Skip to main content

Development of Software Architecture and Machine Learning Modules of Robo-Advisor System for Personalized Investment Portfolio Generation

  • Conference paper
  • First Online:
Information and Communication Technologies in Education, Research, and Industrial Applications (ICTERI 2021)

Abstract

We researched how to use financial technology in the finance industry on the example of robo-advisors; defined the basic functionality of a robo-advisor; got the robo-advisors implementation based on analysis of the most popular financial services. We compared their functions, composed a list of critical features and described the high-level architectural design of a general robo-advisor tool, scope of using robo-advisors, their key features, and a brief overview of existing solutions. Using Markowitz model, we set up a concept of using a robo-advisor by investors who have different attitudes towards risks. Our goal is to cover the main features of financial robo-advisor and to describe a high-level architecture for such applications using prediction of financial instruments rates to rebalance investment portfolio. We have defined the main modules that represent the architecture of a typical robo-advisor. We also described different techniques, which could be applied building a personalized investment portfolio. We considered ARIMA models to predict stock prices. The experimental part demonstrates how to use LSTM neural networks and multiple linear regression techniques in the scope of the Robo-Advisor profitability-forecasting module.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. J.W., Lam.: Robo-Advisors: a portfolio management perspective. Yale College. New Haven, Connecticut (2016)

    Google Scholar 

  2. Waliszewski, K., Warchlewska, A.: Financial Technologies in personal financial planning: robo-advice vs. human-advice, Ruch Prawniczy, Ekonomiczny i Socjologiczny 4, 303 – 317 (2020). https://doi.org/10.14746/rpeis.2020.82.4.22.

  3. Maedche, A., Morana, S., Schacht, S., Werth, D., Krumeich, J.: Advanced user assistance systems. Bus. Inf. Syst. Eng. 58(5), 367–370 (2016). https://doi.org/10.1007/s12599-016-0444-2

    Article  Google Scholar 

  4. Fein, M.L.: Robo-advisors: a closer look. SSRN Electron. J. (2015). https://doi.org/10.2139/ssrn.2658701

    Article  Google Scholar 

  5. Dorfleitner, G., Hornuf, L., Schmitt, M., Weber, M.: Definition of FinTech and description of the FinTech industry. In: FinTech in Germany. Springer, Cham, pp. 5–10 (2017). https://doi.org/10.1007/978-3-319-54666-7_2.

  6. Semenog, A.Y., Kryvych, Y.M., Tsyrulyk, S.V.: Fintech services: essence, role and value for the economy of the country. Odessa Nat. Univ. Herald. Econ. 2(67), 100–105 (2018)

    Google Scholar 

  7. Narayanan, A.: As robo advisors go viral, where do traditional money managers go? (2016). https://www.investors.com/etfs-and-funds/etfs/fund-industry-wakens-from-slumber-to-take-on-digital-advice-upstarts/

  8. The Basel committee on banking supervision, consultative document, sound practices: implications of Fintech developments for banks and bank supervisors / bank for international settlements (2017). https://www.bis.org/bcbs/publ/d415.pdf

  9. Waliszewski, K., Zięba-Szklarska, M.: Robo-advisors as automated personal financial planners – SWOT analysis. J. Finan. Fin. Law 3(27), 155–173 (2020). https://doi.org/10.18778/2391-6478.3.27.09

    Article  Google Scholar 

  10. Ivanov, O., Snihovyi, O., Kobets, V.: Implementation of robo-advisors tools for different risk attitude investment decisions. In: Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, ICTERI 2018, CEUR-WS, vol. 2104, pp. 195–206. Kyiv Ukraine (2018). http://ceur-ws.org/Vol-2104/paper_161.pdf

  11. Kobets, V., Yatsenko, V., Mazur, A., Zubrii, M.: Data analysis of private investment decision making using tools of Robo-advisers in long-run period. In: Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, ICTERI 2018, CEUR-WS, vol. 2104, pp. 144–159.Kyiv Ukraine (2018). http://ceur-ws.org/Vol-2104/paper_162.pdf

  12. Marquit, M., Curry, B.: How to invest with a robo-advisor (2021). https://www.forbes.com/advisor/investing/what-is-robo-advisor/

  13. Ernst and Young, EY FinTech Adoption Index 2017 (2017). https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/banking-and-capital-markets/ey-fintech-adoption-index-2017.pdf?download

  14. Annaert, J., Osselaer, S.V., Verstraete, B.: Performance evaluation of portfolio insurance strategies using stochastic dominance criteria. J. Bank. Finan. 33, 272–280 (2009). https://doi.org/10.1016/j.jbankfin.2008.08.002

