Data science in central banking: enhancing the access to and sharing of data
Author
Abstract
Individual chapters are listed in the "Chapters" tab
Suggested Citation
Download full text from publisher
References listed on IDEAS
- 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.
- 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.
- 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).
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.- 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.
- Fang, Yi & Wang, Qi & Wang, Yanru & Yuan, Yan, 2024. "Media sentiment, deposit stability and bank systemic risk: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 1150-1172.
- Allassonnière, Stéphanie & Chevallier, Juliette, 2021. "A new class of stochastic EM algorithms. Escaping local maxima and handling intractable sampling," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
- Rodrigo Zeidan, 2022. "Why don't asset managers accelerate ESG investing? A sentiment analysis based on 13,000 messages from finance professionals," Business Strategy and the Environment, Wiley Blackwell, vol. 31(7), pages 3028-3039, November.
- Hasan, Tahseen & John, Kose & Teng, Haimeng & Wu, Qiang, 2024. "Creative corporate culture and corporate tax avoidance," The British Accounting Review, Elsevier, vol. 56(3).
- Leonardo Fernandez, 2012. "Price Discovery, Investor Distraction and Analyst Recommendations Under Continuous Disclosure Requirements in Australia," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2012, January-A.
- Riccardo Rastelli & Michael Fop, 2020. "A stochastic block model for interaction lengths," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(2), pages 485-512, June.
- Gu, Chen & Kurov, Alexander & Wolfe, Marketa Halova, 2018. "Relief Rallies after FOMC Announcements as a Resolution of Uncertainty," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 1-18.
- Oehler, Andreas & Neuss, Charlotte, 2025. "ESG disclosure vs. ESG ratings: Consistent information value?," International Review of Financial Analysis, Elsevier, vol. 107(C).
- 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.
- Ren, Tingting & Li, Shaofang, 2025. "Stock market forecasting based on machine learning: The role of investor sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 666(C).
- Aaryan Gupta & Vinya Dengre & Hamza Abubakar Kheruwala & Manan Shah, 2020. "Comprehensive review of text-mining applications in finance," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-25, December.
- Yi-Hsuan Chen, Cathy & Fengler, Matthias & Härdle, Wolfgang Karl & Liu, Yanchu, 2018.
"Textual Sentiment, Option Characteristics, and Stock Return Predictability,"
Economics Working Paper Series
1808, University of St. Gallen, School of Economics and Political Science.
- Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2018. "Textual Sentiment, Option Characteristics, and Stock Return Predictability," IRTG 1792 Discussion Papers 2018-023, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Yen-Ju Hsu & Yang-Cheng Lu & J. Jimmy Yang, 2021. "News sentiment and stock market volatility," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 1093-1122, October.
- Deng, Justin, 2025. "Pulling back the curtain, does news about a firm’s economic events before the earnings announcement help investors contextualize earnings surprise?," Journal of Contemporary Accounting and Economics, Elsevier, vol. 21(3).
- Deborah Gefang & Gary Koop & Aubrey Poon, 2019.
"Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage,"
Discussion Papers in Economics
19/05, Division of Economics, School of Business, University of Leicester.
- Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," CAMA Working Papers 2019-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Deborah Gefang & Gary Koop & Aubrey Poon, 2019. "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-07, Economic Statistics Centre of Excellence (ESCoE).
- Yan Luo & Linying Zhou, 2020. "Textual tone in corporate financial disclosures: a survey of the literature," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 17(2), pages 101-110, September.
- Wolfgang Breuer & Andreas Knetsch & Astrid Juliane Salzmann, 2020. "What Does It Mean When Managers Talk About Trust?," Journal of Business Ethics, Springer, vol. 166(3), pages 473-488, October.
- Jiao Ji & Oleksandr Talavera & Shuxing Yin, 2018. "The Hidden Information Content: Evidence from the Tone of Independent Director Reports," Working Papers 2018-28, Swansea University, School of Management.
- Jang, Junkyu, 2025. "Selective news selection model for explainable stock prediction via cross-attention integration," Finance Research Letters, Elsevier, vol. 85(PD).
Book Chapters
The following chapters of this book are listed in IDEAS- Bruno Tissot, 2025. "Data science in central banking: enhancing the access to and sharing of data," 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.
- Beju Shah, 2025. "Project Aurora: the power of data, technology and collaboration to combat money laundring across institutions and borders," 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.
- Eric Anvar, 2025. "Why SDMX matters? A community journey towards SDMX as an AI-enabler and a data mesh enabler," 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.
- Jacob Ewertzh & John Svanäng, 2025. "Data science in the context of international banking statistics," 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.
- Patty Duijm & Iman van Lelyveld, 2025. "Experiences, essentials and perspectives for data science in the hearts of central banks and supervisors: a case study of the Dutch central bank," 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.
