Unique Calendar Effects in the Indian Stock Market: Evidence and Explanations

2019 ◽  
Vol 18 (1_suppl) ◽  
pp. S35-S58 ◽  
Author(s):  
Harshita ◽  
Shveta Singh ◽  
Surendra S. Yadav
Keyword(s):  
Stock Market ◽  
Jel Classification ◽  
Calendar Effects ◽  
Window Dressing ◽  
Year Effect ◽  
Index Level ◽  
Indian Stock Market ◽  
Tax Loss ◽  
Behavioural Aspects

Covering 20 years (1995–2015), the article ascertains the presence of the month-of-the-year effect in the Indian stock market, for the raw returns series as well as after adjusting for non-linearities of the market. Whether the effect is the same for portfolios of different sizes and values is also ascertained. The threshold generalised autoregressive conditionally heteroskedastic (TGARCH) model is employed to address non-linearity. The results suggest the presence of higher returns in November/December at the index level. Further, only firms with a size smaller than the average exhibit seasonality in the form of the April/May and November/December effect. The value-sorted portfolios exhibit weaker evidence of the December effect. Tax-loss selling, window dressing and behavioural aspects seem to provide the explanation. JEL Classification: C58, G14

Does time-varying illiquidity matter for the Indian stock market? Evidence from high-frequency data

2021 ◽  
pp. 031289622110102
Author(s):  
Mousumi Bhattacharya ◽  
Sharad Nath Bhattacharya ◽  
Sumit Kumar Jha
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
High Frequency ◽  
Jel Classification ◽  
Exogenous Shock ◽  
Intraday Data ◽  
Day Of The Week ◽  
Holiday Effects ◽  
Indian Stock Market ◽  
The Impact

This article examines variations in illiquidity in the Indian stock market, using intraday data. Panel regression reveals prevalent day-of-the-week, month, and holiday effects in illiquidity across industries, especially during exogenous shock periods. Illiquidity fluctuations are higher during the second and third quarters. The ranking of most illiquid stocks varies, depending on whether illiquidity is measured using an adjusted or unadjusted Amihud measure. Using pooled quantile regression, we note that illiquidity plays an important asymmetric role in explaining stock returns under up- and down-market conditions in the presence of open interest and volatility. The impact of illiquidity is more severe during periods of extreme high and low returns. JEL Classification: G10, G12

Institutional Herding: Causality and Persistence

2021 ◽  
pp. 227797522110402
Author(s):  
S S S Kumar
Keyword(s):  
Stock Market ◽  
Market Efficiency ◽  
Mutual Funds ◽  
Institutional Investors ◽  
International Markets ◽  
Jel Classification ◽  
Trading Strategies ◽  
Trading Activity ◽  
Indian Stock Market ◽  
Institutional Herding

We investigate the causality in herding between foreign portfolio investors (FPIs) and domestic mutual funds (MFs) in the Indian stock market. The estimated herding levels are considerably higher than those observed in other international markets, and herding is prevalent in small stocks. We find that institutional investors follow contrarian-trading strategies, unlike what was documented in most other markets. Analysis of the aggregate herding measure shows a bi-directional causality between FPIs and MFs. Further analysis using directional herding measures indicate no evidence of causality between institutional herds on the sell-side. But we find causality on the buy-side and it is running in both directions between FPIs and MFs, implying a feedback of information. Given the tendency of institutions for herding in small stocks, adopting contrarian-trading strategies, the observed sell-side causality is perhaps having a salubrious effect. As institutional investors are contrarians, their trading activity will lead to price corrections in small stocks aligning with the fundamentals, thereby contributing to market efficiency. JEL Classification: C23, C58, G23, G15, G40

scholarly journals Trends and Calendar effects in Malaysia’s Stock Market

2017 ◽  
Vol 6 (1) ◽  
pp. 18 ◽  
Author(s):  
Ayman Abdalmajeed Ahmad Al-smadi ◽  
Mahmoud Khalid Almsafir ◽  
Nur Hanis Hazwani Binti Husni
Keyword(s):  
Stock Market ◽  
Interest Rates ◽  
Sovereign Debt ◽  
Stock Price ◽  
Debt Crisis ◽  
Weak Form ◽  
Study Data ◽  
January Effect ◽  
Calendar Effects ◽  
Tax Loss

