IDEAS home Printed from https://ideas.repec.org/p/sce/scecf2/3.html
   My bibliography  Save this paper

Are Capital Markets Efficient? Evidence from the Term Structure of Interest Rates in Europe

Author

Listed:
  • Andrew Hughes Hallett
  • Christian R Richter

Abstract

This paper investigates the uncovered interest parity hypothesis in an unusual way. We provide empirical evidence on the efficiency of capital markets using a time domain approach. However, a common prediction from theoretical models is that inefficient capital markets cause greater volatility of the observed time series. By using cross spectral analysis we are able to test this proposition directly. We show, in particular, how this can be done for time-varying models and time-varying spectra. We use our techniques to examine the changing stability of the relationship between British and German interest rates during and following the ERM crisis of 1992/3.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Andrew Hughes Hallett & Christian R Richter, 2002. "Are Capital Markets Efficient? Evidence from the Term Structure of Interest Rates in Europe," Computing in Economics and Finance 2002 3, Society for Computational Economics.
  • Handle: RePEc:sce:scecf2:3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mario Cunha, 2010. "Modelling the Cyclical Behaviour of Wine Production in the Douro Region Using a Time-Varying Parameters Approach," Working Papers 2010.1, International Network for Economic Research - INFER.
    2. Christian Richter & Andrew Hughes Hallett, 2005. "A Time-Frequency Analysis of the Coherences of the US Business," Computing in Economics and Finance 2005 45, Society for Computational Economics.
    3. Essahbi Essaadi & Mohamed Boutahar, 2010. "A Measure of Variability in Comovement for Economic Variables: a Time-Varying Coherence Function Approach," Economics Bulletin, AccessEcon, vol. 30(2), pages 1054-1070.
    4. Francis In & Sangbae Kim, 2012. "An Introduction to Wavelet Theory in Finance:A Wavelet Multiscale Approach," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8431, December.
    5. Kim Sangbae & In Francis Haeuck, 2003. "The Relationship Between Financial Variables and Real Economic Activity: Evidence From Spectral and Wavelet Analyses," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-18, December.
    6. Andrew Hughes Hallett & Christian Richter, 2009. "Economics in the Backyard: How Much Convergence is there between China and her Special Regions?," The World Economy, Wiley Blackwell, vol. 32(6), pages 819-861, June.
    7. TRIANDAFIL, Cristina Maria, 2013. "Sustainability of convergence in the context of macro-prudential policies in the European Union," Working Papers of National Institute for Economic Research 130618, Institutul National de Cercetari Economice (INCE).
    8. Maria do Rosario CORREIA & Christian GOKUS & Andrew Hughes HALLETT & Christian R. RICHTER, 2016. "A Dynamic Analysis of the Determinants of the Greek Credit Default Swaps," Journal of Economics and Political Economy, KSP Journals, vol. 3(2), pages 350-376, June.
    9. Bachar Fakhry & Christian Richter, 2015. "Is the sovereign debt market efficient? Evidence from the US and German sovereign debt markets," International Economics and Economic Policy, Springer, vol. 12(3), pages 339-357, September.
    10. Andrew Hallett & Christian Richter, 2006. "Measuring the Degree of Convergence among European Business Cycles," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 229-259, May.
    11. repec:hal:journl:halshs-00333582 is not listed on IDEAS

    More about this item

    Keywords

    Interest Rates; Time Dependent Spectral Analysis; Behavioural Finance; Learning; Uncovered Interest Parity;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:sce:scecf2:3. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.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.