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Interest rate expectations and uncertainty during ECB governing council days: evidence from intraday implied densities of 3-month Euribor

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  • Puigvert Gutiérrez, Josep Maria
  • Vergote, Olivier

Abstract

This paper analyses changes in short-term interest rate expectations and uncertainty during ECB Governing Council days. For this purpose, it first extends the estimation of risk-neutral probability density functions up to tick frequency. In particular, the non-parametric estimator of these densities, which is based on fitting implied volatility curves, is applied to estimate intraday expectations of threemonth EURIBOR three months ahead. The estimator proves to be robust to market microstructure noise and able to capture meaningful changes in expectations. Estimates of the noise impact on the statistical moments of the densities further enhance the interpretation. In addition, the paper assesses the impact of the ECB communication during Governing Council days. The results show that the whole density may react to the communication and that such repositioning of market participants JEL Classification: C14, E43, E52, E58, E61

Suggested Citation

  • Puigvert Gutiérrez, Josep Maria & Vergote, Olivier, 2011. "Interest rate expectations and uncertainty during ECB governing council days: evidence from intraday implied densities of 3-month Euribor," Working Paper Series 1391, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20111391
    Note: 1503965
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    1. Claus Brand & Daniel Buncic & Jarkko Turunen, 2010. "The Impact of ECB Monetary Policy Decisions and Communication on the Yield Curve," Journal of the European Economic Association, MIT Press, vol. 8(6), pages 1266-1298, December.
    2. Luca Agnello & Jacopo Cimadomo, 2012. "Discretionary Fiscal Policies over the Cycle: New Evidence Based on the ESCB Disaggregated Approach," International Journal of Central Banking, International Journal of Central Banking, vol. 8(2), pages 43-85, June.
    3. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    4. Michael Ehrmann & Marcel Fratzscher, 2009. "Explaining Monetary Policy in Press Conferences," International Journal of Central Banking, International Journal of Central Banking, vol. 5(2), pages 42-84, June.
    5. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    6. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    7. Bødskov Andersen, Allan & Wagener, Tom, 2002. "Extracting risk neutral probability densities by fitting implied volatility smiles: some methodological points and an application to the 3M Euribor futures option prices," Working Paper Series 198, European Central Bank.
    8. de Vincent-Humphreys, Rupert & Puigvert Gutiérrez, Josep Maria, 2010. "A quantitative mirror on the Euribor market using implied probability density functions," Working Paper Series 1281, European Central Bank.
    9. Cox, John C. & Ross, Stephen A., 1976. "The valuation of options for alternative stochastic processes," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 145-166.
    10. Josep Puigvert-Gutiérrez & Rupert Vincent-Humphreys, 2012. "A Quantitative Mirror on the Euribor Market Using Implied Probability Density Functions," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 2(1), pages 1-31, June.
    11. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
    12. Bhupinder Bahra, 1997. "Implied risk-neutral probability density functions from option prices: theory and application," Bank of England working papers 66, Bank of England.
    13. Allan M. Malz, 1998. "Option Prices And The Probability Distribution Of Exchange Rates," World Scientific Book Chapters, in: Zhaohui Chen (ed.), Currency Options And Exchange Rate Economics, chapter 7, pages 108-137, World Scientific Publishing Co. Pte. Ltd..
    14. Bliss, Robert R. & Panigirtzoglou, Nikolaos, 2002. "Testing the stability of implied probability density functions," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 381-422, March.
    15. Andersson, Magnus, 2007. "Using intraday data to gauge financial market responses to Fed and ECB monetary policy decisions," Working Paper Series 726, European Central Bank.
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    Cited by:

    1. A. Leonhardt & A. W. Rathgeber & J. Stadler & S. Stöckl, 2015. "Pricing fx forwards in OTC markets - new evidence for the pricing mechanism when faced with counterparty risk," Applied Economics, Taylor & Francis Journals, vol. 47(27), pages 2860-2877, June.
    2. Roberto Casarin & Fabrizio Leisen & German Molina & Enrique ter Horst, 2014. "A Bayesian Beta Markov Random Field Calibration of the Term Structure of Implied Risk Neutral Densities," Papers 1409.1956, arXiv.org.
    3. Dalderop, Jeroen, 2020. "Nonparametric filtering of conditional state-price densities," Journal of Econometrics, Elsevier, vol. 214(2), pages 295-325.
    4. Jung, Alexander, 2016. "Have monetary data releases helped markets to predict the interest rate decisions of the European Central Bank?," Working Paper Series 1926, European Central Bank.
    5. Jukka Sihvonen & Sami Vähämaa, 2014. "Forward‐Looking Monetary Policy Rules and Option‐Implied Interest Rate Expectations," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(4), pages 346-373, April.
    6. Rui Fan & Stephen J. Taylor & Matteo Sandri, 2018. "Density forecast comparisons for stock prices, obtained from high‐frequency returns and daily option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 83-103, January.

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    More about this item

    Keywords

    announcement effects; central bank communication; interest rate expectations; intraday analysis; option-implied densities; risk-neutral probability density functions; tick data;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination

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