Investing can help a person's wealth to generate more, and investing in stock is proven as one of the most profitable forms of available investment. The benefits gained in stock broking are immediate Buy/Sell which investor can sell part of their investment any time and at low transaction cost. However, investing in stock will require investor to observe the market, as market can be a volatile place and investor need to acquire knowledge of what they actually are doing. This study will discuss the price trends over the year, and how it will get affected by the seasonality in Malaysia, which also known as the calendar effects. The factor to be investigated in this study is the price on holiday’s season, the January effect or any other monthly seasonality. The daily price of KPJ Healthcare Berhad for the year 2011 is the sample was chosen in this study. Further this study, data used is derived from the weak-form efficient markets hypothesis, which is the price history and case study. Regression method is used in this study in order to help achieving the findings. This should be a continuous study, and adding on more other factors, such as wars and economic crises, and traders, investors and other speculators. This paper has proved the existence of calendar anomalies in KPJ's stock price for Chinese New Effect, Aidilfitri Effect and Christmas Effect. However, the price changes are believed more likely due to the investors tormenting about central banks raising interest rates to restrain rising inflation. Other than that, for Aidilfitri Effect and Christmas Effect, further study should be perform since the raise of the stock market, may be due to the world’s stock market begin to be stronger after the European sovereign debt crisis to Spain and Italy in August. Conversely, there are positive returns for January. However, the findings are non-related to the January effect. This is because January effect arises due to tax-loss selling, which Malaysia has a different tax system compared to other countries. Shareholders in Malaysia are not necessary to pay any taxes on the return they gained from share trading.

scholarly journals Calendar Effects In The Indian Stock Market

2011 ◽  
Vol 7 (3) ◽  
Author(s):  
Jayen B. Patel
Keyword(s):  
Stock Market ◽  
The Other ◽  
Calendar Effects ◽  
Indian Stock Market

We find two distinct calendar effects in returns for the Indian stock market. More specifically, we find a November-December effect in which we document that mean returns for November and December are significantly greater than those of the other ten months. We also identify a March-to-May effect in which mean returns for the months March to May are significantly less than those during the other nine months. We further demonstrate that these are two distinct effects that are independent of each other.

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

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.

STOCK MARKET ANOMALIES: A CASE OF CALENDAR EFFECTS ON THE MALAYSIAN STOCK MARKET

2021 ◽  
Vol 6 (1) ◽  
pp. 772
Author(s):  
Nurul Sima Mohamad Shariff ◽  
Nur Aisyah Yusof
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Stock Exchange ◽  
Composite Index ◽  
Investment Strategy ◽  
Series Data ◽  
Kuala Lumpur ◽  
Market Anomalies ◽  
Calendar Effects ◽  
Year Effect

The existence of market anomalies for the return reveals the inefficiency in the market that could affect investor investment strategy, portfolio selection, and profit management. It is due to the unpredictable movement of the stock market return that will affect the decision of investors later. As such, this study intends to investigate day of the week effect, a month of the year effect, and a quarter of the year effect on the Malaysian Stock Exchange, namely the Kuala Lumpur Composite Index (KLCI) on data from 2nd January of 2015 until 31st December 2018. Based on the findings from Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model analysis, it is found that the daily effect on returns was insignificant. Possible reasons for the insignificant return could be due to the lack of time-series data. However, the significant monthly effect on returns of May, November, and December while the quarterly effect on the returns is found significant in the first quarter. This study also concludes that volatility shock is persistent in the returns for all those three market anomalies.

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