IDEAS home Printed from https://ideas.repec.org/a/cup/jfinqa/v49y2014i03p575-598_00.html
   My bibliography  Save this article

Spillover Effects among Financial Institutions: A State-Dependent Sensitivity Value-at-Risk Approach

Author

Listed:
  • Adams, Zeno
  • Füss, Roland
  • Gropp, Reint

Abstract

In this paper, we develop a state-dependent sensitivity value-at-risk (SDSVaR) approach that enables us to quantify the direction, size, and duration of risk spillovers among financial institutions as a function of the state of financial markets (tranquil, normal, and volatile). For four sets of major financial institutions (commercial banks, investment banks, hedge funds, and insurance companies), we show that while small during normal times, equivalent shocks lead to considerable spillover effects in volatile market periods. Commercial banks and, especially, hedge funds appear to play a major role in the transmission of shocks to other financial institutions.

Suggested Citation

  • Adams, Zeno & Füss, Roland & Gropp, Reint, 2014. "Spillover Effects among Financial Institutions: A State-Dependent Sensitivity Value-at-Risk Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 575-598, June.
  • Handle: RePEc:cup:jfinqa:v:49:y:2014:i:03:p:575-598_00
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S0022109014000325/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. King, Michael R. & Maier, Philipp, 2009. "Hedge funds and financial stability: Regulating prime brokers will mitigate systemic risks," Journal of Financial Stability, Elsevier, vol. 5(3), pages 283-297, September.
    2. repec:hrv:faseco:33077921 is not listed on IDEAS
    3. Lorenzo Cappiello & Bruno Gérard & Arjan Kadareja & Simone Manganelli, 2014. "Measuring Comovements by Regression Quantiles," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 12(4), pages 645-678.
    4. Danielsson, Jon & Taylor, Ashley & Zigrand, Jean-Pierre, 2004. "Highwaymen or heroes: should hedge funds be regulated?," LSE Research Online Documents on Economics 24782, London School of Economics and Political Science, LSE Library.
    5. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    6. Reint Gropp & Marco Lo Duca & Jukka Vesala, 2009. "Cross-Border Bank Contagion in Europe," International Journal of Central Banking, International Journal of Central Banking, vol. 5(1), pages 97-139, March.
    7. Klaus, Benjamin & Rzepkowski, Bronka, 2009. "Risk spillover among hedge funds: The role of redemptions and fund failures," Working Paper Series 1112, European Central Bank.
    8. Hott, Christian, 2009. "Herding behavior in asset markets," Journal of Financial Stability, Elsevier, vol. 5(1), pages 35-56, January.
    Full references (including those not matched with items on IDEAS)

    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. Caporin, Massimiliano & Pelizzon, Loriana & Ravazzolo, Francesco & Rigobon, Roberto, 2018. "Measuring sovereign contagion in Europe," Journal of Financial Stability, Elsevier, vol. 34(C), pages 150-181.
    2. Zhu, Xuening & Wang, Weining & Wang, Hansheng & Härdle, Wolfgang Karl, 2019. "Network quantile autoregression," Journal of Econometrics, Elsevier, vol. 212(1), pages 345-358.
    3. Henry, Jérôme & Zimmermann, Maik & Leber, Miha & Kolb, Markus & Grodzicki, Maciej & Amzallag, Adrien & Vouldis, Angelos & Hałaj, Grzegorz & Pancaro, Cosimo & Gross, Marco & Baudino, Patrizia & Sydow, , 2013. "A macro stress testing framework for assessing systemic risks in the banking sector," Occasional Paper Series 152, European Central Bank.
    4. Apostolos Thomadakis, 2012. "Measuring Financial Contagion with Extreme Coexceedances," School of Economics Discussion Papers 1112, School of Economics, University of Surrey.
    5. Boyson, Nicole M. & Stahel, Christof W. & Stulz, Rene M., 2011. "Liquidity Shocks and Hedge Fund Contagion," Working Paper Series 2011-12, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    6. Dimitrios Bisias & Mark Flood & Andrew W. Lo & Stavros Valavanis, 2012. "A Survey of Systemic Risk Analytics," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 255-296, October.
    7. Nicole M. Boyson & Christof W. Stahel & René M. Stulz, 2010. "Hedge Fund Contagion and Liquidity Shocks," Journal of Finance, American Finance Association, vol. 65(5), pages 1789-1816, October.
    8. Duygun, Meryem & Tunaru, Radu & Vioto, Davide, 2021. "Herding by corporates in the US and the Eurozone through different market conditions," Journal of International Money and Finance, Elsevier, vol. 110(C).
    9. Raffaella Calabrese & Silvia Osmetti, 2014. "Modelling cross-border systemic risk in the European banking sector: a copula approach," Papers 1411.1348, arXiv.org.
    10. Grzegorz Hałaj & Christoffer Kok, 2013. "Assessing interbank contagion using simulated networks," Computational Management Science, Springer, vol. 10(2), pages 157-186, June.
    11. Kok, Christoffer & Gross, Marco, 2013. "Measuring contagion potential among sovereigns and banks using a mixed-cross-section GVAR," Working Paper Series 1570, European Central Bank.
    12. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    13. Tabuga, Aubrey D., 2007. "International Remittances and Household Expenditures: the Philippine Case," Discussion Papers DP 2007-18, Philippine Institute for Development Studies.
    14. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    15. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    16. Javier Alejo & Nicolás Badaracco, 2015. "Counterfactual Distributions in Bivariate Models—A Conditional Quantile Approach," Econometrics, MDPI, Open Access Journal, vol. 3(4), pages 1-14, November.
    17. Zhao, Zhibiao & Wu, Wei Biao, 2009. "Nonparametric inference of discretely sampled stable Lévy processes," Journal of Econometrics, Elsevier, vol. 153(1), pages 83-92, November.
    18. Alexandre Belloni & Victor Chernozhukov & Kengo Kato, 2019. "Valid Post-Selection Inference in High-Dimensional Approximately Sparse Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 749-758, April.
    19. Héctor Manuel Zárate S., 2005. "Cambios en la estructura salarial: una historia desde la regresión cuanfílica," Monetaria, Centro de Estudios Monetarios Latinoamericanos, CEMLA, vol. 0(4), pages 339-364, octubre-d.
    20. Efobi, Uchenna & Asongu, Simplice & Okafor, Chinelo & Tchamyou, Vanessa & Tanankem, Belmondo, 2016. "Diaspora Remittance Inflow, Financial Development and the Industrialisation of Africa," MPRA Paper 76121, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

    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:cup:jfinqa:v:49:y:2014:i:03:p:575-598_00. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://www.cambridge.org/jfq .

    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: Keith Waters (email available below). General contact details of provider: https://www.cambridge.org/jfq .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.