Testing the Random Walk Hypothesis in the Indian Stock Market Using ARIMA Modelling

Mihir Dash ()

Journal of Applied Management and Investments, 2019, vol. 8, issue 2, 71-77

Abstract: The Random Walk Hypothesis (RWH) is a consequence of two foundational financial theories: the Geometric Brownian Motion (GBM) model and the Efficient Market Hypothesis (EMH). The paper examines the RWH for twenty major stocks from the Indian banking sector. The stock price data was collected from the National Stock Exchange (NSE). The study period selected was Apr. 1, 2017 to Mar. 31, 2018, a period of one year. The study uses the runs test, the Augmented Dickey-Fuller (ADF) unit root test, and Auto-regressive integrated moving average (ARIMA) modelling for the stock log-returns to test the RWH. While the results of runs test and ADF test support the RWH, the results of the Auto-regressive moving average (ARMA) modelling, however, provide some evidence against the RWH. However, as the R2 for the ARMA models were low, log-returns may largely be due to random stock price movements. Thus, though log-returns may not follow a pure random walk, there is some scope for randomness in log-returns series.

Keywords: random walk; efficient market; unit root test; ARIMA modelling (search for similar items in EconPapers)
JEL-codes: C22 G14 G21 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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