scholarly journals The Impact of Risk Anomalies on the Pharmaceutical Sector of the Indian Stock Market. A comparative analysis between pharmaceutical, FMCG and IT companies

2020 ◽  
Vol 71 (2) ◽  
pp. 58-63
Author(s):  
Prakash Pinto ◽  
Iqbal Thonse Hawaldar ◽  
Guruprasad Kemminje ◽  
Babitha Rohit ◽  
Cristi Marcel Spulbar ◽  
...  

The main purpose of this research article is to provide a comparative framework on various implications of risk anomalies on Indian stock market based on an empirical study for the following sectors: Pharmaceutical, Fast-Moving Consumer Goods (FMCG) and IT. Risk anomaly is a notable anomaly because it is continual and all-inclusive. This research study aims to examine the existence of risk anomaly in the National Stock Exchange, India, and in particular providing a comparative analysis on the behavior of the pharmaceutical sector in India.

2012 ◽  
Vol 13 (1) ◽  
pp. 39-50 ◽  
Author(s):  
M. Selvam ◽  
G. Indhumathi ◽  
J. Lydia

Changes in an index are a regular phenomenon and they take place due to the inclusion and exclusion of stocks from the index. The inclusion or exclusion of stocks creates great impact on the value of the firm. However, these changes are simply a short-lived event with no permanent valuation effect. The present research study analyzed the impact of the inclusion into and exclusion of certain stocks from National Stock Exchange (NSE) S&P CNX Nifty index with Indian perspective. The study provides evidence on whether the announcements of Nifty index maintenance committee have any information content. This will also demonstrate the efficiency of Indian stock market with particular reference to NSE. The study revealed that on an average, no permanent effects were observed on stock prices. It is also found from the study that the NSE reacted unfavourably to the inclusion and exclusion of stocks and it is impossible to earn any excess returns where the particular stocks are included or excluded from the index.


2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.


2020 ◽  
Vol 17 (3) ◽  
pp. 133-147
Author(s):  
Rashmi Chaudhary ◽  
Priti Bakhshi ◽  
Hemendra Gupta

The current empirical study attempts to analyze the impact of COVID-19 on the performance of the Indian stock market concerning two composite indices (BSE 500 and BSE Sensex) and eight sectoral indices of Bombay Stock Exchange (BSE) (Auto, Bankex, Consumer Durables, Capital Goods, Fast Moving Consumer Goods, Health Care, Information Technology, and Realty) of India, and compare the composite indices of India with three global indexes S&P 500, Nikkei 225, and FTSE 100. The daily data from January 2019 to May 2020 have been considered in this study. GLS regression has been applied to assess the impact of COVID-19 on the multiple measures of volatility, namely standard deviation, skewness, and kurtosis of all indices. All indices’ key findings show lower mean daily return than specific, negative returns in the crisis period compared to the pre-crisis period. The standard deviation of all the indices has gone up, the skewness has become negative, and the kurtosis values are exceptionally large. The relation between indices has increased during the crisis period. The Indian stock market depicts roughly the same standard deviation as the global markets but has higher negative skewness and higher positive kurtosis of returns, making the market seem more volatile.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Binghui Wu ◽  
Yuanman Cai ◽  
Mengjiao Zhang

This paper uses the partial least squares method to construct the investor sentiment index in Chinese stock market. The Shanghai Stock Exchange 180 Index and the Shenzhen Stock Exchange 100 Index are used as samples. From the perspectives of holistic sentiment and heterogeneous sentiment, this paper studies the impact of investor sentiment on stock price crash risk. The results show that investor sentiment can significantly affect stock price crash risk in Shanghai and Shenzhen A-share markets, especially in the Shenzhen A-share market no matter from which perspective. And investor pessimism has a greater impact on stock price crash risk in the Shenzhen A-share market from the perspective of heterogeneous sentiment. Compared with the available researches, this paper makes two contributions: (i) the comparative analysis is adopted to discuss the differences between Shanghai and Shenzhen A-share markets, abandoning the research approach that takes the two markets as a whole in existing literature, and (ii) this paper not only studies the impact of investor holistic sentiment on stock price crash risk from a macro perspective, but also adds a more micro heterogeneous sentiment and conducts a comparative analysis.


