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Exploring the influence of industries and randomness in stock prices


This study explores the behavior of time series of historical prices and makes two additional contributions to the literature. In summarized form, we present an overview of each of the financial theories that discuss the movements of stock prices and their connection with industry trends. Within this theoretical framework, we first propose that prices be distinguished by following stock prices and a random-walk approach, and second, that the analysis of historical prices be broken down by industries. Similarities among price series are extracted through a clustering methodology based on an approach to non-computable Kolmogorov complexity. We model price series by following geometric Brownian motion and compare them to historical series of stock prices. Our first contribution confirms the existence of hidden common patterns in time series of historical prices that are clearly distinguishable from simulated series. The second contribution claims strong connections among firms carrying out similar industrial activities. The results confirm that stock prices belonging to the same industry behave similarly, whereas they behave differently from those of firms in other industries. Our research sheds new light on the stylized feature of the non-randomness of stock prices by pointing at fundamental aspects related to the industry as partial explanatory factors behind price movements.

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  1. The EMH contends that since markets are efficient and current prices fully reflect all available information, the price itself is a good estimate of the intrinsic value of the market.

  2. The spring model based on the force-directed method is an algorithms for drawing graphs in an esthetically pleasing way. The method aims to build graphs while avoiding as many crossings of edges and node overlapping as possible.


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This work was partially supported by the Spanish Government Minister of Science and Innovation under Grant TIN2014-54806-R and the People Programme (Marie Curie Actions) of the Seventh Framework Programme of the European Union (FP7/2007-2013) under REA Grant No. 600388 (TECNIOspring programme), and from the Agency for Business Competitiveness of the Government of Catalonia, ACCIÓ. J.I.Hidalgo also acknowledges the support of the Spanish Ministry of Education mobility Grant PRX16/00216.

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Correspondence to Ivan Contreras.

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Contreras, I., Hidalgo, J.I. & Nuñez, L. Exploring the influence of industries and randomness in stock prices. Empir Econ 55, 713–729 (2018).

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  • Time series
  • Stock prices
  • Information theory
  • Random walk
  • Industry analysis
  • Macroeconomic analysis
  • Clustering

JEL Classification

  • C63
  • C81