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Modeling Stock Market Volatility in Emerging Markets: Evidence from India

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  • Sinha, Bhaskar

Abstract

This study models the volatility present in the inter day returns in the stock of the two major national indices of India. Sensitive Index or Sensex related to Bombay Stock Exchange (BSE) and Nifty associated with National Stock Exchange (NSE). The objective is to model the phenomena of volatility clustering and persistence of shock using asymmetric GARCH family of models. Research showed that EGARCH model successfully models the Sensex (BSE) data whereas it is GJR-GARCH which was able to explain conditional variance in the returns from Nifty (NSE).

Suggested Citation

  • Sinha, Bhaskar, 2007. "Modeling Stock Market Volatility in Emerging Markets: Evidence from India," MPRA Paper 102455, University Library of Munich, Germany, revised 2009.
    • Handle: RePEc:pra:mprapa:102455
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    References listed on IDEAS

    as
    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. repec:bla:kyklos:v:26:y:1973:i:3:p:576-99 is not listed on IDEAS
    3. Andersen, Torben G & Bollerslev, Tim, 1997. "Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July.
    4. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    5. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Engle, Robert F. & Ng, Victor K. & Rothschild, Michael, 1990. "Asset pricing with a factor-arch covariance structure : Empirical estimates for treasury bills," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 213-237.
    8. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    9. 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 225-234, April.
    10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    11. 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.
    12. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    13. Dryden, Myles M, 1970. "A Statistical Study of U.K. Share Prices," Scottish Journal of Political Economy, Scottish Economic Society, vol. 17(3), pages 369-389, November.
    14. Klaus Conrad & D. Johannes Jüttner, 1973. "Recent Behaviour Of Stock Market Prices In Germany And The Random Walk Hypothesis," Kyklos, Wiley Blackwell, vol. 26(3), pages 576-599, January.
    15. 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 542-547, August.
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    More about this item

    Keywords

    GARCH; Volatility; Index;
    All these keywords.

    JEL classification:

    • N2 - Economic History - - Financial Markets and Institutions
    • N25 - Economic History - - Financial Markets and Institutions - - - Asia including Middle East

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