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A market-based approach to sector risk determinants and transmission in the euro area

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  • Saldías, Martín

Abstract

In a panel data framework applied to Portfolio Distance-to-Default series of corporate sectors in the euro area, this paper evaluates systemic and idiosyncratic determinants of default risk and examines how distress is transferred in and between the financial and corporate sectors since the early days of the euro. This approach takes into account observed and unobserved common factors and the presence of different degrees of cross-section dependence in the form of economic proximity. This paper contributes to the financial stability literature with a contingent claims approach to a sector-based analysis with a less dominant macro focus while being compatible with existing stress-testing methodologies in the literature. A disaggregated analysis of the different corporate and financial sectors allows for a more detailed assessment of specificities in terms of risk profile, i.e. heterogeneity of business models, risk exposures and interaction with the rest of the macro environment.

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  • Saldías, Martín, 2013. "A market-based approach to sector risk determinants and transmission in the euro area," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4534-4555.
  • Handle: RePEc:eee:jbfina:v:37:y:2013:i:11:p:4534-4555
    DOI: 10.1016/j.jbankfin.2013.01.026
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    Cited by:

    1. Turalay Kenc & Emrah Ismail Cevik & Sel Dibooglu, 2021. "Bank default indicators with volatility clustering," Annals of Finance, Springer, vol. 17(1), pages 127-151, March.
    2. Jože P. Damijan, 2014. "Corporate financial soundness and its impact on firm performance: Implications for corporate debt restructuring in Slovenia," Working Papers 168, European Bank for Reconstruction and Development, Office of the Chief Economist.
    3. Natalia Nehrebecka, 2018. "Sectoral risk assessment: evidence from Poland," IFC Bulletins chapters, in: Bank for International Settlements (ed.), External sector statistics: current issues and new challenges, volume 48, Bank for International Settlements.
    4. Turalay Kenc & Emrah Ismail Cevik, 2021. "Estimating volatility clustering and variance risk premium effects on bank default indicators," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1373-1392, November.
    5. Natalia Nehrebecka, 2018. "Sectoral risk assessment with particular emphasis on export enterprises in Poland," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 36(2), pages 677-700.
    6. Wan-Chien Chiu & Juan Ignacio Pe~na & Chih-Wei Wang, 2022. "Measuring Systemic Risk: Common Factor Exposures and Tail Dependence Effects," Papers 2202.02276, arXiv.org.
    7. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    8. Wan†Chien Chiu & Juan Ignacio Peña & Chih†Wei Wang, 2015. "Measuring Systemic Risk: Common Factor Exposures and Tail Dependence Effects," European Financial Management, European Financial Management Association, vol. 21(5), pages 833-866, November.

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    More about this item

    Keywords

    Macro-prudential analysis; Portfolio credit risk measurement; Common correlated effects; Contingent claims analysis;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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