IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/11535.html
   My bibliography  Save this paper

Volatility and Long Term Relations in Equity Markets: Empirical Evidence from Germany, Switzerland, and the UK

Author

Listed:
  • Guidi, Francesco

Abstract

The aim of this paper is twofold. First it aims to compare several GARCH family models in order to model and forecast the conditional variance of German, Swiss, and UK stock market indexes. The main result is that all GARCH family models show evidence of asymmetric effects. Based on the “out of sample” forecasts I can say that for each market considered there is a model that will lead to better volatility forecasts. Secondly a long run relation between these markets was investigated using the cointegration methodology. Cointegration tests show that DAX30, FTSE100, and SMI indexes move together in the long term. The VECM model indicates a positive long run relation among these indexes, while the error correction terms indicate that the Swiss market is the initial receptor of external shocks. One of the main findings of this analysis is that although the UK, Switzerland and Germany do not share a common currency, the diversification benefits of investing in these countries could be very low given that their stock markets seem to move together in the lung term.

Suggested Citation

  • Guidi, Francesco, 2008. "Volatility and Long Term Relations in Equity Markets: Empirical Evidence from Germany, Switzerland, and the UK," MPRA Paper 11535, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:11535
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/11535/1/MPRA_paper_11535.pdf
    File Function: original version
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    2. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    5. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    6. Bodart, Vincent & Reding, Paul, 1999. "Exchange rate regime, volatility and international correlations on bond and stock markets," Journal of International Money and Finance, Elsevier, vol. 18(1), pages 133-151, January.
    7. Pindyck, Robert S, 1984. "Risk, Inflation, and the Stock Market," American Economic Review, American Economic Association, vol. 74(3), pages 335-351, June.
    8. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    9. Kim, Chang-Jin & Morley, James C & Nelson, Charles R, 2004. "Is There a Positive Relationship between Stock Market Volatility and the Equity Premium?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(3), pages 339-360, June.
    10. Voronkova, Svitlana, 2004. "Equity market integration in Central European emerging markets: A cointegration analysis with shifting regimes," International Review of Financial Analysis, Elsevier, vol. 13(5), pages 633-647.
    11. Richards, Anthony J., 1995. "Comovements in national stock market returns: Evidence of predictability, but not cointegration," Journal of Monetary Economics, Elsevier, vol. 36(3), pages 631-654, December.
    12. Gikas A. Hardouvelis & Dimitrios Malliaropulos & Richard Priestley, 2006. "EMU and European Stock Market Integration," The Journal of Business, University of Chicago Press, vol. 79(1), pages 365-392, January.
    13. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    14. Osterwald-Lenum, Michael, 1992. "A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 461-472, August.
    15. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
    16. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    17. R. F. Engle & A. J. Patton, 2001. "What good is a volatility model?," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 237-245.
    18. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    19. Francis, Bill B. & Leachman, Lori L., 1998. "Superexogeneity and the dynamic linkages among international equity markets," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 475-492, June.
    20. Ng, Angela, 2000. "Volatility spillover effects from Japan and the US to the Pacific-Basin," Journal of International Money and Finance, Elsevier, vol. 19(2), pages 207-233, April.
    21. Mohammad Najand, 2002. "Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models," The Financial Review, Eastern Finance Association, vol. 37(1), pages 93-104, February.
    22. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    23. Gilmore, Claire G. & McManus, Ginette M., 2002. "International portfolio diversification: US and Central European equity markets," Emerging Markets Review, Elsevier, vol. 3(1), pages 69-83, March.
    24. Dima Alberg & Haim Shalit & Rami Yosef, 2008. "Estimating stock market volatility using asymmetric GARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 18(15), pages 1201-1208.
    25. Swanson, Peggy E., 2003. "The interrelatedness of global equity markets, money markets, and foreign exchange markets," International Review of Financial Analysis, Elsevier, vol. 12(2), pages 135-155.
    26. Cotter, John, 2004. "International equity market integration in a small open economy: Ireland January 1990-December 2000," International Review of Financial Analysis, Elsevier, vol. 13(5), pages 669-685.
    27. Li, Qi & Yang, Jian & Hsiao, Cheng & Chang, Young-Jae, 2005. "The relationship between stock returns and volatility in international stock markets," Journal of Empirical Finance, Elsevier, vol. 12(5), pages 650-665, December.
    28. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    29. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
    30. Ratanapakorn, Orawan & Sharma, Subhash C., 2002. "Interrelationships among regional stock indices," Review of Financial Economics, Elsevier, vol. 11(2), pages 91-108.
    31. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    32. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    33. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    34. Manning, Neil, 2002. "Common trends and convergence? South East Asian equity markets, 1988-1999," Journal of International Money and Finance, Elsevier, vol. 21(2), pages 183-202, April.
    35. Koutmos, Gregory, 1998. "Asymmetries in the Conditional Mean and the Conditional Variance: Evidence From Nine Stock Markets," Journal of Economics and Business, Elsevier, vol. 50(3), pages 277-290, May.
    36. Robert W. Faff & David Hillier & Joseph Hillier, 2000. "Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(5&6), pages 523-554.
    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. Ioannis A. Tampakoudis & Demetres N. Subeniotis & Ioannis G. Kroustalis, 2012. "Modelling volatility during the current financial crisis: an empirical analysis of the US and the UK stock markets," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 5(3/4), pages 171-194.

    More about this item

    Keywords

    Stock Returns; Volatility; GARCH models; Cointegration;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:pra:mprapa:11535. 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: (Joachim Winter). General contact details of provider: http://edirc.repec.org/data/vfmunde.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.