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Quantitative Finance Volume 18, 2018 - Issue 10
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Canonical sectors and evolution of firms in the US stock markets

Lorien X. HaydenDepartment of Physics, Cornell University, Ithaca, NY, 14853USA.ORCID Iconhttp://orcid.org/0000-0002-0047-5140View further author information
ORCID Icon,
Ricky ChachraDepartment of Physics, Cornell University, Ithaca, NY, 14853USA.View further author information
,
Alexander A. AlemiDepartment of Physics, Cornell University, Ithaca, NY, 14853USA.View further author information
,
Paul H. GinspargDepartment of Physics, Cornell University, Ithaca, NY, 14853USA.View further author information
&
James P. SethnaDepartment of Physics, Cornell University, Ithaca, NY, 14853USA.Correspondence[email protected]
ORCID Iconhttp://orcid.org/0000-0001-9126-0892View further author information
ORCID Icon
Pages 1619-1634 | Received 17 Nov 2016, Accepted 19 Jan 2018, Published online: 08 Jun 2018
 
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Abstract

Unsupervised machine learning can provide an objective and comprehensive broad-level sector decomposition of stocks

Acknowledgements

We thank Jean–Philippe Bouchaud, Ming Huang and Janet Gao for helpful discussions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was partially supported by NSF [grant number DMR-1312160], [grant number DMR-1719490], [grant number IIS-1247696] and [grant number DGE-1144153].

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