IDEAS home Printed from https://ideas.repec.org/h/bis/bisifc/64-29.html

Constructing high-frequency and thematic economic sentiment indicators from online news articles: applications in the Philippine context

In: Data science in central banking: enhancing the access to and sharing of data

Author

Listed:
  • Alan Chester Arcin
  • Carmelita Esclanda-Lo
  • Chelsea Anne Ong
  • Rossvern Reyes

Abstract

No abstract is available for this item.

Suggested Citation

  • Alan Chester Arcin & Carmelita Esclanda-Lo & Chelsea Anne Ong & Rossvern Reyes, 2025. "Constructing high-frequency and thematic economic sentiment indicators from online news articles: applications in the Philippine context," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Data science in central banking: enhancing the access to and sharing of data, volume 64, Bank for International Settlements.
    • Handle: RePEc:bis:bisifc:64-29
    as

    Download full text from publisher

    File URL: https://www.bis.org/ifc/publ/ifcb64_29.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David M. Blei & Alp Kucukelbir & Jon D. McAuliffe, 2017. "Variational Inference: A Review for Statisticians," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 859-877, April.
    2. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    3. Kanzari, Dalel & Nakhli, Mohamed Sahbi & Gaies, Brahim & Sahut, Jean-Michel, 2023. "Predicting macro-financial instability – How relevant is sentiment? Evidence from long short-term memory networks," Research in International Business and Finance, Elsevier, vol. 65(C).
    4. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Irving Fisher Committee, 2025. "Data science in central banking: enhancing the access to and sharing of data," IFC Bulletins, Bank for International Settlements, number 64.
    2. Müller, Karsten, 2020. "German forecasters' narratives: How informative are German business cycle forecast reports?," Working Papers 23, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    3. David M. Arseneau & Alejandro Drexler & Mitsuhiro Osada, 2022. "Central Bank Communication about Climate Change," Finance and Economics Discussion Series 2022-031, Board of Governors of the Federal Reserve System (U.S.).
    4. Kirtac, Kemal & Germano, Guido, 2024. "Sentiment trading with large language models," Finance Research Letters, Elsevier, vol. 62(PB).
    5. Leilane de Freitas Rocha Cambara & Roberto Meurer, 2023. "News sentiment and foreign portfolio investment in Brazil," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3332-3348, July.
    6. Tarek A Hassan & Stephan Hollander & Laurence van Lent & Ahmed Tahoun, 2019. "Firm-Level Political Risk: Measurement and Effects," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(4), pages 2135-2202.
    7. Budras, Oliver & Dierkes, Maik & Schroen, Sebastian, 2026. "Text-implied uncertainty in 10-K filings: Do investors get the message?," The Quarterly Review of Economics and Finance, Elsevier, vol. 106(C).
    8. Himounet, Nicolas, 2022. "Searching the nature of uncertainty: Macroeconomic and financial risks VS geopolitical and pandemic risks," International Economics, Elsevier, vol. 170(C), pages 1-31.
    9. Tim Bollerslev & Jia Li & Yuan Xue, 2018. "Volume, Volatility, and Public News Announcements," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(4), pages 2005-2041.
    10. Dim, Chukwuma & Koerner, Kevin & Wolski, Marcin & Zwart, Sanne, 2022. "Hot off the press: News-implied sovereign default risk," EIB Working Papers 2022/06, European Investment Bank (EIB).
    11. Slonimczyk, Fabian, 2025. "This Candidate is [MASK]. Prompt-based Sentiment Extraction and Reference Letters," MPRA Paper 126675, University Library of Munich, Germany.
    12. Luca Barbaglia & Sergio Consoli & Sebastiano Manzan, 2024. "Forecasting GDP in Europe with textual data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 338-355, March.
    13. Di (Andrew) Wu, 2024. "Text-Based Measure of Supply Chain Risk Exposure," Management Science, INFORMS, vol. 70(7), pages 4781-4801, July.
    14. Ming Gu & David Hirshleifer & Siew Hong Teoh & Shijia Wu, 2025. "GIFfluence: A Visual Approach to Investor Sentiment and the Stock Market," Papers 2512.20027, arXiv.org.
    15. John Garcia, 2024. "Herding the crowds: how sentiment affects crowdsourced earnings estimates," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 38(3), pages 331-370, September.
    16. Necmettin Alpay Koçak, 2020. "The Role of Ecb Speeches in Nowcasting German Gdp," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2020(2), pages 05-20.
    17. Murad, S.M. Woahid & Pathan, Shams & Durand, Robert B. & Zheng, Chen, 2025. "Understanding Bank-Level Uncertainty: New insights into banking activity and its macroeconomic impacts," International Review of Economics & Finance, Elsevier, vol. 102(C).
    18. Yuting Chen & Don Bredin & Valerio Potì & Roman Matkovskyy, 2022. "COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic," Digital Finance, Springer, vol. 4(1), pages 17-61, March.
    19. John Garcia, 2021. "Analyst herding and firm-level investor sentiment," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(4), pages 461-494, December.
    20. Youngjoon Lee & Soohyon Kim & Ki Young Park, 2018. "Deciphering Monetary Policy Committee Minutes with Text Mining Approach: A Case of South Korea," Working papers 2018rwp-132, Yonsei University, Yonsei Economics Research Institute.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bis:bisifc:64-29. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Martin Fessler (email available below). General contact details of provider: https://edirc.repec.org/data/bisssch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.