2020 ◽  
Vol 16 (2) ◽  
pp. 146-156
Author(s):  
Rajdeep Kumar Raut ◽  
Rohit Kumar

This article examines the association between daylight hours as a proxy for the seasonal affective disorder (SAD) and stock market return. Past studies have documented different decision-making mechanisms induced by investors’ cognition mainly influenced by greed and fear. However, this study appears to be different from evidence where investors’ mood is affected by seasonality, which plays a vital role in risk-taking propensity. Data have been taken from three indexes of Bombay Stock Exchange (BSE), for the period between April 2003 and December 2016. The impact of SAD on stock market return was examined by using naïve ordinary least square (OLS) model. This study reports a negative relationship between daylight hours and pattern of midcap as well as smallcap indexes, which are in alignment with mood maintenance hypothesis (MMH). The result of negative correlation suggests a summer-type SAD, which is an addition to the findings of the existing literature.


2020 ◽  
Author(s):  
Debakshi Bora ◽  
Daisy Basistha

Abstract The outbreak of COVID-19 has affected the entire global financial market in an unprecedented way. Due to the disruptions that emerged in the global market; the financial market of India also reacted to the pandemic and witnessed sharp volatility. Given the COVID-19 situation, this paper empirically investigates the impact of COVID-19 on the Indian stock market. Using daily closing prices of indices such as Nifty and Sensex, this study examines the volatility of these indices over the period 3rd September 2019 to 10th July 2020. Further, the study has attempted to make a comparative analysis of the return of the stock market in pre-COVID-19 and during the COVID-19 situation. GARCH model is used to capture the volatility of the indices. Findings reveal that the stock market in India has experienced volatility during the pandemic period. While comparing the results with that of the pre-COVID-19 period, we find that return on the indices is higher in the pre-COVID-19 period than during COVID-19. The return of both the stock market reached the bottom line during the first lockdown period, which is from24th March to 6th April.


2016 ◽  
Vol 7 (2) ◽  
Author(s):  
Babitha Rohit ◽  
Prakash Pinto ◽  
Shakila B.

The current paper studies the impact of two events i.e stock splits and rights issue announcement on the stock returns of companies listed on the Bombay Stock Exchange. The study consists of a sample of 90 announcements for stock splits and 29 announcements for rights issue during the period 2011-2014. Market model is used to calculate the abnormal returns of securities. Positive Average Abnormal Returns were observed for the two events on the day their announcements, however they are not statistically significant. The study concludes that the Indian stock market is efficient in its semi-strong form.


2021 ◽  
pp. 0258042X2110531
Author(s):  
Miklesh Prasad Yadav ◽  
Aastha Khera ◽  
Nandita Mishra

This study investigates the relationship between the Indian stock market price behaviour and macroeconomic variables. The proxy for the Indian stock market is the BSESENSEX while Foreign Reserve, Exchange Rate (Indian vs. US Dollar) and CPI are proxies for the macroeconomic variables. The Johansen Cointegration Test and the Vector Error Correction Model (VECM) on monthly data collected from websites of Reserve Bank of India and Bombay Stock Exchange within the time period of January 2000 and February 2020 have been applied. We observe a contradiction between the results of trace statistics and the maximal eigenvalue of the Johansen Cointegration. The -trace statistics of cointegration allude to the long-run association between the Indian stock market and its constituent macroeconomic variables. The VECM is then applied to examine the long-run and short-run causalities and the results reveal the same. This study has profound implications for investors to diversify their portfolio, considering the impact of the constituent selected macroeconomic variables in the short run and long run. JEL Codes: B22, J11, R53


Think India ◽  
2014 ◽  
Vol 17 (3) ◽  
pp. 22-24
Author(s):  
Sreekumar Ray

Since inception, the growth of the Indian stock market has been constrained through unethical, illegal and self-actualized activities of swanky persons involved in different capacities in the market. The stock market was trying to retrieve itself from the devastating effect of Harshad Mehta share market scam, when within a gap of ten years it was once again pushed into the darkness of the dungeon by another demon-child of the country- Ketan Parekh. Corporations have been looted by the insider traders, diversifying internal information to an external in lieu of cash. Investigations in the majority cases have proved the involvement of the high ranking officers of the companies in the crime, sophistically referred to as white-collar crime. It has an adverse impact on the growth and sustainability of the share market. Under the light of the above issue, this paper endeavors to study the impact of such crime on the share market. It focuses on the mechanism behind the insider-trading, its impact on the share market and the regulators supervision on the issue. Finally, suggestions have been provided which will contribute towards the dream of every Indian-a fraud-free share market focusing towards the overall development of the country.


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