IDEAS home Printed from https://ideas.repec.org/a/eee/intfin/v81y2022ics1042443122001640.html
   My bibliography  Save this article

When central bank research meets Google search: A sentiment index of global financial stress

Author

Listed:
  • Stolbov, Mikhail
  • Shchepeleva, Maria
  • Karminsky, Alexander

Abstract

We construct a sentiment-based index of global financial stress (s-GFS index) for the period January 2004-December 2020. It builds on a novel methodological approach, which synthesizes the intensity of Google search for specific terms and word collocations related to financial instability and their prior selection based on the titles and abstracts of more than 2,000 working papers posted on the Basel Bank for International Settlements Central Bank Research Hub. The s-GFS index obtained by means of sparse principal component analysis (PCA) accurately captures major episodes of global financial instability during the observation period, playing a pivotal role for the US financial stress as well as industrial production in the USA, the Eurozone and China. It also Granger causes several well-known measures of global financial instability based on sentiment and “hard” data, e.g. the VIX index, as well as the overall dynamics of the global financial cycle, thereby emphasizing the usefulness of sentiment-based measures in monitoring worldwide financial stress.

Suggested Citation

  • Stolbov, Mikhail & Shchepeleva, Maria & Karminsky, Alexander, 2022. "When central bank research meets Google search: A sentiment index of global financial stress," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:intfin:v:81:y:2022:i:c:s1042443122001640
    DOI: 10.1016/j.intfin.2022.101692
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1042443122001640
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intfin.2022.101692?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Istrefi, Klodiana & Odendahl, Florens & Sestieri, Giulia, 2023. "Fed communication on financial stability concerns and monetary policy decisions: Revelations from speeches," Journal of Banking & Finance, Elsevier, vol. 151(C).
    2. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    3. Fernandez, Raul & Palma Guizar, Brenda & Rho, Caterina, 2021. "A sentiment-based risk indicator for the Mexican financial sector," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(3).
    4. Reuven Glick & Michael M. Hutchison, 1999. "Banking and currency crises; how common are twins?," Proceedings, Federal Reserve Bank of San Francisco, issue Sep.
    5. Gao, Zhenyu & Ren, Haohan & Zhang, Bohui, 2020. "Googling Investor Sentiment around the World," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(2), pages 549-580, March.
    6. Mittnik, Stefan & Semmler, Willi, 2013. "The real consequences of financial stress," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1479-1499.
    7. Ehrmann, Michael & Wabitsch, Alena, 2022. "Central bank communication with non-experts – A road to nowhere?," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 69-85.
    8. Luc Laeven & Fabian Valencia, 2020. "Systemic Banking Crises Database II," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 68(2), pages 307-361, June.
    9. Svetlana Borovkova & Evgeny Garmaev & Philip Lammers & Jordi Rustige, 2017. "SenSR: A sentiment-based systemic risk indicator," DNB Working Papers 553, Netherlands Central Bank, Research Department.
    10. Lo Duca, Marco & Koban, Anne & Basten, Marisa & Bengtsson, Elias & Klaus, Benjamin & Kusmierczyk, Piotr & Lang, Jan Hannes & Detken, Carsten & Peltonen, Tuomas, 2017. "A new database for financial crises in European countries," ESRB Occasional Paper Series 13, European Systemic Risk Board.
    11. Shapiro, Adam Hale & Sudhof, Moritz & Wilson, Daniel J., 2022. "Measuring news sentiment," Journal of Econometrics, Elsevier, vol. 228(2), pages 221-243.
    12. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    13. Markku Lanne & Henri Nyberg, 2016. "Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 595-603, August.
    14. Kremer, Manfred & Lo Duca, Marco & Holló, Dániel, 2012. "CISS - a composite indicator of systemic stress in the financial system," Working Paper Series 1426, European Central Bank.
    15. Metiu, Norbert & Hilberg, Björn & Grill, Michael, 2016. "Credit constraints and the international propagation of US financial shocks," Journal of Banking & Finance, Elsevier, vol. 72(C), pages 67-80.
    16. Arina Wischnewsky & David‐Jan Jansen & Matthias Neuenkirch, 2021. "Financial stability and the Fed: Evidence from congressional hearings," Economic Inquiry, Western Economic Association International, vol. 59(3), pages 1192-1214, July.
    17. Fadejeva, Ludmila & Feldkircher, Martin & Reininger, Thomas, 2017. "International spillovers from Euro area and US credit and demand shocks: A focus on emerging Europe," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 1-25.
    18. Mallick, Sushanta K. & Sousa, Ricardo M., 2013. "The real effects of financial stress in the Eurozone," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 1-17.
