Eintrag weiter verarbeiten
Market graph clustering via QUBO and digital annealing
Gespeichert in:
| Veröffentlicht in: | Journal of risk and financial management 14(2021), 1/34 vom: Jan., Seite 1-13 |
|---|---|
| Personen und Körperschaften: | , , , |
| 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: | |
| Quelle: | Verbunddaten SWB Lizenzfreie Online-Ressourcen |
| LEADER | 03382caa a2200589 4500 | ||
|---|---|---|---|
| 001 | 0-1745186018 | ||
| 003 | DE-627 | ||
| 005 | 20211028101102.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 210121s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.3390/jrfm14010034 |2 doi | |
| 024 | 7 | |a 10419/239451 |2 hdl | |
| 035 | |a (DE-627)1745186018 | ||
| 035 | |a (DE-599)KXP1745186018 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rda | ||
| 041 | |a eng | ||
| 100 | 1 | |a Hong, Seo Woo |e VerfasserIn |4 aut | |
| 245 | 1 | 0 | |a Market graph clustering via QUBO and digital annealing |c Seo Woo Hong, Pierre Miasnikof, Roy Kwon and Yuri Lawryshyn |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 506 | 0 | |q DE-206 |a Open Access |e Controlled Vocabulary for Access Rights |u http://purl.org/coar/access_right/c_abf2 | |
| 520 | |a 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. | ||
| 540 | |q DE-206 |a Namensnennung 4.0 International |f CC BY 4.0 |2 cc |u https://creativecommons.org/licenses/by/4.0/ | ||
| 650 | 4 | |a graph clustering | |
| 650 | 4 | |a K-medoids | |
| 650 | 4 | |a market graph | |
| 650 | 4 | |a combinatorial optimization | |
| 650 | 4 | |a QUBO | |
| 650 | 4 | |a portfolioconstruction | |
| 650 | 4 | |a index-tracking | |
| 655 | 4 | |a Aufsatz in Zeitschrift |5 DE-206 | |
| 700 | 1 | |a Miasnikof, Pierre |e VerfasserIn |4 aut | |
| 700 | 1 | |a Kwon, Roy |e VerfasserIn |4 aut | |
| 700 | 1 | |a Lawryshyn, Yuri |e VerfasserIn |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of risk and financial management |d Basel : MDPI, 2008 |g 14(2021), 1/34 vom: Jan., Seite 1-13 |h Online-Ressource |w (DE-627)770970427 |w (DE-600)2739117-6 |w (DE-576)395129494 |x 1911-8074 |7 nnns |
| 773 | 1 | 8 | |g volume:14 |g year:2021 |g number:1/34 |g month:01 |g pages:1-13 |
| 856 | 4 | 0 | |u https://www.mdpi.com/1911-8074/14/1/34/pdf |x Verlag |z kostenfrei |
| 856 | 4 | 0 | |u https://doi.org/10.3390/jrfm14010034 |x Resolving-System |z kostenfrei |
| 856 | 4 | 0 | |u http://hdl.handle.net/10419/239451 |x Resolving-System |z kostenfrei |
| 936 | u | w | |d 14 |j 2021 |e 1/34 |c 1 |h 1-13 |
| 951 | |a AR | ||
| 856 | 4 | 0 | |u https://doi.org/10.3390/jrfm14010034 |9 LFER |
| 856 | 4 | 0 | |u https://www.mdpi.com/1911-8074/14/1/34/pdf |9 LFER |
| 852 | |a LFER |z 2021-02-09T15:10:58Z | ||
| 970 | |c OD | ||
| 971 | |c EBOOK | ||
| 972 | |c EBOOK | ||
| 973 | |c Aufsatz | ||
| 935 | |a lfer | ||
| 980 | |a 1745186018 |b 0 |k 1745186018 |c lfer | ||
| openURL |
url_ver=Z39.88-2004&ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fvufind.svn.sourceforge.net%3Agenerator&rft.title=Market+graph+clustering+via+QUBO+and+digital+annealing&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.creator=Hong%2C+Seo+Woo&rft.pub=&rft.format=Journal&rft.language=English&rft.issn=1911-8074 |
|---|
| _version_ | 1757969407771934720 |
|---|---|
| access_facet | Electronic Resources |
| access_state_str | Open Access |
| author | Hong, Seo Woo, Miasnikof, Pierre, Kwon, Roy, Lawryshyn, Yuri |
| author_facet | Hong, Seo Woo, Miasnikof, Pierre, Kwon, Roy, Lawryshyn, Yuri |
| author_role | aut, aut, aut, aut |
| author_sort | Hong, Seo Woo |
| author_variant | s w h sw swh, p m pm, r k rk, y l yl |
| callnumber-sort | |
| collection | lfer |
| container_reference | 14(2021), 1/34 vom: Jan., Seite 1-13 |
| container_title | Journal of risk and financial management |
| contents | 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. |
| ctrlnum | (DE-627)1745186018, (DE-599)KXP1745186018 |
| doi_str_mv | 10.3390/jrfm14010034 |
| facet_avail | Online, Free |
| finc_class_facet | not assigned |
| format | ElectronicBookComponentPart |
| format_access_txtF_mv | Article, E-Article |
| format_de105 | Ebook |
| format_de14 | Article, E-Article |
| format_de15 | Article, E-Article |
| format_del152 | Buch |
| format_detail_txtF_mv | text-online-monograph-child |
| format_dezi4 | e-Book |
| format_finc | Article, E-Article |
