Agent-based computational investing recommender system

Mona Taghavi, Kaveh Bakhtiyari, Edgar Scavino

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    10 Citations (Scopus)

    Abstract

    The fast development of computing and communication has reformed the financial markets' dynamics. Nowadays many people are investing and trading stocks through online channels and having access to real-time market information efficiently. There are more opportunities to lose or make money with all the stocks information available throughout the World; however, one should spend a lot of effort and time to follow those stocks and the available instant information. This paper presents a preliminary regarding a multi-agent recommender system for computational investing. This system utilizes a hybrid filtering technique to adaptively recommend the most profitable stocks at the right time according to investor's personal favour. The hybrid technique includes collaborative and content-based filtering. The content-based model uses investor preferences, influencing macro-economic factors, stocks profiles and the predicted trend to tailor to its advices. The collaborative filter assesses the investor pairs' investing behaviours and actions that are proficient in economic market to recommend the similar ones to the target investor.

    Original languageEnglish
    Title of host publicationRecSys 2013 - Proceedings of the 7th ACM Conference on Recommender Systems
    Pages455-458
    Number of pages4
    DOIs
    Publication statusPublished - 2013
    Event7th ACM Conference on Recommender Systems, RecSys 2013 - Hong Kong
    Duration: 12 Oct 201316 Oct 2013

    Other

    Other7th ACM Conference on Recommender Systems, RecSys 2013
    CityHong Kong
    Period12/10/1316/10/13

    Fingerprint

    Recommender systems
    Economics
    Macros
    Communication
    Financial markets

    Keywords

    • Computational investing
    • Hybrid filtering
    • Multi-agent system
    • Recommender system
    • Stock market

    ASJC Scopus subject areas

    • Software

    Cite this

    Taghavi, M., Bakhtiyari, K., & Scavino, E. (2013). Agent-based computational investing recommender system. In RecSys 2013 - Proceedings of the 7th ACM Conference on Recommender Systems (pp. 455-458) https://doi.org/10.1145/2507157.2508072

    Agent-based computational investing recommender system. / Taghavi, Mona; Bakhtiyari, Kaveh; Scavino, Edgar.

    RecSys 2013 - Proceedings of the 7th ACM Conference on Recommender Systems. 2013. p. 455-458.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Taghavi, M, Bakhtiyari, K & Scavino, E 2013, Agent-based computational investing recommender system. in RecSys 2013 - Proceedings of the 7th ACM Conference on Recommender Systems. pp. 455-458, 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, 12/10/13. https://doi.org/10.1145/2507157.2508072
    Taghavi M, Bakhtiyari K, Scavino E. Agent-based computational investing recommender system. In RecSys 2013 - Proceedings of the 7th ACM Conference on Recommender Systems. 2013. p. 455-458 https://doi.org/10.1145/2507157.2508072
    Taghavi, Mona ; Bakhtiyari, Kaveh ; Scavino, Edgar. / Agent-based computational investing recommender system. RecSys 2013 - Proceedings of the 7th ACM Conference on Recommender Systems. 2013. pp. 455-458
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