Nifty Junior Research Articles

Seasonal Anomalies in Vietnamese Stock Markets: New Evidence

This paper primarily studies the possible existence of the January Effect or the Turn-Of-The-Year Effect in the Vietnamese stock markets and the study proceeds on two propositions. First, if the January anomaly is ascribed to the tax-related selling, it should be clear in the month of April in the Vietnamese context. Second, if the phenomenon is due to some other reason than it should make itself visible in the month of January in Vietnamese market given its interrelationship with international markets. This study also explores the chances of other common seasonal anomalies discrediting the efficient market hypothesis in the Vietnamese market viz., Other January Effect and Beginning of the month and End of the month effect. This study has used VN 500, S&P VN Nifty, VN Nifty Junior, VN mid cap and VN small cap indices of National Stock Exchange of Vietnam (VN). Statistical techniques like dummy variable regression analysis, ARIMA modeling, parametric and non-parametric tests, etc. have been used to fulfill the objective of the study. The findings of the study exhibit a significantly pronounced April Effect in VN small cap and VN midcap indices, with relatively much lower return in March (although statistically not significant). These findings are consistent with the tax-loss-selling hypothesis. An interesting finding of the study, which is apparently unique, is the presence of statistically significant and strongly positive December effect in all the studied indices.

Existence of Day-of-the-Week Effect in Returns of Some Selected Indices of the Indian Stock Market

The present study attempted to measure day-of-the-week effect on the returns and volatility of Bombay Stock Exchange (BSE) and National Stock Exchange (NSE) indices for the period from 2005 through 2014. Along with the descriptive statistics, t-test and ANOVA were used to capture mean deference in returns for the trading days Monday through Friday. Mean returns of only one index, Nifty Junior, were found statistically significant while using t-test ; whereas, no such difference was observed in any of the index (BSE and NSE) in ANOVA. To confirm the findings of t-test and ANOVA, an econometric model AR (1)-GARCH (1, 1) was used. In contrast to the findings of the other indices, returns on Monday for BSE small cap were found to be statistically significant. It was also observed that volatility on Monday for returns on BSE small cap were statistically significant. Returns on Tuesday, for BSE small cap and BSE mid cap, were found to be negative and statistically significant. Returns on these two indices were also found to be negatively volatile on Tuesday. Wednesday effect was only observed for Nifty Junior, but no volatility was captured on Wednesday for Nifty Junior. Returns on Nifty Junior were also found to be positive and statistically significant on Friday, but volatility was captured for returns on Nifty Junior on Friday.

Integration of the Indian stock market with the world market: a study based on the time-varying Kalman filter approach

This paper examines the time-varying integration of the Indian stock market with the world market using Kalman filter approach. We consider major stock indices from the Indian stock market which includes S&P CNX Nifty, CNX 200, S&P CNX 500, CNX Nifty Junior, CNX Midcap and CNX Smallcap. Our approach involves the computation of an appropriate return index, based on the capital asset pricing model (CAPM), which can capture the sensitivity of the given stock returns to the market risk. Our findings confirm the time-varying integration of the S&P CNX Nifty with the world market over the study period. However, S&P CNX 500, CNX 200 and CNX Midcap exhibit deviation from the integration relationship during the period of the global financial crisis. The CNX Midcap and CNX Smallcap display deviation from the integration relationship during most of the periods before sub-prime crisis.

Integration of the Indian stock market with the world market: a study based on the time-varying Kalman filter approach

This paper examines the time-varying integration of the Indian stock market with the world market using Kalman filter approach. We consider major stock indices from the Indian stock market which includes S&P CNX Nifty, CNX 200, S&P CNX 500, CNX Nifty Junior, CNX Midcap and CNX Smallcap. Our approach involves the computation of an appropriate return index, based on the capital asset pricing model (CAPM), which can capture the sensitivity of the given stock returns to the market risk. Our findings confirm the time-varying integration of the S&P CNX Nifty with the world market over the study period. However, S&P CNX 500, CNX 200 and CNX Midcap exhibit deviation from the integration relationship during the period of the global financial crisis. The CNX Midcap and CNX Smallcap display deviation from the integration relationship during most of the periods before sub-prime crisis.

Pricing Efficiency of Equity Index Option Contracts: Evidence from National Stock Exchange of India

The present study examines the pricing efficiency of equity index options traded at National Stock Exchange of India by comparing the premium of options contracts traded on NIFTY, BANK NIFTY, CNXIT, NIFTY JUNIOR, and CNX100 indices with their respective theoretical price estimated by using Black-Scholes Model. 91-day T-Bill rate is used as risk-free rate and standard deviation computed on daily returns of the underlying index is used as volatility to estimate the theoretical prices. Pricing efficiency has been tested both for daily closing prices per se as well as for the In-the-Money, At-the-Money, and Out-of-the-Money options contracts. Mean Absolute Errors (MAE), Mean Squared Errors (MSE), Root Mean Squared Errors (RMSE), and Theils U statistics suggest that the premium of equity index options contracts do not follow Black-Scholes Model.

