An Integrated Analysis of Market Efficiency and Volatility Forecasting: A Case Study on Hindustan Unilever Limited Using ARIMA and GARCH Models

Abstract

This research paper examines the market efficiency of Hindustan Unilever Limited (HUL) by exploring weak, semi-strong, and strong forms of market efficiency. Utilizing historical stock price data, we employ statistical analyses, including the Augmented Dickey-Fuller (ADF) test, Autocorrelation Function (ACF), and Variance Ratio test, to assess weak form efficiency. Our findings indicate that HUL’s stock prices are stationary and exhibit no significant autocorrelation, supporting the notion of efficient processing of historical price information.

In our examination of semi-strong form efficiency, we analyze Cumulative Abnormal Returns (CAR) and Abnormal Returns (AR) surrounding public announcements, revealing that market reactions are swift and reflect publicly available information effectively. This suggests that investors cannot achieve superior returns through fundamental analysis based on public data.

The discussion of strong form efficiency presents theoretical insights, acknowledging the challenges in collecting insider trading data. Although empirical evidence often suggests that insider trading can lead to abnormal returns, our study emphasizes the importance of understanding the implications of information dissemination in financial markets.

Overall, this research contributes to the discourse on market efficiency by providing a comprehensive analysis of HUL, highlighting the interplay between information, stock price movements, and market behavior. The findings underscore the necessity for ongoing investigation into the evolving dynamics of market efficiency, particularly in the context of regulatory frameworks and investor strategies.