Big data in finance: Evidence and challenges
I review the literature on the use of big data sets in finance. While big data and machine learning are exciting fields, there is a danger that we get carried away by the novelty of the topics but pay less attention to the reliability of the academic evidence. Following my review, I argue that big d...
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Format: | Article |
Language: | English |
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Elsevier
2019-12-01
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Series: | Borsa Istanbul Review |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2214845019302650 |
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author | Avanidhar Subrahmanyam |
author_facet | Avanidhar Subrahmanyam |
author_sort | Avanidhar Subrahmanyam |
collection | DOAJ |
description | I review the literature on the use of big data sets in finance. While big data and machine learning are exciting fields, there is a danger that we get carried away by the novelty of the topics but pay less attention to the reliability of the academic evidence. Following my review, I argue that big data-based evidence should be held to the same academic standards as the rest of the finance academic literature if we are to provide useful advice to finance practitioners. JEL classification: G12, G14, G40 |
first_indexed | 2024-04-12T16:52:56Z |
format | Article |
id | doaj.art-9bf38b4934f54fa4b98c1e2ee09228f6 |
institution | Directory Open Access Journal |
issn | 2214-8450 |
language | English |
last_indexed | 2024-04-12T16:52:56Z |
publishDate | 2019-12-01 |
publisher | Elsevier |
record_format | Article |
series | Borsa Istanbul Review |
spelling | doaj.art-9bf38b4934f54fa4b98c1e2ee09228f62022-12-22T03:24:21ZengElsevierBorsa Istanbul Review2214-84502019-12-01194283287Big data in finance: Evidence and challengesAvanidhar Subrahmanyam0Anderson School, UCLA, Los Angeles, CA, 90095-1481, USAI review the literature on the use of big data sets in finance. While big data and machine learning are exciting fields, there is a danger that we get carried away by the novelty of the topics but pay less attention to the reliability of the academic evidence. Following my review, I argue that big data-based evidence should be held to the same academic standards as the rest of the finance academic literature if we are to provide useful advice to finance practitioners. JEL classification: G12, G14, G40http://www.sciencedirect.com/science/article/pii/S2214845019302650 |
spellingShingle | Avanidhar Subrahmanyam Big data in finance: Evidence and challenges Borsa Istanbul Review |
title | Big data in finance: Evidence and challenges |
title_full | Big data in finance: Evidence and challenges |
title_fullStr | Big data in finance: Evidence and challenges |
title_full_unstemmed | Big data in finance: Evidence and challenges |
title_short | Big data in finance: Evidence and challenges |
title_sort | big data in finance evidence and challenges |
url | http://www.sciencedirect.com/science/article/pii/S2214845019302650 |
work_keys_str_mv | AT avanidharsubrahmanyam bigdatainfinanceevidenceandchallenges |