IDEAS home Printed from https://ideas.repec.org/p/abn/wpaper/auwp2016-15.html
   My bibliography  Save this paper

Forecasting Financial Vulnerability in the US: A Factor Model Approach

Author

Listed:
  • Hyeongwoo Kim
  • Wen Shi

Abstract

This paper presents a factor-based forecasting model for the financial market vulnerability, measured by changes in the Cleveland Financial Stress Index (CFSI). We estimate latent common factors via the method of the principal components from 170 monthly frequency macroeconomic data in order to out-of-sample forecast the CFSI. Our factor models outperform both the random walk and the autoregressive benchmark models in out-of-sample predictability at least for the short-term forecast horizons, which is a desirable feature since financial crises often come to a surprise realization. Interestingly, the first common factor, which plays a key role in predicting the financial vulnerability index, seems to be more closely related with real activity variables rather than nominal variables. We also present a binary choice version factor model that estimates the probability of the high stress regime successfully.

Suggested Citation

  • Hyeongwoo Kim & Wen Shi, 2016. "Forecasting Financial Vulnerability in the US: A Factor Model Approach," Auburn Economics Working Paper Series auwp2016-15, Department of Economics, Auburn University.
  • Handle: RePEc:abn:wpaper:auwp2016-15
    as

    Download full text from publisher

    File URL: https://cla.auburn.edu/econwp/Archives/2016/2016-15.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cipollini, A. & Kapetanios, G., 2009. "Forecasting financial crises and contagion in Asia using dynamic factor analysis," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 188-200, March.
    2. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "Varieties of Crises and Their Dates," Introductory Chapters, in: This Time Is Different: Eight Centuries of Financial Folly, Princeton University Press.
    3. Hyeongwoo Kim & Wen Shi & Hyun Hak Kim, 2020. "Forecasting financial stress indices in Korea: a factor model approach," Empirical Economics, Springer, vol. 59(6), pages 2859-2898, December.
    4. 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.
    5. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency Crashes in Emerging Markets: Empirical Indicators," Center for International and Development Economics Research (CIDER) Working Papers 233424, University of California-Berkeley, Department of Economics.
    6. Frankel, Jeffrey A. & Rose, Andrew K., 1996. "Currency crashes in emerging markets: An empirical treatment," Journal of International Economics, Elsevier, vol. 41(3-4), pages 351-366, November.
    7. Jeffrey D. Sachs & Aaron Tornell & Andrés Velasco, 1996. "Financial Crises in Emerging Markets: The Lessons from 1995," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(1), pages 147-216.
    8. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers 48/2018, Deutsche Bundesbank.
    9. Scott Brave & R. Andrew Butters, 2012. "Diagnosing the Financial System: Financial Conditions and Financial Stress," International Journal of Central Banking, International Journal of Central Banking, vol. 8(2), pages 191-239, June.
    10. Frankel, Jeffrey & Saravelos, George, 2012. "Can leading indicators assess country vulnerability? Evidence from the 2008–09 global financial crisis," Journal of International Economics, Elsevier, vol. 87(2), pages 216-231.
    11. Reinhart, Karmen & Rogoff, Kenneth, 2009. ""This time is different": panorama of eight centuries of financial crises," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 77-114, March.
    12. Robert Vermeulen & Marco Hoeberichts & Bořek Vašíček & Diana Žigraiová & Kateřina Šmídková & Jakob Haan, 2015. "Financial Stress Indices and Financial Crises," Open Economies Review, Springer, vol. 26(3), pages 383-406, July.
    13. El-Shagi, M. & Knedlik, T. & von Schweinitz, G., 2013. "Predicting financial crises: The (statistical) significance of the signals approach," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 76-103.
    14. Duprey, Thibaut & Klaus, Benjamin, 2017. "How to predict financial stress? An assessment of Markov switching models," Working Paper Series 2057, European Central Bank.
    15. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    16. Andrew Berg & Eduardo Borensztein & Catherine Pattillo, 2005. "Assessing Early Warning Systems: How Have They Worked in Practice?," IMF Staff Papers, Palgrave Macmillan, vol. 52(3), pages 1-5.
    17. Carmen M. Reinhart & Kenneth S. Rogoff, 2014. "This Time is Different: A Panoramic View of Eight Centuries of Financial Crises," Annals of Economics and Finance, Society for AEF, vol. 15(2), pages 215-268, November.
