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Dynamic Bayesian Networks Application for Evaluating the Investment Projects Effectiveness

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Lecture Notes in Computational Intelligence and Decision Making (ISDMCI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1246))

Abstract

In this paper, we propose a methodology for using dynamic Bayesian networks (DBN) in the tasks of assessing the success of an investment project. The methods of constructing DBN, their parametric learning, validation and scenario analysis of “What-if” are considered. A dynamic Bayesian model has been developed for scenario analysis and forecasting the success of an investment project. The model takes into account the time component and is designed in collaboration with expert economists in the selection and quantification of input and output variables. Now, using the dynamic Bayesian model, it is possible with a certain degree of probability to assess the degree of success of the capital investment, without incurring monetary and temporary losses. This will greatly facilitate the investment forecast for identifying profitable investment sources. This is the advantage of the proposed approach.

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Author information

Authors and Affiliations

  1. Department of Informatics and Computing Technology, Kherson National Technical University, Kherson, Ukraine

    Volodymyr Lytvynenko & Mariia Voronenko

  2. University of State Fiscal Service of Ukraine, Irpin, Ukraine

    Oleksandr Naumov & Larisa Naumova

  3. Jan Evangelista Purkyne University in Usti nad Labem, Ústí nad Labem, Czech Republic

    Jan Krejci

  4. National University of Water and Environmental Engineering, Rivne, Ukraine

    Dmytro Nikytenko & Nataliia Savina

Authors
  1. Volodymyr Lytvynenko
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  2. Oleksandr Naumov
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  3. Mariia Voronenko
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  4. Jan Krejci
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  5. Larisa Naumova
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  6. Dmytro Nikytenko
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  7. Nataliia Savina
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Corresponding author

Correspondence to Volodymyr Lytvynenko .

Editor information

Editors and Affiliations

  1. Department of Informatics, Jan Evangelista Purkyně University in Ústí nad Labem, Ústí nad Labem, Czech Republic

    Sergii Babichev

  2. Department of Informatics and Computer Science, Kherson National Technical University, Kherson, Ukraine

    Volodymyr Lytvynenko

  3. Institute of Electronics and Information, Lublin University of Technology, Lublin, Poland

    Waldemar Wójcik

  4. Department of Informatics and Computer Science, Kherson National Technical University, Kherson, Ukraine

    Svetlana Vyshemyrskaya

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Lytvynenko, V. et al. (2021). Dynamic Bayesian Networks Application for Evaluating the Investment Projects Effectiveness. In: Babichev, S., Lytvynenko, V., Wójcik, W., Vyshemyrskaya, S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2020. Advances in Intelligent Systems and Computing, vol 1246. Springer, Cham. https://doi.org/10.1007/978-3-030-54215-3_20

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