    19. 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.
    20. Wang, Yizhi & Lucey, Brian M. & Vigne, Samuel A. & Yarovaya, Larisa, 2022. "The Effects of Central Bank Digital Currencies News on Financial Markets," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    21. Chen, Pu & Semmler, Willi, 2018. "Financial stress, regime switching and spillover effects: Evidence from a multi-regime global VAR model," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 318-348.
    22. repec:ecb:ecbwps:20111426 is not listed on IDEAS
    23. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    24. Munday, Tim & Brookes, James, 2021. "Mark my words: the transmission of central bank communication to the general public via the print media," Bank of England working papers 944, Bank of England.
    25. Manela, Asaf & Moreira, Alan, 2017. "News implied volatility and disaster concerns," Journal of Financial Economics, Elsevier, vol. 123(1), pages 137-162.
    26. Benjamin Born & Michael Ehrmann & Marcel Fratzscher, 2014. "Central Bank Communication on Financial Stability," Economic Journal, Royal Economic Society, vol. 124(577), pages 701-734, June.
    27. Kevin L. Kliesen & Michael T. Owyang & E. Katarina Vermann, 2012. "Disentangling diverse measures: a survey of financial stress indexes," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 369-398.
    28. Mr. Fabio Comelli & Ms. Sumiko Ogawa, 2021. "What Can We Learn from Financial Stability Reports?," IMF Working Papers 2021/200, International Monetary Fund.
    29. Armelius, Hanna & Bertsch, Christoph & Hull, Isaiah & Zhang, Xin, 2020. "Spread the Word: International spillovers from central bank communication," Journal of International Money and Finance, Elsevier, vol. 103(C).
    30. Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022. "Making text count: Economic forecasting using newspaper text," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
    31. Larsen, Vegard H. & Thorsrud, Leif A., 2019. "The value of news for economic developments," Journal of Econometrics, Elsevier, vol. 210(1), pages 203-218.
    32. Tim Loughran & Bill Mcdonald, 2016. "Textual Analysis in Accounting and Finance: A Survey," Journal of Accounting Research, Wiley Blackwell, vol. 54(4), pages 1187-1230, September.
    33. Nicolas Woloszko, 2020. "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers 1634, OECD Publishing.
    34. Cees Diks & Marcin Wolski, 2016. "Nonlinear Granger Causality: Guidelines for Multivariate Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1333-1351, November.
    35. Christian Brownlees & Robert F. Engle, 2017. "SRISK: A Conditional Capital Shortfall Measure of Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 48-79.
    36. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "News media versus FRED‐MD for macroeconomic forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 63-81, January.
    37. Park, Cyn-Young & Mercado, Rogelio V., 2014. "Determinants of financial stress in emerging market economies," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 199-224.
    38. Zohair Alam & Mr. Adrian Alter & Jesse Eiseman & Mr. Gaston Gelos & Mr. Heedon Kang & Mr. Machiko Narita & Erlend Nier & Naixi Wang, 2019. "Digging Deeper--Evidence on the Effects of Macroprudential Policies from a New Database," IMF Working Papers 2019/066, International Monetary Fund.
    39. Ms. Sònia Muñoz & Mr. Samir Jahjah & Mr. Martin Cihak & Ms. Sharika Teh Sharifuddin & Mr. Kalin I Tintchev, 2012. "Financial Stability Reports: What Are they Good for?," IMF Working Papers 2012/001, International Monetary Fund.
    40. Phillip J. Monin, 2019. "The OFR Financial Stress Index," Risks, MDPI, vol. 7(1), pages 1-21, February.
    41. Tim Loughran & Bill McDonald, 2020. "Textual Analysis in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 12(1), pages 357-375, December.
    42. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    43. Zijia Du & Alan Guoming Huang & Russ Wermers & Wenfeng Wu, 2022. "Language and Domain Specificity: A Chinese Financial Sentiment Dictionary [The effects of analyst-country institutions on biased research: Evidence from target prices]," Review of Finance, European Finance Association, vol. 26(3), pages 673-719.
    44. Beutel, Johannes & Metiu, Norbert & Stockerl, Valentin, 2021. "Toothless tiger with claws? Financial stability communication, expectations, and risk-taking," Journal of Monetary Economics, Elsevier, vol. 120(C), pages 53-69.
    45. Jun, Seung-Pyo & Yoo, Hyoung Sun & Choi, San, 2018. "Ten years of research change using Google Trends: From the perspective of big data utilizations and applications," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 69-87.
    46. 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.
    47. Ricardo Correa & Keshav Garud & Juan M. Londono & Nathan Mislang, 2017. "Constructing a Dictionary for Financial Stability," IFDP Notes 2017-06-28, Board of Governors of the Federal Reserve System (U.S.).
