IDEAS home Printed from https://ideas.repec.org/p/fir/econom/wp2016_03.html
   My bibliography  Save this paper

Sovereign Debt Spreads within the Euro Area: When Fears Become Excess Fears

Author

Listed:

Abstract

The issue of divergence of sovereign spreads in the Euro area, following the deep financial crisis initiated in 2008 can only in part be related to the stability of the institutional agreements behind the common currency. There is a widespread debate as of how spreads signal a justifiable credit risk differential within the area, or, rather, reflect irrational fears and subjective and biased reasoning. In this paper we suggest a way to filter out of the observed spreads a component which we dub physiological , which is the reflection of the reaction to difference between expectations and realizations of economic fundamentals. Such a component is a function of market volatility, a proxy which represents well how new information is processed. The model parameters are estimated over a tranquil period (2000-2007) and then, in keeping with a substantial stream of literature on the topic, they are kept unchanged over the more recent and more turbulent period (2008-2015). We apply our procedure on nine Euro area countries and the US. The difference between observed and predicted values is what we label excess fears . As a result, the actual spread is much higher than it should be using as a reference a physiological view where news on macroeconomic fundamentals do indeed induce a reaction by the markets, but that this reaction was excessive when compared to what similar episodes had generated in the past.

Suggested Citation

  • Francesco Calvori & Matteo Dentella & Giampiero M. Gallo, 2016. "Sovereign Debt Spreads within the Euro Area: When Fears Become Excess Fears," Econometrics Working Papers Archive 2016_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  • Handle: RePEc:fir:econom:wp2016_03
    as

    Download full text from publisher

    File URL: http://local.disia.unifi.it/wp_disia/2016/wp_disia_2016_03.pdf
    File Function: First version, 2016-04
    Download Restriction: no

    References listed on IDEAS

    as
    1. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    2. Engle, Robert F. & Gallo, Giampiero M., 2006. "A multiple indicators model for volatility using intra-daily data," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 3-27.
    3. Pesaran M.H. & Schuermann T. & Weiner S.M., 2004. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 129-162, April.
    4. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range-Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
    5. Alessandro Beber & Michael W. Brandt & Kenneth A. Kavajecz, 2009. "Flight-to-Quality or Flight-to-Liquidity? Evidence from the Euro-Area Bond Market," Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 925-957, March.
    6. Antonio Di Cesare & Giuseppe Grande & Michele Manna & Marco Taboga, 2012. "Recent estimates of sovereign risk premia for euro-area countries," Questioni di Economia e Finanza (Occasional Papers) 128, Bank of Italy, Economic Research and International Relations Area.
    7. Lorenzo Codogno & Carlo Favero & Alessandro Missale, 2003. "Yield spreads on EMU government bonds," Economic Policy, CEPR;CES;MSH, vol. 18(37), pages 503-532, October.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Euro area; Bonds; Spread; Volatility; Fear Index;

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:fir:econom:wp2016_03. 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: (Francesco Calvori) The email address of this maintainer does not seem to be valid anymore. Please ask Francesco Calvori to update the entry or send us the correct email address. General contact details of provider: http://edirc.repec.org/data/dsfirit.html .

    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 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.

    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.