A Fuzzy-Based Recommender System: Case Börsenspiel for Swiss Universities

  • José ManceraEmail author
  • Minh Tue Nguyen
  • Edy Portmann
Part of the Fuzzy Management Methods book series (FMM)


This case study introduces a new investment technique approach to make investment decisions in the stock market with minimum risk and reduced potential human intuition bias. The document introduces a fuzzy recommender system (FRS) and discusses its impact in generating positive revenue compared with decisions of real investors. The theoretical background, design and implementation of the FRS in a stock exchange platform are properly presented. The performance is evaluated with respect to the strategies used by real investors in weekly investment rounds, considering three different investment scenarios: conservative, explorer and adventurer. Finally, a proper discussion about the results of the investment via the stock exchange platform, where the FRS performed in the top three of the list of best investors during the evaluation period and improvement opportunity areas is presented.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of InformaticsUniversity of FribourgFribourgSwitzerland
  2. 2.Human-IST InstituteUniversity of FribourgFribourgSwitzerland

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