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

Muneer Shaik and Rutvik Digambar Gulhane

International Journal of Finance & Economics, 2023, vol. 28, issue 3, 2989-2997

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.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/ijfe.2579

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:ijfiec:v:28:y:2023:i:3:p:2989-2997

Ordering information: This journal article can be ordered from
http://jws-edcv.wile ... PRINT_ISSN=1076-9307

Access Statistics for this article

International Journal of Finance & Economics is currently edited by Mark P. Taylor, Keith Cuthbertson and Michael P. Dooley

More articles in International Journal of Finance & Economics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().