Indian Derivatives Market: A Study of Impact on Volatility and Investor Perception

Derivatives Market has an important role to play in the economic development of a country. The objective of the study is to examine the impact of financial derivatives (futures and options) on the underlying market volatility. The paper also analyses the perception of investor about objectives of investment, investment pattern, risk, derivatives awareness level, future of derivatives market in India. Data has been collected for a period of 18 years from January 1, 1996 to February 5, 2014. Data has been collected for various indexes like CNX S&P Nifty index daily closing prices (from January 1, 1996 to February 5, 2014), Nifty Junior Index (from January 1, 1996 to February 5, 2014), Index Futures near month contracts daily closing prices from (June 12, 2000 to February 5, 2014) and S&P 500 Index (from January 1, 1996 to February 5, 2014).The questionnaire was distributed to 1000 respondents but 522 filled questionnaires were received and have been analyzed in this study. The questionnaire was subjected to reliability and expert validity.The final AR (1)-GARCH (1,1) model show that overall volatility has reduced in the spot market after the introduction of derivatives. In the model all variables are highly significant. Awareness about financial markets, experience in derivatives trading, workplace activity and return expectation are significantly associated with derivative awareness level (DAL) of respondents at 5 percent level of significance. The results of Structural Equation Modelling reveals perception of investors about future of derivatives market in India include having an investor grievance redressal mechanism which is approachable under trading hours, steps to be taken by regulators to increase investments, conducting investor training and awareness programmes, global integration will happen, derivatives market will affect growth of the economy and consolidation of exchanges is required.

Indian Derivatives Market: A Study of Impact on Volatility and Investor Perception

Derivatives Market has an important role to play in the economic development of a country. The objective of the study is to examine the impact of financial derivatives (futures and options) on the underlying market volatility. The paper also analyses the perception of investor about objectives of investment, investment pattern, risk, derivatives awareness level, future of derivatives market in India. Data has been collected for a period of 18 years from January 1, 1996 to February 5, 2014. Data has been collected for various indexes like CNX S&P Nifty index daily closing prices (from January 1, 1996 to February 5, 2014), Nifty Junior Index (from January 1, 1996 to February 5, 2014), Index Futures near month contracts daily closing prices from (June 12, 2000 to February 5, 2014) and S&P 500 Index (from January 1, 1996 to February 5, 2014).The questionnaire was distributed to 1000 respondents but 522 filled questionnaires were received and have been analyzed in this study. The questionnaire was subjected to reliability and expert validity.The final AR (1)-GARCH (1,1) model show that overall volatility has reduced in the spot market after the introduction of derivatives. In the model all variables are highly significant. Awareness about financial markets, experience in derivatives trading, workplace activity and return expectation are significantly associated with derivative awareness level (DAL) of respondents at 5 percent level of significance. The results of Structural Equation Modelling reveals perception of investors about future of derivatives market in India include having an investor grievance redressal mechanism which is approachable under trading hours, steps to be taken by regulators to increase investments, conducting investor training and awareness programmes, global integration will happen, derivatives market will affect growth of the economy and consolidation of exchanges is required.

Stock market predictability

Purpose – The main objective of this study is to obtain new empirical evidence on non-synchronous trading effects through modelling the predictability of market indices. Design/methodology/approach – The authors test for lead-lag effects between the Indian Nifty and Nifty Junior indices using Pesaran–Timmermann tests and Granger-Causality. Then, a simple test on overnight returns is proposed to infer whether the observed predictability is mainly attributable to non-synchronous trading or some form of inefficiency. Findings – The evidence suggests that non-synchronous trading is a better explanation for the observed predictability in the Indian Stock Market. Research limitations/implications – The indication that non-synchronous trading effects become more pronounced in high-frequency data suggests that prior studies using daily data may underestimate the impacts of non-synchronicity. Originality/value – The originality of the paper rests on various important contributions: overnight returns is looked at to infer whether predictability is more attributable to non-synchronous trading or to some form of inefficiency; the impacts of non-synchronicity are investigated in terms of lead-lag effects rather than serial correlation; and high-frequency data is used which gauges the impacts of non-synchronicity during less active parts of the trading day.

An Empirical Study on Efficient Market Hypothesis: The Case of Indian Capital Markets

The objective of this paper is to study the efficiency of Indian stock markets during the period 2001-2011. The weak form of efficient markets is extensively tested using NIFTY and 6 major NSE sectoral indices Pharma, IT, MNC, Bank, FMCG and Nifty Junior. Univariate time series analysis of indices returns is carried using tests for randomness / non-stationarity - runs test, unit root testing. ACF, correlograms and other relevant statistical methods. The study concludes that Indian markets are inefficient in its weak form for the study period.

