IDEAS home Printed from https://ideas.repec.org/p/bis/bisifr/11.html
   My bibliography  Save this paper

Computing platforms for big data analytics and artificial intelligence

Author

Listed:
  • Giuseppe Bruno
  • Hiren Jani
  • Rafael Schmidt
  • Bruno Tissot

Abstract

No abstract is available for this item.

Suggested Citation

  • Giuseppe Bruno & Hiren Jani & Rafael Schmidt & Bruno Tissot, 2020. "Computing platforms for big data analytics and artificial intelligence," IFC Reports 11, Bank for International Settlements.
  • Handle: RePEc:bis:bisifr:11
    as

    Download full text from publisher

    File URL: https://www.bis.org/ifc/publ/ifc_report_computing_2004.pdf
    File Function: Full PDF document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eiglsperger, Martin, 2019. "New features in the Harmonised Index of Consumer Prices: analytical groups, scanner data and web-scraping," Economic Bulletin Boxes, European Central Bank, vol. 2.
    2. Renaud Lacroix, 2019. "The Bank of France datalake," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
    3. Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
    4. Bholat, David, 2015. "Big data and central banks," Bank of England Quarterly Bulletin, Bank of England, vol. 55(1), pages 86-93.
    5. Anna Drozdova, 2017. "Modern informational technologies for data analysis: from business analytics to data visualization," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Statistical implications of the new financial landscape, volume 43, Bank for International Settlements.
    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. Okiriza Wibisono & Hidayah Dhini Ari & Anggraini Widjanarti & Alvin Andhika Zulen & Bruno Tissot, 2019. "The use of big data analytics and artificial intelligence in central banking – An overview," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
    2. Dmitry Protsenko & Maria Vilkova & Edward Lambe & Bruno Tissot, 2019. "Business intelligence systems and central bank statistics," IFC Reports 9, Bank for International Settlements.
    3. Fernando Alvarez & Francesco Lippi & Juan Passadore, 2017. "Are State- and Time-Dependent Models Really Different?," NBER Macroeconomics Annual, University of Chicago Press, vol. 31(1), pages 379-457.
    4. Antoaneta Serguieva, 2017. "Multichannel Contagion vs Stabilisation in Multiple Interconnected Financial Markets," Papers 1701.06975, arXiv.org, revised Apr 2017.
    5. Fernando Alvarez & Francesco Lippi, 2020. "Temporary Price Changes, Inflation Regimes, and the Propagation of Monetary Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(1), pages 104-152, January.
    6. John M. Abowd & Ian M. Schmutte & William Sexton & Lars Vilhuber, 2019. "Suboptimal Provision of Privacy and Statistical Accuracy When They are Public Goods," Papers 1906.09353, arXiv.org.
    7. 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.
    8. Erica L. Groshen & Brian C. Moyer & Ana M. Aizcorbe & Ralph Bradley & David M. Friedman, 2017. "How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 187-210, Spring.
    9. Patrick Bajari & Zhihao Cen & Victor Chernozhukov & Manoj Manukonda & Jin Wang & Ramon Huerta & Junbo Li & Ling Leng & George Monokroussos & Suhas Vijaykunar & Shan Wan, 2023. "Hedonic prices and quality adjusted price indices powered by AI," CeMMAP working papers 08/23, Institute for Fiscal Studies.
    10. Antoaneta Serguieva & David Bholat, 2017. "Multichannel contagion vs stabilisation in multiple interconnected financial markets," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Statistical implications of the new financial landscape, volume 43, Bank for International Settlements.
    11. Jennifer Peña & Elvira Prades, 2021. "Price setting in Chile: Micro evidence from consumer on-line prices during the social outbreak and Covid-19," Working Papers 2112, Banco de España.
    12. Giuseppe Arbia & Vincenzo Nardelli, 2024. "Using Web-Data to Estimate Spatial Regression Models," International Regional Science Review, , vol. 47(2), pages 204-226, March.
    13. Jean-Marc Israel & Bruno Tissot, 2021. "Incorporating micro data into macro policy decision-making," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Micro data for the macro world, volume 53, Bank for International Settlements.
    14. Hai Long Vo & Duc Hong Vo, 2023. "The purchasing power parity and exchange‐rate economics half a century on," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 446-479, April.
    15. Diego Bodas & Juan Ramon Garcia & Juan Murillo & Matias Pacce & Tomasa Rodrigo & Juan de Dios Romero & Pep Ruiz & Camilo Ulloa & Heribert Valero, 2018. "Measuring Retail Trade Using Card Transactional Data," Working Papers 18/03, BBVA Bank, Economic Research Department.
    16. Cavallo, Alberto & Kryvtsov, Oleksiy, 2023. "What can stockouts tell us about inflation? Evidence from online micro data," Journal of International Economics, Elsevier, vol. 146(C).
    17. Markus Dertwinkel-Kalt & Mats Köster, 2017. "Salience and Online Sales: The Role of Brand Image Concerns," CESifo Working Paper Series 6787, CESifo.
    18. Flood, M. D. & Jagadish, H. V. & Raschid, L., 2016. "Big data challenges and opportunities in financial stability monitoring," Financial Stability Review, Banque de France, issue 20, pages 129-142, April.
    19. Margaret M. Jacobson & Christian Matthes & Todd B. Walker, 2022. "Inflation Measured Every Day Keeps Adverse Responses Away: Temporal Aggregation and Monetary Policy Transmission," Finance and Economics Discussion Series 2022-054, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bisifr:11. 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: Christian Beslmeisl (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.