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Estimating variability in the Italian stock market: An ARCH approach

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  • Fabio Fornari

Abstract

The variability of financial markets has become the focus of considerable interest, especially over the past decade. In this study, ARCH models are applied to the Italian stock market, at both general and sectoral levels, to identify the processes generating variances and to test whether the variances are explainable by an autoregressive equation. The predictive power of the estimated equations has been evaluated by comparing them with forecasts obtained from alternative estimation techniques. The outcome supports the idea of an autoregressive structure for the variances and a hyperreactive behavior of the Italian stock market to the arrival of destabilizing news. Copyright Kluwer Academic Publishers 1993

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File URL: http://hdl.handle.net/10.1007/BF01011138
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Bibliographic Info

Article provided by Springer in its journal Open Economies Review.

Volume (Year): 4 (1993)
Issue (Month): 4 (December)
Pages: 403-423

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Handle: RePEc:kap:openec:v:4:y:1993:i:4:p:403-423

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Web page: http://www.springerlink.com/link.asp?id=100323

Related research

Keywords: ARCH; maximum likelihood; variance;

References

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  1. 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.
  2. Pagan, A.R. & Schwert, G.W., 1989. "Alternative Models For Conditional Stock Volatility," Papers 89-02, Rochester, Business - General.
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  4. Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, vol. 36, pages 394.
  5. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-34, April.
  6. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
  7. 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.
  8. Pagan, Adrian & Ullah, Aman, 1988. "The Econometric Analysis of Models with Risk Terms," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(2), pages 87-105, April.
  9. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
  10. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
  11. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  12. 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.
  13. Hamilton, James D., 1988. "Rational-expectations econometric analysis of changes in regime : An investigation of the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 385-423.
  14. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-31, February.
  15. Mervyn A. King & Sushil Wadhwani, 1989. "Transmission of Volatility Between Stock Markets," NBER Working Papers 2910, National Bureau of Economic Research, Inc.
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Cited by:
  1. Schmitt, Christian, 1996. "Option pricing using EGARCH models," ZEW Discussion Papers 96-20, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.

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