- Pavle Avramović, 2025. "Digital transformation of financial regulators and the emergence of supervisory technologies (SupTech): a case study of the UK Financial Conduct Authority," 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.
- Anamaria Illes & Ilaria Mattei, 2025. "Data Building a database on cryptocurrencies," 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.
- Pawel Martyniuk & Michal Piechocki, 2025. "European single access point as a blueprint for global financial and green data hubs," 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.
- Nelson Matt & Glenn Philip Tice, 2025. "Data sharing using a global data registry: on a place to discover global structured time series, macro and micro data," 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.
- Timur Sattarov & Marco Schreyer, 2025. "Overcoming data-sharing challenges in central banking: federated learning of diffusion models for synthetic mixed-type tabular data generation," 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.
- Mauro Bruno & Erika Cerasti & Massimo De Cubellis & Francesco Pugliese & Rafik Chemli & Benjamin Santos & Julian Templeton & Matjaz Jug, 2025. "Exploring aggregation strategies for federated learning in national statistics," 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.
- Michele Leonardo Bianchi & Bianca Sorvillo & Dario Ruzzi & Federico Apicella & Luigi Abate & Leonardo Del Vecchio, 2025. "EMIR data for financial stability analysis and research," 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.
- Renardi Ardiya Bimantoro & Irfan Sampe & Mohammad Khoyrul Hidayat, 2025. "Unveiling the interconnectedness of banks in payment system: methodology, utilization, and data governance considerations," 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.
- Tsenddorj Dorjpurev, 2025. "Big data platform (FinPulse) initiative," 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.
- Ana R Gonçalves & Mário Lourenço & Daniel V Sousa & Thomas Verheij, 2025. "New strategy of data sharing and data access in statistics: the view from Banco de Portugal," 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.
- Johanes Iman Anugrah & Akhmad Zacky Nugraha & Sapto Widyatmiko, 2025. "Individual data access and sharing protection policy: definition and case study of Bank Indonesia," 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.
- Douglas Kiarelly Godoy de Araujo, 2025. "Open-sourced central bank macroeconomic models," 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.
- Darran Hodder & Matthew Nelson, 2025. "Leveraging open-source software and data standards as the backbone of your open data strategy," 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.
- Brian Buffett & Stratos Nikoloutsos & Xavier Sosnovsky, 2025. "Collaborating on SDMX APIs and open-source software," 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.
- Ryland Thomas, 2025. "Future of time series: preliminary results from a BIS-IFC survey of central banks and statistical agencies," 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.
- Ayoub Mharzi, 2025. "Coding time series with machine learning," 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.
- Katia Boria & Andrea Luciani & Sabina Marchetti & Marco Viticoli, 2025. "Siamese neural networks for detecting banknote printing defects," 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.
- Csaba Burger & Mihály Berndt, 2025. "Error spotting with gradient boosting: a machine learning-based application for central bank data quality," 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.
- Pasquale Cariello & Marco De Simoni & Stefano Iezzi, 2025. "A machine learning approach for the detection of firms infiltrated by organised crime in Italy," 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.
- Carmelita Esclanda-Lo & Gabriel Masangkay & Chelsea Anne Ong & Rossvern Reyes, 2025. "Research for all: exploring machine learning applications in generating synthetic datasets," 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.
- Pablo Acevedo & Dagoberto Quevedo & Marco Rojas & Emiliano Luttini & Matías Pizarro, 2025. "Invoices rather than surveys: using ML to build nominal and real indices," 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.
- Sebastian Seltmann & Emily Kormanyos & Hendrik Christian Doll, 2025. "Leveraging large language models to extract data citations," 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.
- Seung Jung Lee & Sriram Nagaraj & Dylan Saez & Victors Stebunovs & Cindy Vojtech & Karl Wirth, 2025. "Let's talk about sentiment: natural language processing using machine learning on bank earnings transcripts," 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.
- 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.
- Shengwu Du & Karen Guo & Flora Haberkorn & Abby Kessler & Isabel Kitschelt & Seung Jung Lee & Anderson Monken & Dylan Saez & Kelsey Shipman & Sandeep Thakur, 2025. "Do anecdotes matter? Exploring the beige book through textual analysis from 1970 to 2023," 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.
- Sercan Eraslan & Eniko Gabor-Toth, 2025. "Central bank communication on economic activity," 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.
- Janek Blankenburg & Maximilian König & Philipp Rothhaar & Bernd Rusitschka, 2025. "From the ML model to practice: case study on NLP-based decision-making on the eligibility of security prospectuses," 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.
- Alessandra Perrazzelli, 2025. "Data Science in Central Banking: Enhancing the access to and sharing of data," 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.
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:bisifb:64. 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.
Printed from https://ideas.repec.org/b/bis/bisifb/64.html