    18. Phillip J. Monin, 2019. "The OFR Financial Stress Index," Risks, MDPI, vol. 7(1), pages 1-21, February.
    19. Berg, Andrew & Pattillo, Catherine, 1999. "Predicting currency crises:: The indicators approach and an alternative," Journal of International Money and Finance, Elsevier, vol. 18(4), pages 561-586, August.
    20. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-966, July.
    21. Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
    22. Christensen, Ian & Li, Fuchun, 2014. "Predicting financial stress events: A signal extraction approach," Journal of Financial Stability, Elsevier, vol. 14(C), pages 54-65.
    23. Robert Vermeulen & Marco Hoeberichts & Bořek Vašíček & Diana Žigraiová & Kateřina Šmídková & Jakob Haan, 2015. "Financial Stress Indices and Financial Crises," Open Economies Review, Springer, vol. 26(3), pages 383-406, July.
    24. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    25. Carmen M. Reinhart & Kenneth S. Rogoff, 2014. "Recovery from Financial Crises: Evidence from 100 Episodes," American Economic Review, American Economic Association, vol. 104(5), pages 50-55, May.
    26. Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kang, Miao & Kapadia, Sujit & Simsek, Özgür, 2020. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Bank of England working papers 848, Bank of England.
    27. Brüggemann, Axel & Linne, Thomas, 1999. "How Good are Leading Indicators for Currency and Banking Crises in Central and Eastern Europe? An Empirical Test," IWH Discussion Papers 95/1999, Halle Institute for Economic Research (IWH).
    28. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    29. Girton, Lance & Roper, Don, 1977. "A Monetary Model of Exchange Market Pressure Applied to the Postwar Canadian Experience," American Economic Review, American Economic Association, vol. 67(4), pages 537-548, September.
    30. Vašíček, Bořek & Žigraiová, Diana & Hoeberichts, Marco & Vermeulen, Robert & Šmídková, Kateřina & de Haan, Jakob, 2017. "Leading indicators of financial stress: New evidence," Journal of Financial Stability, Elsevier, vol. 28(C), pages 240-257.
    31. Craig S. Hakkio & William R. Keeton, 2009. "Financial stress: what is it, how can it be measured, and why does it matter?," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q II), pages 5-50.
    32. Illing, Mark & Liu, Ying, 2006. "Measuring financial stress in a developed country: An application to Canada," Journal of Financial Stability, Elsevier, vol. 2(3), pages 243-265, October.
    33. Jan Willem Slingenberg & Jakob de Haan, 2011. "Forecasting Financial Stress," DNB Working Papers 292, Netherlands Central Bank, Research Department.
    34. Hali J. Edison, 2003. "Do indicators of financial crises work? An evaluation of an early warning system," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 8(1), pages 11-53.
    35. Kevin L. Kliesen & Douglas C. Smith, 2010. "Measuring financial market stress," Economic Synopses, Federal Reserve Bank of St. Louis.
    36. Mr. Christian B. Mulder & Mr. Matthieu Bussière, 1999. "External Vulnerability in Emerging Market Economies: How High Liquidity Can Offset Weak Fundamentals and the Effects of Contagion," IMF Working Papers 1999/088, International Monetary Fund.
    37. Mr. Evan C Tanner, 2002. "Exchange Market Pressure, Currency Crises, and Monetary Policy: Additional Evidence From Emerging Markets," IMF Working Papers 2002/014, International Monetary Fund.
    38. 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.
    39. Markus Holopainen & Peter Sarlin, 2017. "Toward robust early-warning models: a horse race, ensembles and model uncertainty," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1933-1963, December.
    40. Miroslav Misina & Greg Tkacz, 2009. "Credit, Asset Prices, and Financial Stress," International Journal of Central Banking, International Journal of Central Banking, vol. 5(4), pages 95-122, December.
    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. Kaelo Ntwaepelo & Grivas Chiyaba, 2022. "Financial Stability Surveillance Tools: Evaluating the Performance of Stress Indices," Economics Discussion Papers em-dp2022-06, Department of Economics, University of Reading.
    2. Santino Del Fava & Rangan Gupta & Christian Pierdzioch & Lavinia Rognone, 2023. "Forecasting International Financial Stress: The Role of Climate Risks," Working Papers 202329, University of Pretoria, Department of Economics.
    3. Kim, Hyeongwoo & Son, Jisoo, 2023. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," MPRA Paper 116880, University Library of Munich, Germany.