| format_legacy | ElectronicBookPart |
| format_strict_txtF_mv | E-Article |
| genre | Aufsatz in Zeitschrift DE-206 |
| genre_facet | Aufsatz in Zeitschrift |
| geogr_code | not assigned |
| geogr_code_person | not assigned |
| hierarchy_parent_id | 0-770970427 |
| hierarchy_parent_title | Journal of risk and financial management |
| hierarchy_sequence | 14(2021), 1/34 vom: Jan., Seite 1-13 |
| hierarchy_top_id | 0-770970427 |
| hierarchy_top_title | Journal of risk and financial management |
| id | 0-1745186018 |
| illustrated | Not Illustrated |
| imprint | 2021 |
| imprint_str_mv | 2021 |
| institution | DE-D117, DE-105, LFER, DE-Ch1, DE-15, DE-14, DE-Zwi2 |
| is_hierarchy_id | 0-1745186018 |
| is_hierarchy_title | Market graph clustering via QUBO and digital annealing |
| isil_str_mv | LFER |
| issn | 1911-8074 |
| kxp_id_str | 1745186018 |
| language | English |
| last_indexed | 2023-02-16T06:51:11.066Z |
| license_str_mv | https://creativecommons.org/licenses/by |
| local_heading_facet_dezwi2 | graph clustering, K-medoids, market graph, combinatorial optimization, QUBO, portfolioconstruction, index-tracking |
| marc024a_ct_mv | 10.3390/jrfm14010034, 10419/239451 |
| match_str | hong2021marketgraphclusteringviaquboanddigitalannealing |
| mega_collection | Verbunddaten SWB, Lizenzfreie Online-Ressourcen |
| misc_de105 | EBOOK |
| multipart_link | 395129494 |
| multipart_part | (395129494)14(2021), 1/34 vom: Jan., Seite 1-13 |
| publishDate | 2021 |
| publishDateSort | 2021 |
| publishPlace | |
| publisher | |
| record_format | marcfinc |
| record_id | 1745186018 |
| recordtype | marcfinc |
| rvk_facet | No subject assigned |
| source_id | 0 |
| spelling | Hong, Seo Woo VerfasserIn aut, Market graph clustering via QUBO and digital annealing Seo Woo Hong, Pierre Miasnikof, Roy Kwon and Yuri Lawryshyn, 2021, Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2, 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., DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/, graph clustering, K-medoids, market graph, combinatorial optimization, QUBO, portfolioconstruction, index-tracking, Aufsatz in Zeitschrift DE-206, Miasnikof, Pierre VerfasserIn aut, Kwon, Roy VerfasserIn aut, Lawryshyn, Yuri VerfasserIn aut, Enthalten in Journal of risk and financial management Basel : MDPI, 2008 14(2021), 1/34 vom: Jan., Seite 1-13 Online-Ressource (DE-627)770970427 (DE-600)2739117-6 (DE-576)395129494 1911-8074 nnns, volume:14 year:2021 number:1/34 month:01 pages:1-13, https://www.mdpi.com/1911-8074/14/1/34/pdf Verlag kostenfrei, https://doi.org/10.3390/jrfm14010034 Resolving-System kostenfrei, http://hdl.handle.net/10419/239451 Resolving-System kostenfrei, https://doi.org/10.3390/jrfm14010034 LFER, https://www.mdpi.com/1911-8074/14/1/34/pdf LFER, LFER 2021-02-09T15:10:58Z |
| spellingShingle | Hong, Seo Woo, Miasnikof, Pierre, Kwon, Roy, Lawryshyn, Yuri, 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., graph clustering, K-medoids, market graph, combinatorial optimization, QUBO, portfolioconstruction, index-tracking, Aufsatz in Zeitschrift |
| title | Market graph clustering via QUBO and digital annealing |
| title_auth | Market graph clustering via QUBO and digital annealing |
| title_full | Market graph clustering via QUBO and digital annealing Seo Woo Hong, Pierre Miasnikof, Roy Kwon and Yuri Lawryshyn |
| title_fullStr | Market graph clustering via QUBO and digital annealing Seo Woo Hong, Pierre Miasnikof, Roy Kwon and Yuri Lawryshyn |
| title_full_unstemmed | Market graph clustering via QUBO and digital annealing Seo Woo Hong, Pierre Miasnikof, Roy Kwon and Yuri Lawryshyn |
| title_in_hierarchy | Market graph clustering via QUBO and digital annealing / Seo Woo Hong, Pierre Miasnikof, Roy Kwon and Yuri Lawryshyn, |
| title_short | Market graph clustering via QUBO and digital annealing |
| title_sort | market graph clustering via qubo and digital annealing |
| topic | graph clustering, K-medoids, market graph, combinatorial optimization, QUBO, portfolioconstruction, index-tracking, Aufsatz in Zeitschrift |
| topic_facet | graph clustering, K-medoids, market graph, combinatorial optimization, QUBO, portfolioconstruction, index-tracking, Aufsatz in Zeitschrift |
| url | https://www.mdpi.com/1911-8074/14/1/34/pdf, https://doi.org/10.3390/jrfm14010034, http://hdl.handle.net/10419/239451 |