Cognitive User Interface for Portfolio Optimization

• Main Authors: Yuehuan He, Oleksandr Romanko, Alina Sienkiewicz, Robert Seidman, Roy Kwon
• Format: Article
• Language: English
• Published: MDPI AG 2021-04-01
• Series: Journal of Risk and Financial Management
• Subjects: chatbot; portfolio optimization; cognitive user interface
• Online Access: https://www.mdpi.com/1911-8074/14/4/180

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.