Measuring News Sentiment of Korea Using Transformer
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022.
"Machine Learning Time Series Regressions With an Application to Nowcasting,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
- Andrii Babii & Eric Ghysels & Jonas Striaukas, 2020. "Machine Learning Time Series Regressions with an Application to Nowcasting," Papers 2005.14057, arXiv.org, revised Dec 2020.
- Babii, Andrii & Ghysels, Eric & Striaukas, Jonas, 2021. "Machine Learning Time Series Regressions With an Application to Nowcasting," LIDAM Reprints LFIN 2021010, Université catholique de Louvain, Louvain Finance (LFIN).
- Babii, Andrii & Ghysels, Eric & Striaukas, Jonas, 2021. "Machine Learning Time Series Regressions With an Application to Nowcasting," LIDAM Discussion Papers LFIN 2021004, Université catholique de Louvain, Louvain Finance (LFIN).
- Robert B. Barsky & Eric R. Sims, 2012.
"Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence,"
American Economic Review, American Economic Association, vol. 102(4), pages 1343-1377, June.
- Robert B. Barsky & Eric R. Sims, 2009. "Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence," NBER Working Papers 15049, National Bureau of Economic Research, Inc.
- Bas Aarle & Marcus Kappler, 2012. "Economic sentiment shocks and fluctuations in economic activity in the euro area and the USA," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 47(1), pages 44-51, January.
- Hamza Bennani & Matthias Neuenkirch, 2017.
"The (home) bias of European central bankers: new evidence based on speeches,"
Applied Economics, Taylor & Francis Journals, vol. 49(11), pages 1114-1131, March.
- Hamza Bennani & Matthias Neuenkirch, 2014. "The (Home) Bias of European Central Bankers: New Evidence Based on Speeches," Research Papers in Economics 2014-16, University of Trier, Department of Economics.
- Hamza Bennani & Matthias Neuenkirch, 2017. "The (Home) Bias of European Central Bankers: New Evidence Based on Speeches," Post-Print hal-01589264, HAL.
- Hamza Bennani & Matthias Neuenkirch, 2016. "The (Home) Bias of European Central Bankers: New Evidence Based on Speeches ," Post-Print hal-04206062, HAL.
- 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.
- Kim Nguyen & Gianni La Cava, 2020. "Start Spreading the News: News Sentiment and Economic Activity in Australia," RBA Research Discussion Papers rdp2020-08, Reserve Bank of Australia.
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.- Jang, Tae-Seok & Sacht, Stephen, 2017. "Modeling consumer confidence and its role for expectation formation: A horse race," Economics Working Papers 2017-04, Christian-Albrechts-University of Kiel, Department of Economics.
- David Bholat & Stephen Hans & Pedro Santos & Cheryl Schonhardt-Bailey, 2015. "Text mining for central banks," Handbooks, Centre for Central Banking Studies, Bank of England, number 33, April.
- Mikael Apel & Marianna Blix Grimaldi & Isaiah Hull, 2022.
"How Much Information Do Monetary Policy Committees Disclose? Evidence from the FOMC's Minutes and Transcripts,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1459-1490, August.
- Apel, Mikael & Blix Grimaldi, Marianna & Hull, Isaiah, 2019. "How Much Information Do Monetary Policy Committees Disclose? Evidence from the FOMC's Minutes and Transcripts," Working Paper Series 381, Sveriges Riksbank (Central Bank of Sweden).
- 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.
- Johannes Zahner, 2020. "Above, but close to two percent. Evidence on the ECB’s inflation target using text mining," MAGKS Papers on Economics 202046, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
- Hanjo Odendaal & Monique Reid & Johann F. Kirsten, 2020.
"Media‐Based Sentiment Indices as an Alternative Measure of Consumer Confidence,"
South African Journal of Economics, Economic Society of South Africa, vol. 88(4), pages 409-434, December.
- Nicolaas Johannes Odendaal & Monique Reid, 2018. "Media based sentiment indices as an alternative measure of consumer confidence," Working Papers 17/2018, Stellenbosch University, Department of Economics.
- Baranowski, Paweł & Doryń, Wirginia & Łyziak, Tomasz & Stanisławska, Ewa, 2021. "Words and deeds in managing expectations: Empirical evidence from an inflation targeting economy," Economic Modelling, Elsevier, vol. 95(C), pages 49-67.
- Picault, Matthieu & Renault, Thomas, 2017.
"Words are not all created equal: A new measure of ECB communication,"
Journal of International Money and Finance, Elsevier, vol. 79(C), pages 136-156.
- Matthieu Picault & Thomas Renault, 2017. "Words are not all created equal: A new measure of ECB communication," Post-Print hal-03535202, HAL.
- Matthieu Picault & Thomas Renault, 2017. "Words are not all created equal: A new measure of ECB communication," Post-Print hal-03205121, HAL.
