Artikel
Market graph clustering via QUBO and digital annealing
We present a novel technique for cardinality-constrained index-tracking, a common task in the financial industry. Our approach is based on market graph models. We model our reference indices as market graphs and express the index-tracking problem as a quadratic K-medoids clustering problem. We take advantage of a purpose-built hardware architecture to circumvent the NP-hard nature of the problem and solve our formulation efficiently. The main contributions of this article are bridging three separate areas of the literature, market graph models, K-medoid clustering and quadratic binary optimization modeling, to formulate the index-tracking problem as a binary quadratic K-medoid graph-clustering problem. Our initial results show we accurately replicate the returns of various market indices, using only a small subset of their constituent assets. Moreover, our binary quadratic formulation allows us to take advantage of recent hardware advances to overcome the NP-hard nature of the problem and obtain solutions faster than with traditional architectures and solvers.
- Language
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Englisch
- Bibliographic citation
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Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 14 ; Year: 2021 ; Issue: 1 ; Pages: 1-13 ; Basel: MDPI
- Classification
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Wirtschaft
- Subject
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graph clustering
K-medoids
market graph
combinatorial optimization
QUBO
portfolioconstruction
index-tracking
- Event
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Geistige Schöpfung
- (who)
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Hong, Seo Woo
Miasnikof, Pierre
Kwon, Roy
Lawryshyn, Yuri
- Event
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Veröffentlichung
- (who)
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MDPI
- (where)
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Basel
- (when)
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2021
- DOI
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doi:10.3390/jrfm14010034
- Handle
- Last update
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10.03.2025, 11:44 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Hong, Seo Woo
- Miasnikof, Pierre
- Kwon, Roy
- Lawryshyn, Yuri
- MDPI
Time of origin
- 2021
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