    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. Hyeongwoo Kim & Wen Shi & Hyun Hak Kim, 2020. "Forecasting financial stress indices in Korea: a factor model approach," Empirical Economics, Springer, vol. 59(6), pages 2859-2898, December.
    2. Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
    3. Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: Partial Least Squares Factor Model Approach," Working Papers 2017-14, Economic Research Institute, Bank of Korea.
    4. Christofides, Charis & Eicher, Theo S. & Papageorgiou, Chris, 2016. "Did established Early Warning Signals predict the 2008 crises?," European Economic Review, Elsevier, vol. 81(C), pages 103-114.
    5. 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.
    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. Hyeongwoo Kim & Jisoo Son, 2023. "Forecasting Net Charge-Off Rates of Large U.S. Bank Holding Companies using Macroeconomic Latent Factors," Auburn Economics Working Paper Series auwp2023-02, Department of Economics, Auburn University.
    8. Mansour-Ichrakieh, Layal & Zeaiter, Hussein, 2019. "The role of geopolitical risks on the Turkish economy opportunity or threat," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    9. Lanbiao Liu & Chen Chen & Bo Wang, 2022. "Predicting financial crises with machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 871-910, August.
    10. Vašíček, Bořek & Žigraiová, Diana & Hoeberichts, Marco & Vermeulen, Robert & Šmídková, Kateřina & de Haan, Jakob, 2017. "Leading indicators of financial stress: New evidence," Journal of Financial Stability, Elsevier, vol. 28(C), pages 240-257.
    11. Markus Holopainen & Peter Sarlin, 2015. "Toward robust early-warning models: A horse race, ensembles and model uncertainty," Papers 1501.04682, arXiv.org, revised Apr 2016.
    12. Hyeongwoo Kim & Jisoo Son, 2023. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series auwp2023-06, Department of Economics, Auburn University.
    13. 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).
    14. Yanping Zhao & Jakob Haan & Bert Scholtens & Haizhen Yang, 2014. "Leading Indicators of Currency Crises: Are They the Same in Different Exchange Rate Regimes?," Open Economies Review, Springer, vol. 25(5), pages 937-957, November.
    15. Rakesh Padhan & K. P. Prabheesh, 2019. "Effectiveness Of Early Warning Models: A Critical Review And New Agenda For Future Direction," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 457-484.
    16. Frankel, Jeffrey & Saravelos, George, 2012. "Can leading indicators assess country vulnerability? Evidence from the 2008–09 global financial crisis," Journal of International Economics, Elsevier, vol. 87(2), pages 216-231.
    17. Tristan Nguyen & Nguyen Ngoc Duy, 2017. "Developing an Early Warning System for Financial Crises in Vietnam," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 7(4), pages 413-430, April.
    18. Cipollini, A. & Kapetanios, G., 2009. "Forecasting financial crises and contagion in Asia using dynamic factor analysis," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 188-200, March.
    19. Oet, Mikhail V. & Gramlich, Dieter & Sarlin, Peter, 2016. "Evaluating measures of adverse financial conditions," Journal of Financial Stability, Elsevier, vol. 27(C), pages 234-249.
    20. Mustapha Djennas & Mohamed Benbouziane & Meriem Djennas, 2011. "An Approach of Combining Empirical Mode Decomposition and Neural Network Learning for Currency Crisis Forecasting," Working Papers 627, Economic Research Forum, revised 09 Jan 2011.

    More about this item

    Keywords

    Financial Stress Index; Method of the Principal Component; Out-of-Sample Forecast; Ratio of Root Mean Square Prediction Error; Diebold-Mariano-West Statistic; Ordered Probit Model;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:abn:wpaper:auwp2016-15. 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: Hyeongwoo Kim (email available below). General contact details of provider: https://edirc.repec.org/data/deaubus.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.