IDEAS home Printed from https://ideas.repec.org/p/ecb/ecbwps/20172057.html
   My bibliography  Save this paper

How to predict financial stress? An assessment of Markov switching models

Author

Listed:
  • Duprey, Thibaut
  • Klaus, Benjamin

Abstract

This paper predicts phases of the financial cycle by combining a continuous financial stress measure in a Markov switching framework. The debt service ratio and property market variables signal a transition to a high financial stress regime, while economic sentiment indicators provide signals for a transition to a tranquil state. Whereas the in-sample analysis suggests that these indicators can provide an early warning signal up to several quarters prior to the respective regime change, the out-of-sample findings indicate that most of this performance is due to the data gathered during the global financial crisis. Comparing the prediction performance with a standard binary early warning model reveals that the MS model is outperforming in the vast majority of model specifications for a horizon up to three quarters prior to the onset of financial stress. JEL Classification: C54, G01, G15

Suggested Citation

  • Duprey, Thibaut & Klaus, Benjamin, 2017. "How to predict financial stress? An assessment of Markov switching models," Working Paper Series 2057, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20172057
    as

    Download full text from publisher

    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecb.wp2057.en.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jeffrey A. Frankel & Shang-Jin Wei, 2004. "Managing Macroeconomic Crises," NBER Working Papers 10907, National Bureau of Economic Research, Inc.
    2. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "The Aftermath of Financial Crises," American Economic Review, American Economic Association, vol. 99(2), pages 466-472, May.
    3. 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.
    4. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    5. Babecký, Jan & Havránek, Tomáš & Matějů, Jakub & Rusnák, Marek & Šmídková, Kateřina & Vašíček, Bořek, 2014. "Banking, debt, and currency crises in developed countries: Stylized facts and early warning indicators," Journal of Financial Stability, Elsevier, vol. 15(C), pages 1-17.
    6. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. Van Dijk, 2016. "Interconnections Between Eurozone and us Booms and Busts Using a Bayesian Panel Markov‐Switching VAR Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1352-1370, November.
    7. 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.
    8. Tyler Atkinson & David Luttrell & Harvey Rosenblum, 2013. "Assessing the costs and consequences of the 2007–09 financial crisis and its aftermath," Economic Letter, Federal Reserve Bank of Dallas, vol. 8(7), September.
    9. repec:ecb:ecbwps:20111426 is not listed on IDEAS
    10. Iskandar Simorangkir, 2012. "Study on early Warning Indicators of Bank Runs: Markov-Switching Approach," EcoMod2012 4147, EcoMod.
    11. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    12. Mathias Drehmann & Kostas Tsatsaronis, 2014. "The credit-to-GDP gap and countercyclical capital buffers: questions and answers," BIS Quarterly Review, Bank for International Settlements, March.
    13. Graciela Kaminsky & Saul Lizondo & Carmen M. Reinhart, 1998. "Leading Indicators of Currency Crises," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 1-48, March.
    14. Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 299-308, July.
    15. Christina D. Romer & David H. Romer, 2015. "New Evidence on the Impact of Financial Crises in Advanced Countries," NBER Working Papers 21021, National Bureau of Economic Research, Inc.
    16. Claudio Borio, 2014. "The financial cycle and macroeconomics: what have we learned and what are the policy implications?," Chapters, in: Ewald Nowotny & Doris Ritzberger-Grünwald & Peter Backé (ed.), Financial Cycles and the Real Economy, chapter 2, pages 10-35, Edward Elgar Publishing.
    17. Abdul Abiad, 2007. "Early Warning Systems for Currency Crises: A Regime-Switching Approach," International Series in Operations Research & Management Science, in: Rogemar S. Mamon & Robert J. Elliott (ed.), Hidden Markov Models in Finance, chapter 10, pages 155-184, Springer.
    18. Engel, Charles & Hakkio, Craig S, 1996. "The Distribution of Exchange Rates in the EMS," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 1(1), pages 55-67, January.
    19. James D. Hamilton & Michael T. Owyang, 2012. "The Propagation of Regional Recessions," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 935-947, November.
    20. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    21. Arias, Guillaume & Erlandsson, Ulf, 2004. "Regime switching as an alternative early warning system of currency crises - an application to South-East Asia," Working Papers 2004:11, Lund University, Department of Economics.
