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Are the Bombay stock Exchange Sectoral indices of Indian stock market cointegrated? Evidence using fractional cointegration test

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  • Krishnankutty, Raveesh
  • Tiwari, Aviral Kumar

Abstract

The present study is an attempt to test whether sectoral indices of Bombay stock Exchange have diversification benefits in the same. For the analysis, we used daily data spanning from 2/1/1999to 3/31/2011. To test our hypothesis we used Fractional cointegration test. Study found that, ingeneral, no evidence of cointegration in the sectoral indices of Bombay stock Exchange and hence conclude that there is benefit to domestic investors for sectoral diversification in the Bombay stock Exchange Sectoral indices of Indian stock market.

Suggested Citation

  • Krishnankutty, Raveesh & Tiwari, Aviral Kumar, 2011. "Are the Bombay stock Exchange Sectoral indices of Indian stock market cointegrated? Evidence using fractional cointegration test," MPRA Paper 48590, University Library of Munich, Germany, revised 20 Dec 2011.
    • Handle: RePEc:pra:mprapa:48590
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    References listed on IDEAS

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    1. Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
    2. 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.
    3. Diebold, Francis X. & Rudebusch, Glenn D., 1991. "On the power of Dickey-Fuller tests against fractional alternatives," Economics Letters, Elsevier, vol. 35(2), pages 155-160, February.
    4. Granger, Clive W. J. & Hyung, Namwon, 2004. "Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 399-421, June.
    5. Mishra, Ritesh Kumar & Sehgal, Sanjay & Bhanumurthy, N.R., 2011. "A search for long-range dependence and chaotic structure in Indian stock market," Review of Financial Economics, Elsevier, vol. 20(2), pages 96-104, May.
    6. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    7. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    8. Luiz Renato Lima & Zhijie Xiao, 2010. "Is there long memory in financial time series?," Applied Financial Economics, Taylor & Francis Journals, vol. 20(6), pages 487-500.
    9. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    10. Olan Henry, 2002. "Long memory in stock returns: some international evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 12(10), pages 725-729.
    11. Benoit B. Mandelbrot, 1972. "Statistical Methodology for Nonperiodic Cycles: From the Covariance To R/S Analysis," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 3, pages 259-290, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    BSE stock Market; Fractional cointegration test; long memory returns; sectoral; diversification benefits;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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