Link lub cytat.
http://elartu.tntu.edu.ua/handle/lib/42710| Tytuł: | Specialized Information System for Support of the Process of Recruiting Securities |
| Authors: | Dubyniak, Taras Manziy, Oleksandra Gancarczyk, Tomasz Senyk, Andriy Futryk, Yurii |
| Cytat: | Taras Dubyniak, Oleksandra Manziy, Tomasz Gancarczyk, Andriy Senyk and Yurii Futryk / Specialized Information System for Support of the Process of Recruiting Securities // CITI’2023: 1st International Workshop on Computer Information Technologies in Industry 4.0, June 14–16, 2023, Ternopil, Ukraine – P. 117-125. |
| Data wydania: | 16-cze-2023 |
| Data archiwizacji: | 16-cze-2023 |
| Date of entry: | 8-lis-2023 |
| Wydawca: | ТНТУ ім. І. Пулюя |
| Kraj (kod): | UA |
| Place edycja: | ТНТУ ім. І. Пулюя |
| Słowa kluczowe: | Information and communication technologies, mathematical methods visualization risk data science Python |
| Zakres stron: | 117-125 |
| Abstract: | The development technologies and functional capabilities of the information system created by the authors aimed at decision-making support of the formation of a set of securities, which enables potential investors with little experience to assess independently the effectiveness of the investment portfolio by simulating the dynamics growth of assets available on the financial market are described. The proposed information system uses visualization methods that present available tabular information in the structured form of schemes, graphs, and charts. The web-oriented solution provides an opportunity to analyze and forecast portfolios in real time based on the available types of shares of various companies. |
| Opis: | 1. Introduction |
| Content: | 1. Introduction 2. Analysis of available researches 3. Description of the created information system 4. Overview of the results of the information system operation 5. Conclusion 6. References |
| URI: | http://elartu.tntu.edu.ua/handle/lib/42710 |
| Wykaz piśmiennictwa: | [1] H. Markowitz, Portfolio selection, Journal of Finance 7(1) (1952) 77–91, https://doi.org/10.1111/j.1540-6261.1952.tb01525.x [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] J. Lu, D. RuanandG. Zhang (eds.), E-ServiceIntelligence: Methodologies, TechnologiesandApplications (Springe [4] 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, https://doi.org/10.1145/3345252.3345254. [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, https://doi.org/10.3390/app10020437. [6] Kalnyi, S. V. and Vysotskyi, V. A. (2019), “Management formation of investment portfolio enterprises in Ukraine”, Efektyvna ekonomika, [Online], vol. 3, available at: http://www.economy.nayka.com.ua/?op=1&z=6953. https://doi:10.32702/2307-2105- 2019.3.39 [7] Medynska, Tetyana V., Rushchyshyn, Nadiia M., and Nikonenko, Uliana M. (2020) “Tax Regulation of Investment Activity of Ukrainian Banks.”, Business Inform 11:316–324. https://doi.org/10.32983/2222-4459-2020-11-316-324 [8] M. García-Galicia, A. A. Carsteanu and J. B. Clempner, Continuous-time mean varianceportfolio with transaction costs: A proximal approach involving time penalization,International Journal of General Systems 48(2) (2019) 91–111, https://doi: 10.1080/03081079.2018. 1522306. [9] X. Huang and X. Wang, Portfolio investment with options based on uncertainty theory,International Journal of Information Technology & Decision Making 18 (2019) 929- 952,https://doi.org/10.1142/S0219622019500159. [10] 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, https://doi.org/10.1007/s10287-020-00373-6. [11] 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/S0377221718306933. [12] A. Rutkowska and M. Bartkowiak, Exertion approach to vague information in portfolioselection 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. [13] F. Wen, L. Xu, G. Ouyang and G. Kou, Retail investor attention and stock price crashrisk: Evidence from China, Journal of International Review of Financial Analysis 65(2019) 1–15, https://doi.org/10.1016/j.irfa.2019.101376. [14] 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, https://doi.org/10.1186/s40854-021-00256-y. [15] Wes McKinney. Python for Data Analysis / Wes McKinney, Julie Steele and Meghan Blanchette. – United States of America: O’Reilly, 2018. – 470 с. [16] 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 [17] YaroshkoS., ManziyO. Financial mathematics. Part 1.Lviv, ZUKC Publishing House, 2021. - 209 p. [18] 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 |
| Typ zawartości: | Article |
| Występuje w kolekcjach: | Наукові публікації працівників кафедри приладів і контрольно-вимірювальних систем |
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