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The Effectiveness of the ECB Announcement Channel

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DOI: 10.4236/am.2014.56097    3,007 Downloads   3,998 Views   Citations

ABSTRACT

Empirical study on the factors that induce jumps in interest rates in the euro area is still missing. In this paper, maximum likelihood estimates of I-distribution parameters are extracted using as a first step, an original linear model. According to the contribution of ([1] [2]) in the case of developing a class of Poisson-Gaussian model, we try to enhance the predictive power of this model by distinguishing between a pure Gaussian and Poisson-Gaussian distributions. Such an empirical tool permits to optimizing results through a comparative analysis dealing with the fluctuation of the Euro-interbank offered rate and its statistical descriptive behaviour. The analytical and empirical methods try to evaluate the behavioural success of the ECB intervention in setting interest rates for different maturities. Jumps in euribor interest rate can mainly be linked to surprise decisions of the European Central Bank, and the too frequent meetings of the ECB before November 2001. Despite this special event that leads to a certain lack of predictability, other few day-of-week effects are modelled to prove eventual evidence of bond market overreaction. Empirical results prove that Mondays and Wednesdays are the preponderant days. Regarding monetary policy, negative surprises induce larger jumps than positive ones.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Hachicha, A. and Masmoudi, A. (2014) The Effectiveness of the ECB Announcement Channel. Applied Mathematics, 5, 1029-1045. doi: 10.4236/am.2014.56097.

References

[1] Das, S. and Sundaram, R. (1999) The Transmission of Monetary Policy via Announcements Effects. Working Paper, UC Davis.
[2] Das, S. (2002) The Surprises Element: Jumps in Interest Rates. Journal of Econometrics, 106, 27-65.
http://dx.doi.org/10.1016/S0304-4076(01)00085-9
[3] Mundell, R. (2005) International Monetary Policy after the Euro. Printed and bound in Great Britain by MPG Books Ltd., Bodmin, 48.
[4] Balduzzi, P., Bertola, G. and Foresei, S. (1997) A Model of Target Changes and the Term Structure of Interest Rates. Journal of Monetary Economics, 39, 223-249.
http://dx.doi.org/10.1016/S0304-3932(97)00010-X
[5] Balduzzi, P., Bertola, G., Foresei, S. and Klapper, I. (1998) Interest Rate Targeting and the Dynamics of Short-Term Rates. Journal of Money, Credit and Banking, 30, 26-50.
http://dx.doi.org/10.2307/2601266
[6] Balduzzi, P., Das, P. and Foresi, S. (1998) The Central Tendency: A Second Factor in Bond Yields. Review of Economics and Statistics, 80, 60-72.
http://dx.doi.org/10.1162/003465398557339
[7] Bartolini, L., Bertola, G. and Prati, A. (2002) Day-to-Day Monetary Policy and the Volatility of the Federal Funds Rate. Journal of Money, Credit and Banking, 34, 137-159.
http://dx.doi.org/10.1353/mcb.2002.0025
[8] Hamilton, J.D. and Jordá, O. (2002) A Model for the Federal Funds Rate Target. Journal of Political Economy, 110, 1135-1167.
http://dx.doi.org/10.1086/341872
[9] Andersson, M., Hansen, L.J and Sebestyén, S. (2006) Which News Move the Euro Area Bond Market ECB Working Paper No. 631.
[10] Piazzesi, M. (2005) Bond Yields and the Federal Reserve. Journal of Political Economy, 113, 311-344.
http://dx.doi.org/10.1086/427466
[11] Prati, A., Bartolini, L. and Bertola, G. (2002) The Overnight Interbank Market: Evidence from the G-7 and the Euro Zone. Journal of Banking & Finance, 27, 2045-2083.
http://dx.doi.org/10.1016/S0378-4266(02)00320-5
[12] Moschitz, J. (2004) The Determinants of the Overnight Interest Rate in the Euro Area. ECB Working Paper No. 393.
[13] Pérez Quirós, G. and Rodríguez Mendizábal, H. (2006) The Daily Market for Funds in Europe: What Has Changed with the EMU. Journal of Money, Credit and Banking, 38, 91-118.
http://dx.doi.org/10.1353/mcb.2006.0023
[14] Duffie, D., Pan, J. and Singleton, K. (2000) Option Pricing and Transform Analysis for Affine Jump Diffusions. Graduate School of Business, Stanford University. Econometrica, 68, 1343-1376.
http://dx.doi.org/10.1111/1468-0262.00164
[15] Ball, C.A. and Torous, W.N. (1983) A Simplified Jump Process for Common Stock Returns. Journal of Financial and Quantitative Analysis, 18, 53-65.
http://dx.doi.org/10.2307/2330804
[16] Roe, B.P. and Woodroofe, M.B. (1999) Improved Probability Method for Estimating Signal in the Presence of Background. Physical Review D, 60, 053009.
http://dx.doi.org/10.1103/PhysRevD.60.053009
[17] Barlow, R. (1989) Statistics: A Guide to the Use of Statistical Methods in the Physical Sciences. Wiley, Chichester.
[18] Eadie, W.T., Drijard, D., James Roos, F.E. and Sadoulet, B. (1971) Statistical Methods in Experimental Physics. North-Holland, Amsterdam.
[19] Taylor, J. (1997) An Historical Analysis of Monetary Policy Rules. Stanford University.
[20] Cramer, H. (1946) Mathematical Methods of Statistics. Princeton University Press, Princeton.
[21] Dempster, A.P., Laird, N.M. and Rubin, D.B. (1977) Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society, Series B, 39, 1-38.
[22] ECB Press Conference: Introductory Statement, 8 November 2001, Frankfurt-am-Main. European Central Bank (2002) Monthly Bulletin, November, 2001, 2002. www.ecb.int/key/01/sp011108_1.htm
[23] Trichet, J.C. (2004) Introductory Statement to the Press Conference after the Governing Council Meeting, September.
[24] Issing, O., Gaspar, V., Tristani, O. and Vestin, D. (2006) Imperfect Knowledge and Monetary Policy. The Stone Lectures in Economics. Cambridge University Press, Cambridge.
[25] Issing, O. (2006) The Watchers Conference—Theory and Practice of Monetary Policy. Jointly Organised by the Center for Financial Studies and the European Central Bank, Frankfurt.
http://www.ecb.int/press/key/date/2006/html/sp060505_2.en.html
[26] Backus, D., Foresi, S. and Wu, L.R. (1997) Macroeconomic Foundations of Higher Order Moments in Bond Yields. Working Paper, New York University.
[27] Nadaraya, E.A. (1964) On Estimating Regression. Theory of Probability and Application, 9, 141-142,
http://dx.doi.org/10.1137/1109020
[28] Silverman, B.W. (1986) Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.
[29] Coleman, T.F. and Li, Y.Y. (1994) On the Convergence of Reflective Newton Method for Large-Scale Nonlinear Minimization Subject to Bounds. Mathematical Programming, 67, 189-224.
http://dx.doi.org/10.1007/BF01582221
[30] Coleman, T.F. and Li, Y.Y. (1996) An Interior Trust-Region Approach for Nonlinear Minimization Subject to Bounds. SIAM Journal on Optimization, 6, 418-445.
http://dx.doi.org/10.1137/0806023
[31] Bollerslev, T. and Wooldridge, J.M. (1992) Quasi-Maximum Likelihood Estimation and Inference in Dynamic Models with Timevarying Covariances. Econometric Reviews, 11, 143-172.
http://dx.doi.org/10.1080/07474939208800229

  
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