Testing the Day-of-the-Week Effect in the Indian Stock Market using the AR-GARCH Model
25 Pages Posted: 27 Apr 2020
Date Written: April 1, 2020
Abstract
This study combines three distinct empirical models of stock returns into a single model: the autoregressive model, which suggests that stock returns are determined by its own past values, the (generalised) autoregressive conditional heteroscedasticity model, which suggests that stock returns volatility is determined by its past values and by returns shocks, and the day-of-the-week effect, which suggests that stock returns are higher on particular days of the week (usually Fridays). All three models represent departures from the Random Walk Hypothesis (RWH), in the sense of proposing a certain degree of predictability in stock returns.
The study examines the extent to which the AR-GARCH model with day-of-the-week dummy variables 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, 2018 to Mar. 31, 2019, a period of one year.
Keywords: Random Walk Hypothesis, AR-GARCH model, day-of-the-week effect, banking sector, NSE
JEL Classification: G14
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