- Matthieu Picault & Thomas Renault, 2017. "Words are not all created equal: A new measure of ECB communication," Post-Print hal-03676646, HAL.
- Shapiro, Adam Hale & Sudhof, Moritz & Wilson, Daniel J., 2022.
"Measuring news sentiment,"
Journal of Econometrics, Elsevier, vol. 228(2), pages 221-243.
- Adam Hale Shapiro & Moritz Sudhof & Daniel J. Wilson, 2020. "Measuring News Sentiment," Working Paper Series 2017-1, Federal Reserve Bank of San Francisco.
- Bennani, Hamza, 2019.
"Does People's Bank of China communication matter? Evidence from stock market reaction,"
Emerging Markets Review, Elsevier, vol. 40(C), pages 1-1.
- Hamza Bennani, 2019. "Does People's Bank of China Communication Matter? Evidence from Stock Market Reaction," Post-Print hal-02127840, HAL.
- Bennani, Hamza, 2019. "Does People's Bank of China communication matter? Evidence from stock market reaction," BOFIT Discussion Papers 9/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
- Vegard H ghaug Larsen & Leif Anders Thorsrud, 2018.
"Business cycle narratives,"
Working Papers
No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Vegard H. Larsen & Leif Anders Thorsrud, 2019. "Business Cycle Narratives," CESifo Working Paper Series 7468, CESifo.
- Vegard H. Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Paper 2018/3, Norges Bank.
- Baranowski, Pawel & Bennani, Hamza & Doryń, Wirginia, 2021.
"Do the ECB's introductory statements help predict monetary policy? Evidence from a tone analysis,"
European Journal of Political Economy, Elsevier, vol. 66(C).
- Pawel Baranowski & Hamza Bennani & Wirginia Doryń, 2020. "Do the ECB's Introductory Statements Help Predict Monetary Policy? Evidence from a Tone Analysis ," Post-Print hal-04205988, HAL.
- Hamza Bennani & Pawel Baranowski & Wirginia Doryn, 2021. "Do the ECB's Introductory Statements Help Predict Monetary Policy? Evidence from a Tone Analysis," Post-Print hal-02957422, HAL.
- Parle, Conor, 2022.
"The financial market impact of ECB monetary policy press conferences — A text based approach,"
European Journal of Political Economy, Elsevier, vol. 74(C).
- Parle, Conor, 2021. "The financial market impact of ECB monetary policy press conferences - a text based approach," Research Technical Papers 4/RT/21, Central Bank of Ireland.
- Young Joon Lee & Soohyon Kim & Ki Young Park, 2019. "Deciphering Monetary Policy Board Minutes with Text Mining: The Case of South Korea," Korean Economic Review, Korean Economic Association, vol. 35, pages 471-511.
- Nabavi Larimi , Seyed Mohsen & Ehsani , Mohammad Ali & Tavakolian , Hossein, 2018. "Effect of Sentiments on Macroeconomic Variables in Iran: A Dynamic Stochastic General Equilibrium Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(1), pages 1-30, January.
- Martin T. Bohl & Dimitrios Kanelis & Pierre L. Siklos, 2022. "How Central Bank Mandates Influence Content and Tone of Communication Over Time," CQE Working Papers 9622, Center for Quantitative Economics (CQE), University of Muenster.
- Bohl, Martin T. & Kanelis, Dimitrios & Siklos, Pierre L., 2023. "Central bank mandates: How differences can influence the content and tone of central bank communication," Journal of International Money and Finance, Elsevier, vol. 130(C).
- Nyman, Rickard & Kapadia, Sujit & Tuckett, David, 2021.
"News and narratives in financial systems: Exploiting big data for systemic risk assessment,"
Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
- Nyman, Rickard & Kapadia, Sujit & Tuckett, David & Gregory, David & Ormerod, Paul & Smith, Robert, 2018. "News and narratives in financial systems: exploiting big data for systemic risk assessment," Bank of England working papers 704, Bank of England.
- Petar Sorić & Blanka Škrabić Perić & Marina Matošec, 2022. "Breaking new grounds: a fresh insight into the leading properties of business and consumer survey indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4511-4535, December.
- Kawamura, Kohei & Kobashi, Yohei & Shizume, Masato & Ueda, Kozo, 2019. "Strategic central bank communication: Discourse analysis of the Bank of Japan’s Monthly Report," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 230-250.
More about this item
Keywords
News Text Data; Natural Language Processing for Economic Analysis; Sentiment Shocks;All these keywords.
JEL classification:
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
Statistics
Access and download statisticsCorrections
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:kea:keappr:ker-20240101-40-1-05. 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: KEA (email available below). General contact details of provider: https://edirc.repec.org/data/keaaaea.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.