    48. Lawson, Jeremy & Watt, Abigail & Martinez, Carolina & Fu, Rong, 2019. "Chinese Financial Conditions and their Spillovers to the Global Economy and Markets," CEPR Discussion Papers 14065, C.E.P.R. Discussion Papers.
    49. Bholat, David & Broughton, Nida & Ter Meer, Janna & Walczak, Eryk, 2019. "Enhancing central bank communications using simple and relatable information," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 1-15.
    50. Ardia, David & Bluteau, Keven & Boudt, Kris, 2019. "Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1370-1386.
    51. Chengyu Huang & Sean Simpson & Daria Ulybina & Agustin Roitman, 2019. "News-based Sentiment Indicators," IMF Working Papers 2019/273, International Monetary Fund.
    52. Eijffinger, Sylvester C.W. & Karataş, Bilge, 2020. "Together or apart? The relationship between currency and banking crises," Journal of Banking & Finance, Elsevier, vol. 119(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Azzone, Michele & Barucci, Emilio, 2023. "Evaluation of sight deposits and central bank digital currency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    2. Sakariyahu, Rilwan & Johan, Sofia & Lawal, Rodiat & Paterson, Audrey & Chatzivgeri, Eleni, 2023. "Dynamic connectedness between investors’ sentiment and asset prices: A comparison between major markets in Europe and USA," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    3. Yu, Zhen & Liu, Wei & Yang, Fuyu, 2023. "A central bankers’ sentiment index of global financial cycle," Finance Research Letters, Elsevier, vol. 57(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.
    1. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    2. Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
    3. 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).
    4. Jean-Charles Bricongne & Baptiste Meunier & Raquel Caldeira, 2024. "Should Central Banks Care About Text Mining? A Literature Review," Working papers 950, Banque de France.
    5. Martin Baumgaertner & Johannes Zahner, 2021. "Whatever it takes to understand a central banker - Embedding their words using neural networks," MAGKS Papers on Economics 202130, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Mikhail Stolbov & Maria Shchepeleva, 2018. "Systemic risk in Europe: deciphering leading measures, common patterns and real effects," Annals of Finance, Springer, vol. 14(1), pages 49-91, February.
    7. 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.
    8. 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.
    9. García, Diego & Hu, Xiaowen & Rohrer, Maximilian, 2023. "The colour of finance words," Journal of Financial Economics, Elsevier, vol. 147(3), pages 525-549.
    10. Juan M. Londono & Stijn Claessens & Ricardo Correa, 2024. "Financial Stability Governance and Central Bank Communications," International Journal of Central Banking, International Journal of Central Banking, vol. 20(4), pages 175-220, October.
    11. David Kohns & Arnab Bhattacharjee, 2020. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," Papers 2011.00938, arXiv.org, revised May 2022.
    12. Aprigliano, Valentina & Emiliozzi, Simone & Guaitoli, Gabriele & Luciani, Andrea & Marcucci, Juri & Monteforte, Libero, 2023. "The power of text-based indicators in forecasting Italian economic activity," International Journal of Forecasting, Elsevier, vol. 39(2), pages 791-808.
    13. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "News media versus FRED‐MD for macroeconomic forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 63-81, January.
    14. Mikhail Stolbov & Maria Shchepeleva, 2023. "Sentiment-based indicators of real estate market stress and systemic risk: international evidence," Annals of Finance, Springer, vol. 19(3), pages 355-382, September.
    15. Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022. "Making text count: Economic forecasting using newspaper text," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
    16. Fernandez, Raul & Palma Guizar, Brenda & Rho, Caterina, 2021. "A sentiment-based risk indicator for the Mexican financial sector," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(3).
    17. Dorinth van Dijk & Jasper de Winter, 2023. "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers 766, DNB.
    18. Faccini, Renato & Matin, Rastin & Skiadopoulos, George, 2023. "Dissecting climate risks: Are they reflected in stock prices?," Journal of Banking & Finance, Elsevier, vol. 155(C).
    19. Chavleishvili, Sulkhan & Kremer, Manfred, 2023. "Measuring systemic financial stress and its risks for growth," Working Paper Series 2842, European Central Bank.
    20. Fulop, Andras & Kocsis, Zalan, 2023. "News indices on country fundamentals," Journal of Banking & Finance, Elsevier, vol. 154(C).

    More about this item

    Keywords

    Financial stability; Financial stress; Google trends; Sentiment index; Sparse principal component analysis;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

    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:eee:intfin:v:81:y:2022:i:c:s1042443122001640. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/intfin .

    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.