Creation of an information system for investment portfolio analysis

  • 1 Lviv Polytechnic National University, Lviv, Ukraine


The issue of decision-making on the formation and optimization of the investment portfolio is in the field of attention of both large investment companies and private investors. In the presented work the developed information system for investment portfolio analysis is offered. The proposed information system focused to new private investor and allows to independently assess the effectiveness of the investment portfolio by comparing the dynamics of growth of shares available on the financial market.



  1. H. Markowitz, Portfolio selection, Journal of Finance 7(1) (1952) 77–91,
  2. Kuzmin O., Alekseev I., Kolisnyk M. Problems of financial and credit regulation of innovative development of production and economic structures: monograph . Lviv Polytechnic National University Publishing House, 2007. - 152 p.
  3. T. Stoilov, How to integrate complex optimal data processing in information services ininternet, in Proc. 20th Int. Conf. Computer Systems and Technologies, ACM DigitalLibrary, 2019, pp. 19–30,
  4. Kalnyi, S. V. and Vysotskyi, V. A. (2019), “Management formation of investment portfolio enterprises in Ukraine”,Efektyvna ekonomika, [Online], vol. 3, available at: 2702/2307-2105-2019.3.39
  5. V. D. Ta, C. M. Liu and D. A. Tadesse, Portfolio optimization-based stock predictionusing long-short term memory network in quantitative trading, Applied Sciences 10(2020) 437,
  6. X. Huang and X. Wang, Portfolio investment with options based on uncertainty theory,International Journal of Information Technology & Decision Making 18 (2019) 929- 952,
  7. E. Allaj, The Black–Litterman model and views from a reverse optimization procedure:An out-of-sample performance evaluation, Computational Management Science 17(2020) 465–492,
  8. A. Palczewski and J. Palczewski, Black–Litterman model for continuous distributions,European Journal of Operational Research 273(2) (2019) 708–720, https://doi:10.1016/j.ejor.2018.08.013, https://www.sciencedirect.comscience/article/pii/S03772217183069 33.
  9. A. Rutkowska and M. Bartkowiak, Exertion approach to vague information in portfolio selection problem with many views, 2019 Conf. Int. Fuzzy Systems Association and theEuropean Society for Fuzzy Logic and Technology (EUSFLAT 2019) (Atlantis Press,Paris, France, 2019), pp. 142–149, https://www.atlantis-press.comproceedings/eus°at-19/125914792.
  10. G. Kou, Ö. Akdeniz, H. Dinçer and S. Yüksel, Fintech investments in European banks: Ahybrid IT2 fuzzy multidimensional decision-making approach, Journal of Financial Innovation 7(39) (2021) 1–28, 00256-y.
  11. Jake VanderPlas. Python Data Science Handbook. Essential Tools for Working with Data / Jake VanderPlas. – United States of America: O’Reilly Media, Inc., 1005. Gravenstein Highway North, Sebastopol, CA 95472., 2017. – 548 с
  12. Dickey, D. A.; Fuller, W. A. (1979).Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association 74 (366): 427–431. JSTOR2286348.https://doi:10.1080/01621459.1979.10482531

Article full text

Download PDF