IDEAS home Printed from https://ideas.repec.org/a/eee/jimfin/v120y2022ics0261560621001832.html
   My bibliography  Save this article

Singular spectrum analysis for real-time financial cycles measurement

Author

Listed:
  • Coussin, Maximilien

Abstract

This paper provides a new statistical methodology based on Singular Spectrum Analysis to extract the cycle component of an economic time series in real-time, addressing several criticisms towards classical ones. I measure the Credit-to-GDP cycles of 21 developed countries and run a horse race to compare it with the Hodrick-Prescott filter, the Hamilton regression filter, the 8-quarters growth rates, a Bartlett window, and variants. The SSA methodology performs best as an Early Warning Indicator for banking vulnerabilities and banking crises up to three years ahead. These conclusions about methodologies have practical implications for the measure of the systemic risk and the conduct of macroprudential policies.

Suggested Citation

  • Coussin, Maximilien, 2022. "Singular spectrum analysis for real-time financial cycles measurement," Journal of International Money and Finance, Elsevier, vol. 120(C).
    • Handle: RePEc:eee:jimfin:v:120:y:2022:i:c:s0261560621001832
    DOI: 10.1016/j.jimonfin.2021.102532
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0261560621001832
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jimonfin.2021.102532?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. Schüler, Yves S. & Hiebert, Paul P. & Peltonen, Tuomas A., 2020. "Financial cycles: Characterisation and real-time measurement," Journal of International Money and Finance, Elsevier, vol. 100(C).
    2. Christian J. Murray, 2003. "Cyclical Properties of Baxter-King Filtered Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 472-476, May.
    3. Richter, Björn & Schularick, Moritz & Shim, Ilhyock, 2019. "The costs of macroprudential policy," Journal of International Economics, Elsevier, vol. 118(C), pages 263-282.
    4. Rodrigo Barbone Gonzalez & Joaquim Lima & Leonardo Marinho, 2015. "Business and Financial Cycles: an estimation of cycles’ length focusing on Macroprudential Policy," Working Papers Series 385, Central Bank of Brazil, Research Department.
    5. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    6. repec:pes:ierequ:v:14:y:2019:i:1:p:lip.29 is not listed on IDEAS
    7. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    8. de Carvalho, Miguel & Rodrigues, Paulo C. & Rua, António, 2012. "Tracking the US business cycle with a singular spectrum analysis," Economics Letters, Elsevier, vol. 114(1), pages 32-35.
    9. Mathias Drehmann & James Yetman, 2021. "Which Credit Gap Is Better at Predicting Financial Crises? A Comparison of Univariate Filters," International Journal of Central Banking, International Journal of Central Banking, vol. 17(70), pages 1-31, October.
    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," Occasional Paper Series 194, European Central Bank.
    11. Bernanke, Ben S, 1995. "The Macroeconomics of the Great Depression: A Comparative Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(1), pages 1-28, February.
    12. James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 831-843, December.
    13. Borio, Claudio, 2014. "The financial cycle and macroeconomics: What have we learnt?," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 182-198.
    14. Mr. Luc Laeven & Mr. Fabian Valencia, 2018. "Systemic Banking Crises Revisited," IMF Working Papers 2018/206, International Monetary Fund.
    15. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
    16. Mathias Drehmann & James Yetman, 2018. "Why you should use the Hodrick-Prescott filter - at least to generate credit gaps," BIS Working Papers 744, Bank for International Settlements.
    17. Marinko Skare & Malgorzata Porada-Rochon, 2019. "Tracking financial cycles in ten transitional economies 2005–2018 using singular spectrum analysis (SSA) techniques," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 14(1), pages 7-29, March.
    18. Mandler, Martin & Scharnagl, Michael, 2022. "Financial cycles across G7 economies: A view from wavelet analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    19. Claudio Borio & Mathias Drehmann, 2009. "Assessing the risk of banking crises - revisited," BIS Quarterly Review, Bank for International Settlements, March.
    20. Mathias Drehmann & Claudio Borio & Leonardo Gambacorta & Gabriel Jiminez & Carlos Trucharte, 2010. "Countercyclical capital buffers: exploring options," BIS Working Papers 317, Bank for International Settlements.
    21. Dahlquist, Magnus & Hasseltoft, Henrik, 2020. "Economic momentum and currency returns," Journal of Financial Economics, Elsevier, vol. 136(1), pages 152-167.
    22. Claudio Borio & Philip Lowe, 2002. "Assessing the risk of banking crises," BIS Quarterly Review, Bank for International Settlements, December.
    23. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
