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Forecasting Financial Crises and Contagion in Asia using Dynamic Factor Analysis

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  • Andrea Cipollini

    (University of Essex)

  • George Kapetanios

    (Queen Mary, University of London)

Abstract

In this paper we use a Dynamic Factor model to retrieve vulnerability indicators able to predict financial turmoil. A stochastic simulation experiment is then used to produce the corresponding probability forecasts regarding the currency crisis events a®ecting a number of East Asian countries during the 1997-1998 period. The Dynamic factor model improves upon a number of competing model, in terms of out of sample forecasting performance

Suggested Citation

  • Andrea Cipollini & George Kapetanios, 2006. "Forecasting Financial Crises and Contagion in Asia using Dynamic Factor Analysis," Computing in Economics and Finance 2006 477, Society for Computational Economics.
    • Handle: RePEc:sce:scecfa:477
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    References listed on IDEAS

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    Cited by:

    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. 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.
    3. Kim, Hyeongwoo & Son, Jisoo, 2024. "What charge-off rates are predictable by macroeconomic latent factors?," Journal of Financial Stability, Elsevier, vol. 74(C).
    4. Kim, Hyeongwoo & Ko, Kyunghwan, 2020. "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, vol. 88(C), pages 341-355.
    5. Briceño Avalos, Hernán Ricardo, 2003. "Tipos de Cambio Cuasi-fijo y Posibilidad de Crisis Financieras: Solarizar o Dolarizar la Economía Peruana? [Fixed Exchange Rates and Possibilities of Financial Crisis: Solarizar or Dollarization of," MPRA Paper 42029, University Library of Munich, Germany.
    6. 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.
    7. Tabak, Benjamin M. & de Castro Miranda, Rodrigo & da Silva Medeiros, Maurício, 2016. "Contagion in CDS, banking and equity markets," Economic Systems, Elsevier, vol. 40(1), pages 120-134.
    8. Boonman, Tjeerd M. & Jacobs, Jan P.A.M. & Kuper, Gerard H., 2012. "The Global Financial Crisis and currency crises in Latin America," Research Report 12005-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    9. Priyadarshi Dash, 2017. "Predicting Financial Crises: A Study of Asian Economies," Global Business Review, International Management Institute, vol. 18(5), pages 1262-1277, October.
    10. 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.
    11. Corder, Matthew & Weale, Martin, 2011. "Banking crises and recessions: what can leading indicators tell us?," Discussion Papers 33, Monetary Policy Committee Unit, Bank of England.
    12. repec:dgr:rugsom:12005-eef is not listed on IDEAS
    13. 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.
    14. Tjeerd M. Boonman & Jan P.A.M. Jacobs & Gerard H. Kuper, 2011. "Why didn't the Global Financial Crisis hit Latin America?," CIRANO Working Papers 2011s-63, CIRANO.

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    More about this item

    Keywords

    Financial Contagion; Dynamic Factor Model; Stochastic Simulation;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • F34 - International Economics - - International Finance - - - International Lending and Debt Problems

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