Market graph clustering via QUBO and digital annealing

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Veröffentlicht in:	Journal of risk and financial management 14(2021), 1/34 vom: Jan., Seite 1-13
Personen und Körperschaften:	Hong, Seo Woo (VerfasserIn), Miasnikof, Pierre (VerfasserIn), Kwon, Roy (VerfasserIn), Lawryshyn, Yuri (VerfasserIn)
Titel:	Market graph clustering via QUBO and digital annealing/ Seo Woo Hong, Pierre Miasnikof, Roy Kwon and Yuri Lawryshyn
Format:	E-Book-Kapitel
Sprache:	Englisch
veröffentlicht:	2021
Gesamtaufnahme:	: Journal of risk and financial management, 14(2021), 1/34 vom: Jan., Seite 1-13 , volume:14
Schlagwörter:	graph clustering K-medoids market graph combinatorial optimization QUBO portfolioconstruction index-tracking Aufsatz in Zeitschrift
Quelle:	Verbunddaten SWB Lizenzfreie Online-Ressourcen

Details
Zusammenfassung:	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.
ISSN:	1911-8074
DOI:	10.3390/jrfm14010034
Zugang:	Open Access