Questioning the efficient markets hypothesis: big data evidence of non-random stock prices

Darwen, Paul J. (2018) Questioning the efficient markets hypothesis: big data evidence of non-random stock prices. In: Proceedings of the International Conference on Big Data Analysis. pp. 201-205. From: ICBDA 2018: IEEE 3rd International Conference on Big Data Analysis, 9-12 March 2018, Shanghai, China.

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Abstract

The efficient markets hypothesis claims that stock prices fully reflect all available information, and that prediction of future changes in stock prices is impossible. For 50 companies listed on stock exchanges in the United States, this paper compares the real data with random data that follows a similar distribution as the real data, in order to ascertain how much usefully predictive information is in the real data. Surprisingly, it turns out that if one can tolerate a modest number of random false positives, around twelve percent of the time there is a modest amount of information.

Item ID: 53834
Item Type: Conference Item (Research - E1)
ISBN: 978-1-5386-4794-3
Keywords: efficient markets hypothesis; big data
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Funders: James Cook University
Date Deposited: 18 Jul 2018 01:12
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0899 Other Information and Computing Sciences > 089999 Information and Computing Sciences not elsewhere classified @ 90%
14 ECONOMICS > 1499 Other Economics > 149903 Heterodox Economics @ 10%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890202 Application Tools and System Utilities @ 80%
89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890205 Information Processing Services (incl. Data Entry and Capture) @ 20%
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