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International Workshop on Enterprise Applications, Markets and Services in the Finance Industry

FinanceCom 2018: Enterprise Applications, Markets and Services in the Finance Industry pp 101–117Cite as

Using NSIA Framework to Evaluate Impact of Sentiment Datasets on Intraday Financial Market Measures: A Case Study

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 345))

Abstract

Current studies on financial markets reaction to news show lack of flexibility for conducting news sentiment datasets evaluations. In other words, there is an absence of clear step-by-step guidance for conducting impact analysis studies in various financial contexts. This paper evaluates the proposed News Sentiment Impact Analysis (NSIA) framework using a highly sensitive financial market measure called the intraday mean cumulative average abnormal returns. The results demonstrate the ability of the framework to evaluate news sentiment impact on high frequency financial data (minutes intervals), while defining clear steps to conduct a systematic evaluation.

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Acknowledgments

We are grateful to Sirca [43] and Thomson Reuters [33] for providing access to the data used in this research.

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Authors and Affiliations

  1. School of Computer Science and Engineering, University of New South Wales, Sydney, 2052, Australia

    Islam Al Qudah & Fethi A. Rabhi

Authors
  1. Islam Al Qudah
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  2. Fethi A. Rabhi
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Corresponding author

Correspondence to Islam Al Qudah .

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Editors and Affiliations

  1. Alliance Manchester Business School, Manchester, UK

    Nikolay Mehandjiev

  2. Alliance Manchester Business School, Manchester, UK

    Brahim Saadouni

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Qudah, I.A., Rabhi, F.A. (2019). Using NSIA Framework to Evaluate Impact of Sentiment Datasets on Intraday Financial Market Measures: A Case Study. In: Mehandjiev, N., Saadouni, B. (eds) Enterprise Applications, Markets and Services in the Finance Industry. FinanceCom 2018. Lecture Notes in Business Information Processing, vol 345. Springer, Cham. https://doi.org/10.1007/978-3-030-19037-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-19037-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19036-1

  • Online ISBN: 978-3-030-19037-8

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