Advanced Search
MyIDEAS: Login

An empirical analysis of alternative parametric ARCH models

Contents:

Author Info

  • Geoffrey F. Loudon

    (Macquarie University, Australia)

  • Wing H. Watt

    (DBS Bank, Singapore)

  • Pradeep K. Yadav

    (Department of Accounting and Finance, University of Strathclyde, 100 Cathedral Street, Glasgow G4 0LN, UK)

Registered author(s):

    Abstract

    This paper presents empirical evidence on the effectiveness of eight different parametric ARCH models in describing daily stock returns. Twenty-seven years of UK daily data on a broad-based value weighted stock index are investigated for the period 1971-97. Several interesting results are documented. Overall, the results strongly demonstrate the utility of parametric ARCH models in describing time-varying volatility in this market. The parameters proxying for asymmetry in models that recognize the asymmetric behaviour of volatility are highly significant in each and every case. However, the 'performance' of the various parameterizations is often fairly similar with the exception of the multiplicative GARCH model that performs qualitatively differently on several dimensions of performance. The outperformance of any model(s) is not consistent across different sub-periods of the sample, suggesting that the optimal choice of a model is period-specific. The outperformance is also not consistent as we change from in-sample inferences to out-of-sample inferences within the same period. Copyright © 2000 John Wiley & Sons, Ltd.Journal: Journal of Applied Econometrics

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://qed.econ.queensu.ca:80/jae/2000-v15.2/
    File Function: Supporting data files and programs
    Download Restriction: no

    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

    Volume (Year): 15 (2000)
    Issue (Month): 2 ()
    Pages: 117-136

    as in new window
    Handle: RePEc:jae:japmet:v:15:y:2000:i:2:p:117-136

    Contact details of provider:
    Web page: http://www.interscience.wiley.com/jpages/0883-7252/

    Order Information:
    Email:
    Web: http://www3.interscience.wiley.com/jcatalog/subscribe.jsp?issn=0883-7252

    Related research

    Keywords:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Baillie, Richard T & Bollerslev, Tim, 2002. "The Message in Daily Exchange Rates: A Conditional-Variance Tale," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 60-68, January.
    2. Rabemananjara, R & Zakoian, J M, 1993. "Threshold Arch Models and Asymmetries in Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 31-49, Jan.-Marc.
    3. West, K.D. & Cho, D., 1993. "The Predictive Ability of Several Models of Exchange Rate Volatility," Working papers 9317r, Wisconsin Madison - Social Systems.
    4. 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.
    5. G. William Schwert, 1990. "Stock Volatility and the Crash of '87," NBER Working Papers 2954, National Bureau of Economic Research, Inc.
    6. James M. Poterba & Lawrence H. Summers, 1984. "The Persistence of Volatility and Stock Market Fluctuations," NBER Working Papers 1462, National Bureau of Economic Research, Inc.
    7. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
    8. Kearns, P & Pagan, A R, 1993. "Australian Stock Market Volatility: 1875-1987," The Economic Record, The Economic Society of Australia, vol. 69(205), pages 163-78, June.
    9. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
    10. Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
    11. Duan, Jin-Chuan, 1997. "Augmented GARCH (p,q) process and its diffusion limit," Journal of Econometrics, Elsevier, vol. 79(1), pages 97-127, July.
    12. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-617, December.
    13. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    14. E.K. Berndt & B.H. Hall & R.E. Hall, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 103-116 National Bureau of Economic Research, Inc.
    15. Thomas H. McCurdy & Ieuan G. Morgan, 1986. "Tests of the Martingale Hypothesis for Foreign Currency Futures with Time-Varying Volatility," Working Papers 663, Queen's University, Department of Economics.
    16. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-53, December.
    17. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    18. Sentana,E., 1995. "Quadratic Arch Models," Papers 9517, Centro de Estudios Monetarios Y Financieros-.
    19. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    20. 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.
    21. Chou, Ray Yeutien, 1988. "Volatility Persistence and Stock Valuations: Some Empirical Evidence Using Garch," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(4), pages 279-94, October-D.
    22. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    23. Poon, Ser-Huang & Taylor, Stephen J., 1992. "Stock returns and volatility: An empirical study of the UK stock market," Journal of Banking & Finance, Elsevier, vol. 16(1), pages 37-59, February.
    24. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August.
    25. Pradeep K. Yadav & Peter F. Pope & Krishna Paudyal, 1994. "Threshold Autoregressive Modeling In Finance: The Price Differences Of Equivalent Assets," Mathematical Finance, Wiley Blackwell, vol. 4(2), pages 205-221.
    26. Engle, Robert F. & Mustafa, Chowdhury, 1992. "Implied ARCH models from options prices," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 289-311.
    27. Higgins, Matthew L & Bera, Anil K, 1992. "A Class of Nonlinear ARCH Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(1), pages 137-58, February.
    28. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    29. Philippe Jorion, 1988. "On Jump Processes in the Foreign Exchange and Stock Markets," Review of Financial Studies, Society for Financial Studies, vol. 1(4), pages 427-445.
    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 in new window

