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Cognitive User Interface for Portfolio Optimization

Author

Listed:
  • Yuehuan He

    (Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada)

  • Oleksandr Romanko

    (Algorithmics, SS&C Technologies, 185 Spadina Ave, Toronto, ON M5T 2C6, Canada)

  • Alina Sienkiewicz

    (Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada)

  • Robert Seidman

    (Algorithmics, SS&C Technologies, 185 Spadina Ave, Toronto, ON M5T 2C6, Canada)

  • Roy Kwon

    (Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada)

Abstract

This paper describes the development of a chatbot as a cognitive user interface for portfolio optimization. The financial portfolio optimization chatbot is proposed to provide an easy-to-use interface for portfolio optimization, including a wide range of investment objectives and flexibility to include a variety of constraints representing investment preferences when compared to existing online automated portfolio advisory services. Additionally, the use of a chatbot interface allows investors lacking a background in quantitative finance and optimization to utilize optimization services. The chatbot is capable of extracting investment preferences from natural text inputs, handling these inputs with a backend financial optimization solver, analyzing the results, and communicating the characteristics of the optimized portfolio back to the user. The architecture and design of the chatbot are presented, along with an implementation using the IBM Cloud, SS&C Algorithmics Portfolio Optimizer, and Slack as an example of this approach. The design and implementation using cloud applications provides scalability, potential performance improvements, and could inspire future applications for financial optimization services.

Suggested Citation

  • Yuehuan He & Oleksandr Romanko & Alina Sienkiewicz & Robert Seidman & Roy Kwon, 2021. "Cognitive User Interface for Portfolio Optimization," JRFM, MDPI, vol. 14(4), pages 1-15, April.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:4:p:180-:d:535829
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    References listed on IDEAS

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    5. Oleksandr Romanko & Helmut Mausser, 2016. "Robust scenario-based value-at-risk optimization," Annals of Operations Research, Springer, vol. 237(1), pages 203-218, February.
    6. Oleksandr Romanko & Helmut Mausser, 2016. "Robust scenario-based value-at-risk optimization," Annals of Operations Research, Springer, vol. 237(1), pages 203-218, February.
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