scholarly journals Derivative Trading and Spot Market Volatility: Evidence from Indian Market

2015 ◽  
Vol 1 (3) ◽  
pp. 23-34 ◽  
Author(s):  
Dhanya Alex ◽  
Roshna Varghese
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Unit Root Test ◽  
Spot Market ◽  
Descriptive Statistics ◽  
Garch Models ◽  
Indian Market ◽  
Stock Volatility ◽  
Asymmetric Behaviour ◽  
Indian Stock Market

The present study tries to estimate the effect of introduction of individual stock derivatives on the underlying stock volatility in Indian stock market. To estimate the effect of introduction of derivatives on stock market, GARCH family models which are known for their ability to model volatility. The return series of the ten companies were tested using methods like, unit root test and descriptive statistics to confirm that GARCH models could be used. Using these models, the asymmetric nature of stock returns and the volatility of stock returns on the introduction of derivatives are checked. The results reveal that the introduction of derivatives has decreased the volatility of the underlying stock returns. It was also found that most of the stock returns show asymmetric behaviour.

scholarly journals Institutional Investments and Their Influence on Stock Returns – An Empirical Study

2017 ◽  
Vol 6 (3) ◽  
pp. 332
Author(s):  
R. Venkataraman ◽  
Srinidhi V.R ◽  
A.S. Chandramouli
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Mutual Fund ◽  
Unit Root Test ◽  
Foreign Investors ◽  
Global Recession ◽  
Market Variables ◽  
Indian Stock Market ◽  
Investment Patterns ◽  
Test Correlation

<div><p><em>Mutual dependency of market variables is crucial for development of any economy. It is equally important to study the stock market for what parameter influences over the others and for what length of time, thus giving direction to investors. Further, Sensex being an important barometer of India’s economic measurement, it would be interesting to know the revelation of its stability while institutional investors influence it in multiple ways over considerable longer period of economy. This study investigates the influence of FII and MF on Sensex over 11 year period between 2004-2015. The objectives were to find out the dependency among the three to conclude about which out theses influences market the most. On applying Unit–root test, Correlation and VAR, the study revealed that there was a regime change for BSE-Sensex returns due to the global recession. The noticeable fact is that change in regime affected the purchase of Mutual Fund which led to increasing in FII investment.   The variation in the investment patterns by institutions brought in heavy market movement. Indian stock market during the selected period was driven by a greater amount of Foreign Investors compared to the domestic investors, the Mutual Fund taken up for  this study.</em></p></div>

Financial Constraints, Stock Returns and R&D in Indian Stock Market

2021 ◽  
pp. 097226292098839
Author(s):  
Pankaj Sinha ◽  
Priya Sawaliya
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Financial Constraints ◽  
Fixed Effect Model ◽  
Quantitative Information ◽  
Common Shocks ◽  
External Finance ◽  
Negative Effect ◽  
Security Returns ◽  
Indian Stock Market

When the accessibility of external finance prohibits a firm from taking the optimum decision related to investment, that firm is called financially constrained. By applying the methodology of Kaplan and Zingales (1997) and Lamont et al. (2001), the current study has created a construct to gauge the level of financial constraints (FC) of the companies which emanate from quantitative information. The study explores whether FC factor is present in the Indian stock market and explores whether the security returns of those firms that are financially constrained move in tandem. The study also attempts to establish the association between security returns and R&D of financially constrained firms. On a sample of 63 R&D reporting companies of S&P BSE 500, traded over the period March 2008 to February 2019, the study used the Fama–French methodology, fixed effect model and the ordered logistic regression. The study finds that firms that are highly constrained earn more returns than low constrained firms. Second, the security returns of firms that are financially constrained move in tandem because these firms are affected by common shocks. This suggests that the FC factor exists in the Indian stock market. Finally, when R&D interacts with the level of FC, then this interaction effect has a negative effect on returns.

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

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

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.

scholarly journals Random Walk Investigation in Indian Market with special reference to S&P Nifty – Fifty Stocks

2015 ◽  
Vol 4 (4) ◽  
pp. 52-61
Author(s):  
Tamilselvan Manickam ◽  
R Madhumitha
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Abnormal Returns ◽  
Empirical Support ◽  
Weak Form ◽  
Indian Market ◽  
Price Series ◽  
Stock Market Efficiency ◽  
Indian Stock Market ◽  
Weak Form Efficiency

The competence of a financial system is entirely depending upon the stock market efficiency. The gradual growth of equity investor’s participation is inevitable to enrich the overall growth of emerging economies.Hence the necessity is felt to provide an empirical support to the investing community. For the purpose, this study attempts to examine the weak-form efficiency of Indian stock market – National Stock Exchange (NSE). The study has used the daily closing price of the Nifty fifty stocks from 3rdJanuary 2011 to 24thApril 2015. To test the weak form efficiency both parametric and non-parametric tests called Autocorrelation, Augmented Dicky Fuller test, and Runs Test were performed.  The study reveals that 39 stocks of NSE-Nifty Fifty are found to be weak form inefficient, so that the investors can formulate trading strategies to gain abnormal returns. The Index and 10 stocks are found to be weak form efficient during the study period since the price series found to be autocorrelation existence.

