scholarly journals Month-of-the-Year Effect: Empirical Evidence from Indian Stock Market

2022 ◽  
Author(s):  
Rajesh Elangovan ◽  
Francis Gnanasekar Irudayasamy ◽  
Satyanarayana Parayitam
Keyword(s):  
Stock Market ◽  
Empirical Evidence ◽  
Year Effect ◽  
Indian Stock Market

Day Of The Week Effect: Empirical Evidence From Indian Stock Market

Paradigm ◽  
2004 ◽  
Vol 8 (2) ◽  
pp. 9-13 ◽  
Author(s):  
Mohit Gupta ◽  
Navdeep Aggarwal
Keyword(s):  
Stock Market ◽  
Empirical Evidence ◽  
Day Of The Week ◽  
Indian Stock Market

Settlement cycle and day of the week anomaly: empirical evidence from Indian stock market

DECISION ◽  
2014 ◽  
Vol 41 (3) ◽  
pp. 327-337 ◽  
Author(s):  
Samveg A. Patel ◽  
M. Mallikarjun
Keyword(s):  
Stock Market ◽  
Empirical Evidence ◽  
Day Of The Week ◽  
Indian Stock Market

Calendar anomaly: unique evidence from the Indian stock market

2018 ◽  
Vol 15 (1) ◽  
pp. 87-108
Author(s):  
Harshita Harshita ◽  
Shveta Singh ◽  
Surendra S. Yadav
Keyword(s):  
Stock Market ◽  
Autocorrelation Function ◽  
Abnormal Returns ◽  
Content Type ◽  
Volatility Clustering ◽  
Year Effect ◽  
Augmented Dickey Fuller ◽  
Short Term Investment ◽  
Investment Portfolios ◽  
Indian Stock Market

Purpose The purpose of this paper is to ascertain the monthly seasonality in the Indian stock market after taking into consideration the market features of leptokurtosis, volatility clustering and the leverage effect. Design/methodology/approach Augmented Dickey-Fuller, Phillips-Perron and Kwaitkowski-Phillips-Schmidt-Shin tests are deployed to check stationarity of the series. Autocorrelation function, partial autocorrelation function and Ljung-Box statistics are employed to check the applicability of volatility models. An exponential generalized auto regressive conditionally heteroskedastic model is deployed to test the seasonality, where the conditional mean equation is a switching model with dummy variables for each month of the year. Findings Though the financial year in India stretches from April to March, the stock market exhibits a November effect (returns in November are the highest). Cultural factors, misattribution bias and liquidity hypothesis seem to explain the phenomenon. Research limitations/implications The paper endeavors to provide a review of possible explanations behind month-of-the-year effect documented in literature in the past four decades. Further, the unique evidence from the Indian stock market supports the argument in the literature that monthly seasonality, by nature, may not be a consistent/robust phenomenon. Therefore, it needs to be examined from time to time. Originality/value As the seasonality in the stock market and resultant anomalies are dynamic phenomena, the paper reports the current seasonality/anomalies prevalent in the Indian market. This would aid investors in designing short-term investment portfolios (based on anomalies present) in order to earn abnormal returns.

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