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On the interaction between market and credit risk: a factor-augmented vector autoregressive (FAVAR) approach

Author

Listed:
  • Roberta Fiori

    (Bank of Italy)

  • Simonetta Iannotti

    (Bank for International Settlements)

Abstract

The aim of the paper is to understand the interaction between market and credit risk. Using a comprehensive set of Italian data, we apply a factor model to identify the common sources of risk driving fluctuations in the real and financial sectors. The common latent factors are then inserted in a VAR framework via a Factor Augmented Vector Autoregressive (FAVAR) approach to analyse the role of risk interactions with monetary policy shocks. We find that the impact of a restrictive monetary policy shock on credit risk is amplified when considering the feedback effect deriving from macroeconomic and equity market risk. Thus, neglecting dynamic interactions among risks may lead to biased estimates of the overall risk measure. The approach provides a framework for modelling macro and financial feedback dynamics, shedding some light on the complex interdependence between the financial sector and the real economy.

Suggested Citation

  • Roberta Fiori & Simonetta Iannotti, 2010. "On the interaction between market and credit risk: a factor-augmented vector autoregressive (FAVAR) approach," Temi di discussione (Economic working papers) 779, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_779_10
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    File URL: http://www.bancaditalia.it/pubblicazioni/temi-discussione/2010/2010-0779/en_tema_779.pdf
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    References listed on IDEAS

    as
    1. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    2. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    3. Sydney C. Ludvigson & Serena Ng, 2009. "A Factor Analysis of Bond Risk Premia," NBER Working Papers 15188, National Bureau of Economic Research, Inc.
    4. Moench, Emanuel, 2008. "Forecasting the yield curve in a data-rich environment: A no-arbitrage factor-augmented VAR approach," Journal of Econometrics, Elsevier, vol. 146(1), pages 26-43, September.
    5. Bai, Jushan & Ng, Serena, 2006. "Evaluating latent and observed factors in macroeconomics and finance," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 507-537.
    6. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    7. Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May.
    8. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    9. 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.
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    Cited by:

    1. Ahmet Akca & Ethem Çanakoğlu, 2021. "Adaptive stochastic risk estimation of firm operating profit," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 48(3), pages 463-504, September.
    2. Bogdan-Gabriel MOINESCU, 2012. "Determinants Of Nonperforming Loans In Central And Eastern European Countries: Macroeconomic Indicators And Credit Discipline," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 10, pages 47-58, December.

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    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
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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