IDEAS home Printed from https://ideas.repec.org/p/ide/wpaper/20628.html
   My bibliography  Save this paper

Cyclicality and Term Structure of Value-at-Risk in Europe

Author

Listed:
  • Bec, Frédérique
  • Gollier, Christian

Abstract

This paper explores empirically the link between stocks returns Value-at-Risk (VaR) and the state of financial markets cycle. The econometric analysis is based on a simple vector autoregression setup. Using quarterly data from 1970Q4 to 2008Q4 for France, Germany and the United-Kingdom, it turns out that the k-year VaR of equities is actually dependent on the cycle phase: the expected losses as measured by the VaR are smaller in recession times than expansion periods, whatever the country and the horizon. These results strongly suggest that the European rules regarding the solvency capital requirements for insurance companies should adapt to the state of the financial market’s cycle.

Suggested Citation

  • Bec, Frédérique & Gollier, Christian, 2009. "Cyclicality and Term Structure of Value-at-Risk in Europe," IDEI Working Papers 587, Institut d'Économie Industrielle (IDEI), Toulouse.
  • Handle: RePEc:ide:wpaper:20628
    as

    Download full text from publisher

    File URL: http://idei.fr/sites/default/files/medias/doc/by/gollier/cyclicality.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2010. "Testing for co-integration in vector autoregressions with non-stationary volatility," Journal of Econometrics, Elsevier, vol. 158(1), pages 7-24, September.
    2. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    3. Campbell, John Y, 1991. "A Variance Decomposition for Stock Returns," Economic Journal, Royal Economic Society, vol. 101(405), pages 157-179, March.
    4. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    5. Mise, Emi & Kim, Tae-Hwan & Newbold, Paul, 2005. "On suboptimality of the Hodrick-Prescott filter at time series endpoints," Journal of Macroeconomics, Elsevier, vol. 27(1), pages 53-67, March.
    6. Guillaume Plantin & Haresh Sapra & Hyun Song Shin, 2008. "Marking‐to‐Market: Panacea or Pandora's Box?," Journal of Accounting Research, Wiley Blackwell, vol. 46(2), pages 435-460, May.
    7. Ľuboš Pástor & Robert F. Stambaugh, 2012. "Are Stocks Really Less Volatile in the Long Run?," Journal of Finance, American Finance Association, vol. 67(2), pages 431-478, April.
    8. Rochet, J C., 2008. "Procyclicality of financial systems: is there a need to modify current accounting and regulatory rules?," Financial Stability Review, Banque de France, issue 12, pages 95-99, October.
    9. J. B. Taylor & M. Woodford (ed.), 1999. "Handbook of Macroeconomics," Handbook of Macroeconomics, Elsevier, edition 1, volume 1, number 1.
    10. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    11. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
    12. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, February.
    13. Anders Møller Christensen & Heino Bohn Nielsen, 2009. "Monetary Policy in the Greenspan Era: A Time Series Analysis of Rules vs. Discretion," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 69-89, February.
    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. Lucyna Gornicka & Sweder van Wijnbergen, 2013. "Financial Frictions and the Credit Transmission Channel: Capital Requirements and Bank Capital," Tinbergen Institute Discussion Papers 13-013/VI/DSF50, Tinbergen Institute.

    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. Frédérique Bec & Christian Gollier, 2009. "Term Structure and Cyclicity of Value-at-Risk: Consequences for the Solvency Capital Requirement," CESifo Working Paper Series 2596, CESifo.
    2. Bec, Frédérique & Gollier, Christian, 2014. "Cyclicality and term structure of Value-at-Risk within a threshold autoregression setup," IDEI Working Papers 835, Institut d'Économie Industrielle (IDEI), Toulouse.
    3. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    4. Mertens, Elmar, 2010. "Structural shocks and the comovements between output and interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1171-1186, June.
    5. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
    6. Fukuda, Kosei, 2012. "Illustrating extraordinary shocks causing trend breaks," Economic Modelling, Elsevier, vol. 29(4), pages 1045-1052.
    7. Jylhä, Petri & Lof, Matthijs, 2022. "Mind the Basel gap," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    8. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.
    9. Aastveit, Knut Are & Trovik, Tørres, 2014. "Estimating the output gap in real time: A factor model approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 180-193.
    10. Amado Peiró, 2000. "Economic Comovements In European Countries," Working Papers. Serie EC 2000-19, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    11. Maravall, A. & del Rio, A., 2007. "Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 975-998, October.
    12. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 9473, Victoria University of Wellington, School of Economics and Finance.
    13. Richard Dennis, 1997. "A measure of monetary conditions," Reserve Bank of New Zealand Discussion Paper Series G97/1, Reserve Bank of New Zealand.
    14. Woitek, Ulrich, 2003. "Height cycles in the 18th and 19th centuries," Economics & Human Biology, Elsevier, vol. 1(2), pages 243-257, June.
    15. João Sousa Andrade & António Portugal Duarte, 2014. "Output-gaps in the PIIGS Economies: An Ingredient of a Greek Tragedy," GEMF Working Papers 2014-06, GEMF, Faculty of Economics, University of Coimbra.
    16. Demetrescu, Matei & Georgiev, Iliyan & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2022. "Testing for episodic predictability in stock returns," Journal of Econometrics, Elsevier, vol. 227(1), pages 85-113.
    17. Woon Gyu Choi, 2007. "Measuring Interest Rates as Determined by Thrift and Productivity," Annals of Economics and Finance, Society for AEF, vol. 8(1), pages 167-195, May.
    18. Bianchi, Francesco, 2016. "Methods for measuring expectations and uncertainty in Markov-switching models," Journal of Econometrics, Elsevier, vol. 190(1), pages 79-99.
    19. Arranz, Miguel A. & Escribano, Álvaro & Mármol, Francesc, 2002. "Effects of Applying Linear and Nonlinear Filters on Tests for Unit Roots with Additive Outliers," UC3M Working papers. Economics we20091101, Universidad Carlos III de Madrid. Departamento de Economía.
    20. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.

    More about this item

    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:ide:wpaper:20628. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/idtlsfr.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.