Benford’s Law and Stock Market—The Implications for Investors: The Evidence from India Nifty Fifty

Abstract

Benford’s law which is also known as first digit law states that data follow a certain frequency. This law was applied to accounting by Nigrini (2012, Benford’s Law: Applications for forensic accounting, auditing, and fraud detection [Vol. 586], John Wiley & Sons) and later on, an exhaustive study was carried out by Amiram, Bozanic, and Rouen (2015, Review of Accounting Studies, 20(4), 1540–1593) to explore the applicability of the law to detect accounting frauds which was proven to be working. The literature has substantial evidence on relationship between accounting numbers and stock returns. The application of Benford’s law to stock trade and returns was explored and it was found that stock trade that included volume, number of trades, and turnover confirmed the distribution but stock returns did not conform the distribution (Jayasree, 2017, Jindal Journal of Business Research, 6(2), 172–186). In this context, the present study attempts to understand its implications to investors by examining the three-day moving average of stock prices and volatility volume by using Chainkin money flow during announcement and post-announcement period of observation. The study also examines whether stocks conforming the distribution and stocks not conforming the distribution are significantly different in buying and selling.