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Assisting investors with collective intelligence

Published:01 October 2018Publication History

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ABSTRACT

There is a growing interest in exploring and developing a new generation of financial services where automated advices generated by computers are offered to individuals, thereby helping them manage their investment portfolios in a way that is best suited for them without costly human expert involvement. In this paper, we describe the development of such a system. Our approach is based on a form of exploratory computing and generates some collective intelligence that investors may use to make informed investment and wealth management decisions.

References

  1. Financial Services Authority. 2013. Retail Distribution Review. http://www.fsa.gov.uk/about/what/rdr Accessed: 2018-07-30.Google ScholarGoogle Scholar
  2. M. Buoncristiano, G. Mecca, E. Quintarelli, M. Roveri, D. Santoro, and L. Tanca. {n. d.}. Database Challenges for Exploratory Computing. 44, 2 ({n. d.}). Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. S-H. Chun and S. H. Kim. 2004. Data Mining for Financial Prediction and Trading: Application to Single and Multiple Markets. Expert Systems with Applications 26 (2004), 131--139.Google ScholarGoogle ScholarCross RefCross Ref
  4. A. Felferni and A. Kiener. 2005. Knowledge-based Interactive Selling of Financial Services with FSAdvisor. In Proceedings of 17th Innovative Applications of Artificial Intelligence Conference (IAAI'05). Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. K. S. Kannan, P. S. Sekar, M. M. Sathik, and P. Arumugam. 2010. Financial Stock Market Forecast using Data Mining Techniques. In Proceedings of the International MultiConference of Engineers and Computer Scientists (IMECS 2010).Google ScholarGoogle Scholar
  6. K. Phoon and F. Koh. 2017. Robo-Advisors and Wealth Management. The Journal of Alternative Investments 20, 3 (2017), 79--94.Google ScholarGoogle ScholarCross RefCross Ref
  7. HM Treasury. 2014. Pension reforms: nine things you should know. https://www.gov.uk/government/news/pension-reforms-eight-things-you-should-know Accessed: 2018-07-30.Google ScholarGoogle Scholar

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  • Published in

    cover image ACM Other conferences
    DATA '18: Proceedings of the First International Conference on Data Science, E-learning and Information Systems
    October 2018
    274 pages
    ISBN:9781450365369
    DOI:10.1145/3279996

    Copyright © 2018 ACM

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 1 October 2018

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