    22. Borio, Claudio, 2014. "The financial cycle and macroeconomics: What have we learnt?," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 182-198.
    23. Moritz Schularick & Alan M. Taylor, 2012. "Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870-2008," American Economic Review, American Economic Association, vol. 102(2), pages 1029-1061, April.
    24. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
    25. Piergiorgio Alessandri & Haroon Mumtaz, 2017. "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 66-78, March.
    26. Chauvet, Marcelle & Piger, Jeremy, 2008. "A Comparison of the Real-Time Performance of Business Cycle Dating Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 42-49, January.
    27. Brunetti, Celso & Scotti, Chiara & Mariano, Roberto S. & Tan, Augustine H.H., 2008. "Markov switching GARCH models of currency turmoil in Southeast Asia," Emerging Markets Review, Elsevier, vol. 9(2), pages 104-128, June.
    28. Duprey, Thibaut & Klaus, Benjamin & Peltonen, Tuomas, 2017. "Dating systemic financial stress episodes in the EU countries," Journal of Financial Stability, Elsevier, vol. 32(C), pages 30-56.
    29. Maria Dolores Gadea Rivas & Gabriel Perez-Quiros, 2015. "The Failure To Predict The Great Recession—A View Through The Role Of Credit," Journal of the European Economic Association, European Economic Association, vol. 13(3), pages 534-559, June.
    30. Valerie Cerra & Sweta Chaman Saxena, 2002. "Contagion, Monsoons, and Domestic Turmoil in Indonesia’s Currency Crisis," Review of International Economics, Wiley Blackwell, vol. 10(1), pages 36-44, February.
    31. repec:zbw:bofrdp:2015_006 is not listed on IDEAS
    32. Maria Soledad Martinez Peria, 2002. "A regime-switching approach to the study of speculative attacks: A focus on EMS crises," Empirical Economics, Springer, vol. 27(2), pages 299-334.
    33. Hartmann, Philipp & Hubrich, Kirstin & Kremer, Manfred & Tetlow, Robert J., 2013. "Melting down: Systemic financial instability and the macroeconomy," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 80487, Verein für Socialpolitik / German Economic Association.
    34. Chauvet, Marcelle, 1998. "An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 969-996, November.
    35. Bussiere, Matthieu & Fratzscher, Marcel, 2006. "Towards a new early warning system of financial crises," Journal of International Money and Finance, Elsevier, vol. 25(6), pages 953-973, October.
    36. repec:idn:journl:v:15:y:2012:i:1:p:1-38 is not listed on IDEAS
    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. Kuang-Liang Chang & Charles Ka Yui Leung, 2022. "How did the asset markets change after the Global Financial Crisis?," Chapters, in: Charles K.Y. Leung (ed.), Handbook of Real Estate and Macroeconomics, chapter 12, pages 312-336, Edward Elgar Publishing.
    2. Pfeifer, Lukáš & Hodula, Martin, 2018. "A profit-to-provisioning approach to setting the countercyclical capital buffer: the Czech example," ESRB Working Paper Series 82, European Systemic Risk Board.
    3. Hyeongwoo Kim & Wen Shi, 2021. "Forecasting financial vulnerability in the USA: A factor model approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 439-457, April.
    4. Phillip J. Monin, 2019. "The OFR Financial Stress Index," Risks, MDPI, vol. 7(1), pages 1-21, February.
    5. Pfeifer, Lukáš & Hodula, Martin, 2021. "A profit-to-provisioning approach to setting the countercyclical capital buffer," Economic Systems, Elsevier, vol. 45(1).
    6. Li, Zhicheng & Chen, Xinyun & Xing, Haipeng, 2023. "A multifactor regime-switching model for inter-trade durations in the high-frequency limit order market," Economic Modelling, Elsevier, vol. 118(C).
    7. Luca Tiozzo Pezzoli & Elisa Tosetti, 2022. "Seismonomics: Listening to the heartbeat of the economy," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 288-309, December.
    8. Rakovská, Zuzana, 2021. "Composite survey sentiment as a predictor of future market returns: Evidence for German equity indices," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 473-495.
    9. Bedayo, Mikel & Estrada, Ángel & Saurina, Jesús, 2020. "Bank capital, lending booms, and busts: Evidence from Spain over the last 150 years," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    10. Tihana Skrinjaric, 2023. "Introducing a composite indicator of cyclical systemic risk in Croatia: possibilities and limitations," Public Sector Economics, Institute of Public Finance, vol. 47(1), pages 1-39.
    11. Nikolaos Papanikolaou, 2020. "Markov-Switching Model of Family Income Quintile Shares," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 48(2), pages 207-222, June.
    12. Somnath Chatterjee & Ching‐Wai (Jeremy) Chiu & Thibaut Duprey & Sinem Hacıoğlu‐Hoke, 2022. "Systemic Financial Stress and Macroeconomic Amplifications in the United Kingdom," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(2), pages 380-400, April.