    Cited by:
    1. Twm Evans & David McMillan, 2007. "Volatility forecasts: the role of asymmetric and long-memory dynamics and regional evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 17(17), pages 1421-1430.
    2. Liu, Hung-Chun & Chiang, Shu-Mei & Cheng, Nick Ying-Pin, 2012. "Forecasting the volatility of S&P depositary receipts using GARCH-type models under intraday range-based and return-based proxy measures," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 78-91.
    3. Robert F. Engle & Kevin Sheppard, 2001. "Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH," NBER Working Papers 8554, National Bureau of Economic Research, Inc.
    4. G.R. Pasha & Tahira Qasim & Muhammad Aslam, 2007. "Estimating and Forecasting Volatility of Financial Time Series in Pakistan with GARCH-type Models," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 12(2), pages 115-149, Jul-Dec.
    5. Leeves, Gareth, 2007. "Asymmetric volatility of stock returns during the Asian crisis: Evidence from Indonesia," International Review of Economics & Finance, Elsevier, vol. 16(2), pages 272-286.
    6. Peter Reinhard Hansen & Asger Lunde & James M. Nason, 2003. "Choosing the Best Volatility Models: The Model Confidence Set Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 839-861, December.
    7. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2009. "Asymmetric multivariate normal mixture GARCH," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2129-2154, April.
    8. Matei, Marius, 2010. "Risk analysis in the evaluation of the international investment opportunities. Advances in modelling and forecasting volatility for risk assessment purposes," Working Papers of Institute for Economic Forecasting 100201, Institute for Economic Forecasting.
    9. Yueh-Neng Lin & Ken Hung, 2008. "Is Volatility Priced?," Annals of Economics and Finance, Society for AEF, vol. 9(1), pages 39-75, May.
    10. Kin-Yip Ho & Ka Cheng Tsui, 2004. "Volatility Dynamics of the Tokyo Stock Exchange: A Sectoral Analysis based on the Multivariate GARCH Approach," Money Macro and Finance (MMF) Research Group Conference 2004 12, Money Macro and Finance Research Group.
    11. Gabriela De Raaij & Burkhard Raunig, 2005. "Evaluating density forecasts from models of stock market returns," The European Journal of Finance, Taylor & Francis Journals, vol. 11(2), pages 151-166.
    12. M. Angeles Carnero & Daniel Peña & Esther Ruiz, 2001. "Is Stochastic Volatility More Flexible Than Garch?," Statistics and Econometrics Working Papers ws010805, Universidad Carlos III, Departamento de Estadística y Econometría.
    13. M. Angeles Carnero & Daniel Peña & Esther Ruiz, 2001. "Outliers And Conditional Autoregressive Heteroscedasticity In Time Series," Statistics and Econometrics Working Papers ws010704, Universidad Carlos III, Departamento de Estadística y Econometría.
    14. Mircea ASANDULUI, 2012. "A Multi-Horizon Comparison Of Volatility Forecasts: An Application To Stock Options Traded At Euronext Exchange Amsterdam," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 10, pages 179-190, December.
    15. María José Rodríguez & Esther Ruiz, 2009. "GARCH models with leverage effect : differences and similarities," Statistics and Econometrics Working Papers ws090302, Universidad Carlos III, Departamento de Estadística y Econometría.

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:jae:japmet:v:15:y:2000:i:2:p:117-136. 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: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.