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Using machine learning algorithms to find patterns in stock prices


  • Nuno Garoupa


This paper analyzes the regulation of access to, and activity of, the legal and medical professions. A critical assessment is offered of the economic theory of the regulation of professions in relation to the key issues of: (a) Why regulate, (b) How to regulate, and (c) What to regulate. We suggest a set of indicators to measure the quality of regulatory restrictions, and thereby expose comparative inefficiencies, in the medical and legal professional activities. We conclude that generally speaking the USA followed by Norway, the UK [England and Wales] and Belgium perform better in terms of efficient regulation, whereas Germany, Austria and Portugal perform badly for both legal and medical professionals. Other countries (including the Netherlands, Spain, France) vary. Our results are partly, but not entirely, consistent with previous findings.

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  • Nuno Garoupa, 2006. "Using machine learning algorithms to find patterns in stock prices," Working Papers 2006-11, FEDEA.
  • Handle: RePEc:fda:fdaddt:2006-11

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