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Do Stock Analysts Make Good Recommendations: A Unified System for Analysts’ Performance Tracking and Ranking

  • Conference paper
  • First Online:
Information Search, Integration, and Personalization (ISIP 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 421))

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Abstract

Stock analyst’s report is among of several important information sources for making investment decisions, as it contains relevant information about stocks as well as recommendation where investors should buy or sell the stock together with entry and exit strategies. Good analysts should often make trustworthy recommendations so that traders following them can make regularly profits from their advices. Nevertheless, identifying good analysts is not a trivial task especially when processed manually. Particularly, one has to collect and extract strategies from unstructured texts appearing in analyst reports, backtest such strategies with historical market data, and summarize backtested results by overall profits and losses. To address these problems, we propose a unified system which makes use of a combination of information integration and computational finance techniques to automate all these tasks. Our system performs considerably well in extracting recommendations from various analysts’ reports and provides new valuable information to traders. The system has been made available online as a mobile application for community use.

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Notes

  1. 1.

    Fundamental recommendations generally contain only rating information and earning estimates while technical recommendations also contain entry price, target price and stop-loss price as well as support and resistant levels.

  2. 2.

    The synonym list created by a system administrator is composed of price types and their alias names. For example, the reference price has “ref.price”, “close price” as its aliases.

  3. 3.

    This paper sets commission at 0.17 % of total transaction cost for all simulations.

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Author information

Authors and Affiliations

  1. National Electronics and Computer Technology Center, 112 Thailand Science Park, Phahonyothin Rd., Klong Luang, Pathumthani, 12120, Thailand

    Chaiyakorn Yingsaeree, Anon Plangprasopchok, Paramet Tanwanont & Rattapoom Tuchinda

Authors
  1. Chaiyakorn Yingsaeree
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  2. Anon Plangprasopchok
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  3. Paramet Tanwanont
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  4. Rattapoom Tuchinda
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Corresponding author

Correspondence to Anon Plangprasopchok .

Editor information

Editors and Affiliations

  1. Kasetsart University, Bangkok, Thailand

    Asanee Kawtrakul

  2. Université de Cergy Pontoise, Cergy-Pontoise, France

    Dominique Laurent

  3. University of Paris South, Orsay, France

    Nicolas Spyratos

  4. Hokkaido University, Sapporo, Japan

    Yuzuru Tanaka

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© 2014 Springer International Publishing Switzerland

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Yingsaeree, C., Plangprasopchok, A., Tanwanont, P., Tuchinda, R. (2014). Do Stock Analysts Make Good Recommendations: A Unified System for Analysts’ Performance Tracking and Ranking. In: Kawtrakul, A., Laurent, D., Spyratos, N., Tanaka, Y. (eds) Information Search, Integration, and Personalization. ISIP 2013. Communications in Computer and Information Science, vol 421. Springer, Cham. https://doi.org/10.1007/978-3-319-08732-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-08732-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08731-3

  • Online ISBN: 978-3-319-08732-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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