    24. Schüler, Yves S., 2018. "Detrending and financial cycle facts across G7 countries: mind a spurious medium term!," Working Paper Series 2138, European Central Bank.
    25. Wolf, Elias & Mokinski, Frieder & Schüler, Yves, 2020. "On adjusting the one-sided Hodrick-Prescott filter," Discussion Papers 11/2020, Deutsche Bundesbank.
    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. Yang, Zihao & Dong, Sheng, 2024. "A novel framework for wind energy assessment at multi-time scale based on non-stationary wind speed models: A case study in China," Renewable Energy, Elsevier, vol. 226(C).
    2. Yang, Zihao & Dong, Sheng, 2023. "A novel decomposition-based approach for non-stationary hub-height wind speed modelling," Energy, Elsevier, vol. 283(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. Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021. "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, vol. 132(C).
    2. Schüler, Yves S. & Hiebert, Paul P. & Peltonen, Tuomas A., 2020. "Financial cycles: Characterisation and real-time measurement," Journal of International Money and Finance, Elsevier, vol. 100(C).
    3. Berger, Tino & Richter, Julia & Wong, Benjamin, 2022. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    4. Greg Farrell & Esti Kemp, 2020. "Measuring the Financial Cycle in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 88(2), pages 123-144, June.
    5. Berger, Tino & Richter, Julia & Wong, Benjamin, 2022. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    6. Josefine Quast & Maik H. Wolters, 2022. "Reliable Real-Time Output Gap Estimates Based on a Modified Hamilton Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 152-168, January.
    7. Bouvatier, Vincent & Delatte, Anne-Laure & Rehault, Pierre-Nicolas, 2022. "Measuring credit procyclicality: A new database," Emerging Markets Review, Elsevier, vol. 52(C).
    8. Piergiorgio Alessandri & Pierluigi Bologna & Maddalena Galardo, 2022. "Financial Crises, Macroprudential Policy and the Reliability of Credit-to-GDP Gaps," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(4), pages 625-667, December.
    9. Daniel O. Beltran & Mohammad R. Jahan-Parvar & Fiona A. Paine, 2021. "Optimizing Credit Gaps for Predicting Financial Crises: Modelling Choices and Tradeoffs," International Finance Discussion Papers 1307, Board of Governors of the Federal Reserve System (U.S.).
    10. Schüler, Yves S., 2020. "On the credit-to-GDP gap and spurious medium-term cycles," Economics Letters, Elsevier, vol. 192(C).
    11. Tihana Škrinjarić, 2023. "Credit-to-GDP Gap Estimates in Real Time: A Stable Indicator for Macroprudential Policy Making in Croatia," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 65(3), pages 582-614, September.
    12. Hessler, Andrew, 2023. "Unobserved components model estimates of credit cycles: Tests and predictions," Journal of Financial Stability, Elsevier, vol. 66(C).
    13. Mathias Drehmann & James Yetman, 2021. "Which Credit Gap Is Better at Predicting Financial Crises? A Comparison of Univariate Filters," International Journal of Central Banking, International Journal of Central Banking, vol. 17(70), pages 1-31, October.
    14. Ihejirika, Peters. O, 2020. "Does the Credit-to-GDP Gap Predict Financial Crisis in Nigeria?," International Journal of Social and Administrative Sciences, Asian Economic and Social Society, vol. 5(2), pages 109-126, June.
    15. Carnazza, Giovanni & Liberati, Paolo & Sacchi, Agnese, 2020. "The cyclically-adjusted primary balance: A novel approach for the euro area," Journal of Policy Modeling, Elsevier, vol. 42(5), pages 1123-1145.
    16. Łukasz Kurowski, 2021. "Financial cycle − A critical analysis of the methodology for its identification," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(3), pages 99-116.
    17. Schüler, Yves S., 2018. "Detrending and financial cycle facts across G7 countries: mind a spurious medium term!," Working Paper Series 2138, European Central Bank.
    18. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.
    19. Melina Dritsaki & Chaido Dritsaki, 2022. "Comparison of HP Filter and the Hamilton’s Regression," Mathematics, MDPI, vol. 10(8), pages 1-18, April.
    20. Fernandez-Gallardo, Alvaro, 2023. "Preventing financial disasters: Macroprudential policy and financial crises," European Economic Review, Elsevier, vol. 151(C).

    More about this item

    Keywords

    Financial cycles; Singular Spectrum Analysis; Early Warning; Real-time; Macroprudential policy;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • E63 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Comparative or Joint Analysis of Fiscal and Monetary Policy; Stabilization; Treasury Policy
    • F45 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Macroeconomic Issues of Monetary Unions

    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:jimfin:v:120:y:2022:i:c:s0261560621001832. 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/inca/30443 .

    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.