    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. Duprey, Thibaut & Klaus, Benjamin, 2022. "Early warning or too late? A (pseudo-)real-time identification of leading indicators of financial stress," Journal of Banking & Finance, Elsevier, vol. 138(C).
    2. Duprey, Thibaut & Klaus, Benjamin & Peltonen, Tuomas, 2017. "Dating systemic financial stress episodes in the EU countries," Journal of Financial Stability, Elsevier, vol. 32(C), pages 30-56.
    3. Pfeifer, Lukáš & Hodula, Martin, 2021. "A profit-to-provisioning approach to setting the countercyclical capital buffer," Economic Systems, Elsevier, vol. 45(1).
    4. Layal MansourIshrakieh & Leila Dagher & Sadika El Hariri, 2020. "A financial stress index for a highly dollarized developing country : The case of Lebanon," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 20(2), pages 43-52.
    5. Michael T. Owyang & Jeremy Piger & Daniel Soques, 2022. "Contagious switching," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 415-432, March.
    6. Mansour Ishrakieh, Layal & Dagher, Leila & El Hariri, Sadika, 2018. "The Institute of Financial Economics Financial Stress Index (IFEFSI) for Lebanon," MPRA Paper 116054, University Library of Munich, Germany.
    7. Pfeifer, Lukáš & Hodula, Martin, 2018. "A profit-to-provisioning approach to setting the countercyclical capital buffer: the Czech example," ESRB Working Paper Series 82, European Systemic Risk Board.
    8. Alessi, Lucia & Detken, Carsten, 2018. "Identifying excessive credit growth and leverage," Journal of Financial Stability, Elsevier, vol. 35(C), pages 215-225.
    9. 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.
    10. Cem Çakmakli & Hamza Dem I˙rcani & Sumru Altug, 2021. "Modelling of Economic and Financial Conditions for Real‐Time Prediction of Recessions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 663-685, June.
    11. Bordo, M.D. & Meissner, C.M., 2016. "Fiscal and Financial Crises," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 355-412, Elsevier.
    12. Alonso-Alvarez, Irma & Molina, Luis, 2023. "How to foresee crises? A new synthetic index of vulnerabilities for emerging economies," Economic Modelling, Elsevier, vol. 125(C).
    13. Bjarni G. Einarsson & Kristófer Gunnlaugsson & Thorvardur Tjörvi Ólafsson & Thórarinn G. Pétursson, 2016. "The long history of financial boom-bust cycles in Iceland - Part II: Financial cycles," Economics wp72, Department of Economics, Central bank of Iceland.
    14. Fendel Ralf & Stremmel Hanno, 2016. "Characteristics of Banking Crises: A Comparative Study with Geographical Contagion," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 349-388, May.
    15. Valentina Aprigliano & Danilo Liberati, 2021. "Using Credit Variables to Date Business Cycle and to Estimate the Probabilities of Recession in Real Time," Manchester School, University of Manchester, vol. 89(S1), pages 76-96, September.
    16. Caruso, Alberto & Reichlin, Lucrezia & Ricco, Giovanni, 2019. "Financial and fiscal interaction in the Euro Area crisis: This time was different," European Economic Review, Elsevier, vol. 119(C), pages 333-355.
    17. 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).
    18. Mikkel Hermansen & Oliver Röhn, 2017. "Economic resilience: The usefulness of early warning indicators in OECD countries," OECD Journal: Economic Studies, OECD Publishing, vol. 2016(1), pages 9-35.
    19. Marcel Fratzscher, 2003. "On currency crises and contagion," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 8(2), pages 109-129.
    20. Psaradakis, Zacharias & Sola, Martin, 2024. "Markov-Switching Models with State-Dependent Time-Varying Transition Probabilities," Econometrics and Statistics, Elsevier, vol. 29(C), pages 49-63.

    More about this item

    Keywords

    continuous coincident financial stress measure; early warning model; time-varying transition probability Markov switching model;
    All these keywords.

    JEL classification:

    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:ecb:ecbwps:20172057. 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: Official Publications (email available below). General contact details of provider: https://edirc.repec.org/data/emieude.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.