    Article  Google Scholar 

  15. Stoeckli, E., Dremel, C., Uebernickel, F.: Exploring characteristics and transformational capabilities of InsurTech innovations to understand insurance value creation in a digital world. Electron. Mark. 28(3), 287–305 (2018). https://doi.org/10.1007/s12525-018-0304-7

    Article  Google Scholar 

  16. Snihovyi, O., Kobets, V., Ivanov, O.: Implementation of Robo-Advisor Services for Different Risk Attitude Investment Decisions Using Machine Learning Techniques. In: Ermolayev, V., Suárez-Figueroa, M.C., Yakovyna, V., Mayr, H.C., Nikitchenko, M., Spivakovsky, A. (eds.) ICTERI 2018. CCIS, vol. 1007, pp. 298–321. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-13929-2_15

    Chapter  Google Scholar 

  17. Snihovyi, O., Ivanov, O., Kobets, V.: Implementation of robo-advisors using neural networks for different risk attitude investment decisions. In: Proceedings of the 9th International Conference on Intelligent Systems, IS 2018, vol. 8710559, pp. 332–336. IEEE, Fun-chal Portugal (2018). https://doi.org/10.1109/IS.2018.8710559

  18. Kobets, V.M., Yatsenko, V.O., Mazur, A., Zubrii, M.I.: Data analysis of personalized investment decision making using robo-advisers. Sci. Innov. 16(2), 80–93 (2020). https://doi.org/10.15407/scin16.02.087

    Article  Google Scholar 

  19. Baek, S., Lee, K.Y., Uctum, M., Oh, S.H.: Robo-advisors: machine learning in trend-following ETF investments. Sustainability 12(16), 6399 (2020). https://doi.org/10.3390/su12166399

    Article  Google Scholar 

  20. Kilinich, D., Kobets, V.: Support of investors’ decision making in economic experiments using software tools. In: Proceedings of the 15th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, ICTERI 2019, CEUR-WS, vol. 2393, pp. 277–288. Kherson Ukraine (2019). http://ceur-ws.org/Vol-2393/paper_273.pdf

  21. Snihovyi, O.S.: Application of machine learning algorithms for forecasting the course of financial instruments under development of individual investment plans, Master’s thesis, Kherson State University (KSU), Kherson, Ukraine (2018)

    Google Scholar 

  22. Saad, L.: Robo-advice still a novelty for U.S. Investors (2016) https://news.gallup.com/poll/193997/robo-advice-novelty-investors.aspx

  23. Anderson, T.: More robo-advisors are adding a human touch to their services (2017). https://www.cnbc.com/2017/01/31/more-robo-advisors-are-adding-that-human-touch.html

  24. Mangram, M.E.: A simplified perspective of the markowitz portfolio theory. Glob. J. Bus. Res. 7(1), 59–70 (2013)

    Google Scholar 

  25. Kobets, V., Poltoratskiy, M.: Using an evolutionary algorithm to improve investment strategies for industries in an economic system. In: Proceedings of the 12th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, ICTERI 2016, CEUR-WS, vol. 1614, pp. 485–501. Kyiv Ukraine (2016). http://ceur-ws.org/Vol-1614/paper_102.pdf

  26. Geron, A.: Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: concepts, tools, and techniques to build intelligent systems, O'Reilly Media, Inc (2019)

    Google Scholar 

  27. Nelson, D., Pereira, A., Oliveira, R.A.: Stock market's price movement prediction with LSTM neural networks. In: Proceeding of 2017 International Joint Conference on Neural Networks (IJCNN), Anchorage, Alaska (2017). https://doi.org/10.1109/IJCNN.2017.7966019

  28. Download historical data in Yahoo finance. https://help.yahoo.com/kb/SLN2311.html

  29. Bhandari, H.N., Rimal, B., Pokhrel, N.R., Rimal, R., Dahal, K.R., Khatri, R.K.C.: Predicting stock market index using LSTM. Mach. Learn. Appl. 9, 2022100320. https://doi.org/10.1016/j.mlwa.2022.100320

  30. Staffini, A.: Stock price forecasting by a deep convolutional generative adversarial network. Front Artif Intell, 5 (2022) https://doi.org/10.3389/frai.2022.837596

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vitaliy Kobets .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Savchenko, S., Kobets, V. (2022). Development of Software Architecture and Machine Learning Modules of Robo-Advisor System for Personalized Investment Portfolio Generation. In: Ermolayev, V., et al. Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2021. Communications in Computer and Information Science, vol 1698. Springer, Cham. https://doi.org/10.1007/978-3-031-20834-8_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-20834-8_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20833-1

  • Online ISBN: 978-3-031-20834-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics