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Power of moment‐based normality tests: Empirical analysis on Indian stock market index

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  • Muneer Shaik
  • Rutvik Digambar Gulhane

Abstract

In this paper, we study the power of moment‐based normality tests which include Jarque Bera (JB) test and D′Agostino and Pearson (DP) omnibus tests. Power comparison were obtained via Monte Carlo simulation of sample data generated from four alternative distributions like Uniform, Logistic, Student t and Gamma distribution. Our simulation results show that for Uniform distribution, DP test has better power compared to JB test. For Logistic, Student t and Gamma distributions, we find JB normality test to be powerful compared to DP test. We further apply the moment‐based normality tests empirically on the Indian stock market indices (NSE Nifty 50 and BSE Sensex) for different frequencies (daily, weekly, monthly and quarterly) during the period from 2010 to 2020. We find that daily returns of Indian stock indices are non‐normal whereas weekly, monthly and quarterly returns are normally distributed.

Suggested Citation

  • Muneer Shaik & Rutvik Digambar Gulhane, 2023. "Power of moment‐based normality tests: Empirical analysis on Indian stock market index," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2989-2997, July.
    • Handle: RePEc:wly:ijfiec:v:28:y:2023:i:3:p:2989-2997
    DOI: 10.1002/ijfe.2579
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    References listed on IDEAS

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    2. Parameswaran Gopikrishnan & Vasiliki Plerou & Luis A. Nunes Amaral & Martin Meyer & H. Eugene Stanley, 1999. "Scaling of the distribution of fluctuations of financial market indices," Papers cond-mat/9905305, arXiv.org.
    3. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
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