ISMIS 2017
mBank logo PW logo Tipranks logo

ISMIS 2017 Data Mining Competition is a challenge organized using the KnowledgePit platform at the 23rd International Symposium on Methodologies and Intelligent Systems, held at Warsaw University of Technology, Poland, on June 26-29, 2017. The task is to come up with a strategy for investing in a stock market based on recommendations provided by different experts. The competition is kindly sponsored by mBank S.A. and Tipranks, with a support from ISMIS 2017 organizers.

Topic outline

  • Topic outline: Financial markets prediction is not an easy task. Plenty of researchers and practitioners have committed a lot of their time and effort trying to come up with a method that would persistently provide profits for investors. Many of them claim that they succeeded and publish their recommendations for different types of assets. The main goal of this competition is to determine whether such recommendations do have a predictive power. We will narrow the problem to the selected number of stocks and analysts. The task is to devise an algorithm that would most accurately predict the class of return from an investment in a stock over the next quarter, basing on historical recommendations related to a particular stock. Here classification seems adequate as we claim that being able to predict whether the return will be positive or negative is a much more appropriate (and perhaps easier) task than trying to guess an exact value.

    More details regarding the task and a description of the competition data can be found in the Data description section.

    Special Session at ISMIS 2017: A special session devoted to the competition will be held at the conference. We will invite authors of selected reports to extend and submit them for further reviewing process, conducted in the same way as for other special sessions at ISMIS 2017. The invited teams will be chosen based on their final rank, innovativeness of their approach and quality of the submitted reports. The accepted papers - depending on their scope and the reviewing results - will be included in the main ISMIS 2017 proceedings or in the Industrial Session proceedings.

    Special Session & Competition Committee:

    • Andrzej Janusz, University of Warsaw - Chair
    • Kamil Żbikowski, Warsaw University of Technology & mBank S.A. - Chair
    • Piotr Gawrysiak, Warsaw University of Technology & mBank S.A.
    • Marzena Kryszkiewicz, Warsaw University of Technology
    • Henryk Rybiński, Warsaw University of Technology
    • Dominik Ślęzak, University of Warsaw & Infobright

    Awards: The teams of the first two top-ranked solutions (based on the final evaluation scores, taking into account solutions satisfying terms and conditions of ISMIS 2017 Data Mining Competition) will be awarded prizes funded by our sponsors:

    • First Prize: 1000 USD + one free ISMIS 2017 conference registration,
    • Second Prize: 500 USD + one free ISMIS 2017 conference registration.

    The award ceremony will take place during the ISMIS 2017 conference (June 26-29, 2017, Warsaw, Poland).

    Schedule:

    • November 22, 2016: start of the competition; data sets become available,
    • January 22, 2017 (23:59 GMT): deadline for submitting the predictions and the reports (the deadline for submitting reports has been extended until January 27),
    • January 29 February 1, 2017: end of the challenge, on-line publication of final results, sending invitations for submitting papers for the special session at ISMIS 2017,
    • late February 2017: deadline for submitting papers describing the selected solutions to the special session at ISMIS 2017.

    In case of any questions please post on the competition forum or write us an email at ismis2017-competition@ii.pw.edu.pl

  • This topic

    Summary

    Summary and information about the final results.

  • Competition rules and data

    Below is a link to Terms and Conditions of the competition. They MUST be read and accepted in order to enroll.

  • Leaderboard

    Here you can follow preliminary results of other participants of the competition. The score of your best solution will be visible here.