doi.org/10.1109/ICICIP53388.2021.9642192
Publication status	Published - Dec 2021
Event	11th International Conference on Intelligent Control and Information Processing (ICICIP 2021) - Dali, China Duration: 3 Dec 2021 → 7 Dec 2021

Publication series

Name	International Conference on Intelligent Control and Information Processing, ICICIP

Conference

Conference	11th International Conference on Intelligent Control and Information Processing (ICICIP 2021)
Place	China
City	Dali
Period	3/12/21 → 7/12/21

Research Keywords

dynamic time warping
Index tracking
k-medoids clustering

RGC Funding Information

RGC-funded

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10.1109/ICICIP53388.2021.9642192

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Zhang, R., Li, H., & Wang, J. (2021). Index Tracking Based on Dynamic Time Warping and Constrained k-medoids Clustering. In 2021 11th International Conference on Intelligent Control and Information Processing (ICICIP) (pp. 352-359). (International Conference on Intelligent Control and Information Processing, ICICIP). IEEE. https://doi.org/10.1109/ICICIP53388.2021.9642192

@inproceedings{c2cac5c0b05f482e8edb262429b42da2,

title = "Index Tracking Based on Dynamic Time Warping and Constrained k-medoids Clustering",

abstract = "Index tracking is a passive investment strategy by replicating a financial market index using its constituents. In this paper, index tracking is addressed based on k-medoids clustering. k-medoids clustering is formulated as a valuation-constrained k-median problem to cluster index constituents. The dissimilarity coefficients among stocks are measured by using dynamic time warping. Experimental results of index tracking on four major indices are elaborated to demonstrate that the tracking performance of the proposed method with dynamic time warping is superior to that with Pearson correlation coefficients.",

keywords = "dynamic time warping, Index tracking, k-medoids clustering",

author = "Ran Zhang and Hongzong Li and Jun Wang",

year = "2021",

month = dec,

doi = "10.1109/ICICIP53388.2021.9642192",

language = "English",

series = "International Conference on Intelligent Control and Information Processing, ICICIP",

publisher = "IEEE",

pages = "352--359",

booktitle = "2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)",

address = "United States",

note = "11th International Conference on Intelligent Control and Information Processing (ICICIP 2021) ; Conference date: 03-12-2021 Through 07-12-2021",

}

Zhang, R, Li, H & Wang, J 2021, Index Tracking Based on Dynamic Time Warping and Constrained k-medoids Clustering. in 2021 11th International Conference on Intelligent Control and Information Processing (ICICIP). International Conference on Intelligent Control and Information Processing, ICICIP, IEEE, pp. 352-359, 11th International Conference on Intelligent Control and Information Processing (ICICIP 2021), Dali, China, 3/12/21. https://doi.org/10.1109/ICICIP53388.2021.9642192

Index Tracking Based on Dynamic Time Warping and Constrained k-medoids Clustering. / Zhang, Ran; Li, Hongzong ; Wang, Jun.
2021 11th International Conference on Intelligent Control and Information Processing (ICICIP). IEEE, 2021. p. 352-359 (International Conference on Intelligent Control and Information Processing, ICICIP).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Index Tracking Based on Dynamic Time Warping and Constrained k-medoids Clustering

AU - Zhang, Ran

AU - Li, Hongzong

AU - Wang, Jun

PY - 2021/12

Y1 - 2021/12

N2 - Index tracking is a passive investment strategy by replicating a financial market index using its constituents. In this paper, index tracking is addressed based on k-medoids clustering. k-medoids clustering is formulated as a valuation-constrained k-median problem to cluster index constituents. The dissimilarity coefficients among stocks are measured by using dynamic time warping. Experimental results of index tracking on four major indices are elaborated to demonstrate that the tracking performance of the proposed method with dynamic time warping is superior to that with Pearson correlation coefficients.

AB - Index tracking is a passive investment strategy by replicating a financial market index using its constituents. In this paper, index tracking is addressed based on k-medoids clustering. k-medoids clustering is formulated as a valuation-constrained k-median problem to cluster index constituents. The dissimilarity coefficients among stocks are measured by using dynamic time warping. Experimental results of index tracking on four major indices are elaborated to demonstrate that the tracking performance of the proposed method with dynamic time warping is superior to that with Pearson correlation coefficients.

KW - dynamic time warping

KW - Index tracking

KW - k-medoids clustering

UR - https://www.scopus.com/pages/publications/85123831992

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85123831992&origin=recordpage

U2 - 10.1109/ICICIP53388.2021.9642192

DO - 10.1109/ICICIP53388.2021.9642192

M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - International Conference on Intelligent Control and Information Processing, ICICIP

SP - 352

EP - 359

BT - 2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)

PB - IEEE

T2 - 11th International Conference on Intelligent Control and Information Processing (ICICIP 2021)

Y2 - 3 December 2021 through 7 December 2021

ER -

Index Tracking Based on Dynamic Time Warping and Constrained k-medoids Clustering

Abstract

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Research Keywords

RGC Funding Information

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