Re-Examining the Nifty Returns after the First Decade of Derivative Trading in Indian Capital Market Using Non-Linear Asymmetric GARCH Models

2012 ◽  
Vol 3 (4) ◽  
pp. 29-52 ◽  
Author(s):  
Sunita Narang
Keyword(s):  
Capital Market ◽  
Garch Models ◽  
Conditional Heteroskedasticity ◽  
Indian Market ◽  
Total Period ◽  
Dummy Variable ◽  
Asymmetric Garch ◽  
Indian Stock Market ◽  
Surrogate Index ◽  
The Impact

This article examines the Indian stock market for conditional volatility using symmetric and asymmetric GARCH (Generalized Autoregressive Conditional Heteroskedasticity) variants with reference to a comprehensive period of 20 years from July 3, 1990 to November 30, 2010 using S&P CNX Nifty. The impact of future trading on Nifty return and volatility is assessed using dummy variable in total period and using Log (Open Interest of Nifty futures) in post-derivative period. Along with the period of two decades the analysis has also been done on a sub-period of a decade from 1995 to 2005 with NiftyJunior as surrogate index as it had no derivatives during this period. The results show that the PGARCH model is best suited to Indian market conditions.

Friday the 13th effect on Indian stock market

2020 ◽  
Vol 07 (02) ◽  
pp. 2050010
Author(s):  
Tarika Singh Sikarwar ◽  
Karuna Shrivastava ◽  
Pratibha Jadon
Keyword(s):  
Stock Market ◽  
Design Methodology ◽  
Stock Exchange ◽  
Emerging Market ◽  
Indian Market ◽  
Study Results ◽  
Developed Nations ◽  
Indian Stock Market ◽  
Work Done ◽  
Practical Implications

Purpose: This paper attempts to investigate the presence of Friday the 13th Effect in the Indian stock market. Design/methodology/approach: This paper tests the presence of the Friday the 13th Effect using different sets of hypotheses for 7 days, 15 days and normal versus Friday the 13th by using statistical methods. Findings: The findings of the study do not support the presence of Friday the 13th Effect for all cases. There are few months for certain specific years where the effect was seen. Research limitations/implications: The Friday the 13th effect has been examined for two major indices of the Indian market, i.e., the Bombay Stock Exchange Index SENSEX and the National Stock Exchange Nifty Fifty Index. However, there are other major and sectoral indices as well where in the effect may be checked. Practical implications: The study results indicate that Indian stock market shows phased anomaly. The effect of Friday the 13th is seen only in some cases during certain years only. Originality/value: Friday the 13th effect has been mostly checked for developed nations and again there has been less work done with respect to this particular market anomaly. The present research is an original work done for emerging market naming India.

scholarly journals VOLATILITY IN STOCK RETURN SERIES OF VIETNAM STOCK MARKET

2011 ◽  
Vol 14 (3) ◽  
pp. 5-21
Author(s):  
Vinh Xuan Vo ◽  
Ngan Thi Kim Nguyen
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Structural Breaks ◽  
Garch Models ◽  
Financial Policies ◽  
Long Span ◽  
Return Variance ◽  
Daily Stock Returns ◽  
Icss Algorithm

This paper studies the features of the stock return volatility using GARCH models and the presence of structural breaks in return variance of VNIndex in the Vietnam stock market by using the iterated cumulative sums of squares (ICSS) algorithm. Using a long-span data, GARCH and GARCH in mean (GARCH-M) models seems to be effective in describing daily stock returns’ features. About structural breaks, when applying ICSS to standardized residuals filtered from GARCH (1, 1) model, the number of volatility shifts significantly decreases in comparison with the raw return series. Events corresponding to those breaks and altering the volatility pattern of stock return are found to be country-specific. Not any shifts are found during global crisis period. Further evidence also reveals that when sudden shifts are taken into account in the GARCH models, volatility persistence remarkably reduces and that the conditional variance of stock return is much affected by past trend of observed shocks and variance. Our results have important implications regarding advising investors on decisions concerning pricing equity, portfolio investment and management, hedging and forecasting. Moreover, it is also helpful for policy-makers in making and promulgating the financial policies.

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