Month of the Year Anomalies in Stock Markets: Evidence from India

Judging the importance of existence of calendar anomalies in the stock market to the investors, the paper attempts to find out monthly anomalies in the market. The presence of seasonal effects in monthly returns in the Indian market has been reported by many researchers in the past. This study attempts to examine whether the month-of-the-year anomaly still exists in the Indian Stock Market. For this purpose, two indices, S&P CNX Nifty and S&P CNX Nifty Junior and top nine companies (according to market capitalisation) from both the indices have been selected.The daily closing prices of the respective indices and stocks have been taken and the logarithm return of these prices has been calculated. Line charts and unit-root test are applied to check the stationary nature of the series. The Dummy Variable Regression Model has been applied on the returns to find out any statistically significant deterrent month in the year.The paper observes that both the indices and some of the selected companies reflect the month-of-the-year anomalies in the Indian Stock Market. Mainly, the monthly anomaly is found at the end of a quarter for the given period.

Existence of Weekend Effect: An Empirical Investigation on Indian Stock Market

Investors have a tendency to search for investment opportunities. If error exists in the pricing of stocks, it indicates that anomalies are present and that stock market is inefficient. Investors then have the possibility to utilise the anomaly in order to receive above-average returns. The objective of this paper is to investigate whether abnormal patterns exists concerning rates of returns on Mondays. The paper tests the seasonality of the stock market, using observations of 14 years, from 1998 to 2011, of the two major indices reported by National Stock Exchange (NSE), i.e. Standard & Poor's (S & P) Nifty and CNX Nifty Junior. The day-of-the-week effect is examined by using analysis of variance, Mann-Whitney U-test and dummy variable regression analysis, which are tests for seasonality. The results show that Wednesdays’ returns are highest in both the indices and there is non-existence of the Monday effect.

What Does Capital Structure Decision Depend on? - Empirical Evidence from S&P CNX Nifty and Nifty Junior Firms

In this paper we attempted to analyze as to how Indian firms went about in designing their capital structure during the period 2002 through 2011. The findings of the study revealed that designing the capital structure depended on profitability in general and on ROCE and RONW in particular. The hypotheses testing revealed that, on an aggregate basis, capital structure decisions of Indian firms were influenced by profitability, solvency, size, tax factor and growth opportunities. The analysis pertaining to the impact of individual factor on leverage decision revealed that there was no link between growth opportunities and the way the firms designed their capital structure. Though other factors impacted the leverage decision, ‘t’ values of beta coefficients indicated that the influence was not so high. Though the extent of reliance varied among the years, the findings reveal that capital structure decision of Indian firms depended mostly on profitability followed by short-term solvency, size and tax laws in India. The study goes into in-depth analysis of capital structure decisions by Indian firms and made its own contribution to the body of knowledge on the topic.

Testing Weak form Market Efficiency: A Study of Selected Indices of National Stock Exchange

Informational efficiency of the Stock market is an important parameter to determine the effectiveness of a financial system, especially in the Indian context. The efficiency of Indian stock markets, especially the leading stock exchange of India – the National Stock Exchange (NSE), attracts the attention of researchers in view of recent instability in investment levels and the global financial turmoil. This paper therefore, attempts to seek evidence for the weak form efficient market hypothesis using the daily data for two stock indices of NSE i.e. S&P CNX Nifty and Nifty Junior from the National Stock Exchange for the period 1st January, 2000 to 31st December 2009. We have used Kolmogrov–Smirnov test and Run test which is a non-parametric test and a Unit Root Test, which is a parametric test to examine weak-form market efficiency

New Insights into the Impact of Futures and Options Trading on the Underlying Spot Market Volatility in India

Indian capital market saw the launching of index futures and options on NSE on June 12, 2000 and June 4, 2001 respectively. This launching of futures and options in Indian stock markets was perceived to increase volatility in the stock market by some researchers, while other researchers anticipated decline in volatility. So far, studies have examined volatility implication in macro-level, that is, they measured volatility reduction by comparing volatility of pre and post derivatives period, using various models. This paper tries to study in micro-level, how as to the volatility implications are there across the days of the week in post futures and options period in Indian stock market by isolating volatility related to market-wide factors as well as international-wide factors. This paper also examines the nature of the volatility after the introduction of futures and options contracts. The study has been undertaken with a comprehensive daily data set of S&P CNX Nifty, Nifty Junior and S&P 500 index from October 4, 1995 to May 31, 2007, and to measure the volatility GARCH (1, 1) model has been used. The results of the study show that the presences of derivatives markets on S&P CNX Nifty have declined the volatility marginally and volatility implication in days of the week as a consequence of derivatives introduction revealed the presence of speculative activities in spot as well as derivatives market. And, further results show that options market reduce volatility and stabilize underlying spot market marginally more than futures market.

Positive Feedback Strategy of FIIs in Indian Stock Market: A Sectoral Analysis

The Positive feedback hypothesis stipulates the strategy of rushing in when the markets are booming and rushing out when the markets are on the decline. The present study empirically documents the static and dynamic interaction between FII flows and returns of various indices of National Stock Exchange, using daily data for the variables from 2000 to 2009. Results indicate that there is evidence of positive feedback trading in Indian context in four selective indices viz. Bank Nifty, CNX Midcap, CNX Nifty Junior, and S&P CNX 500 out of fifteen sampled indices. It is also observed that FIIs are not only causating agents but also the effects of the stock return; and there is selective bidirectional relationship between net FII flows and returns of selected indices viz. CNX Midcap, CNX Nifty Junior, S&P CNX 500 and S&P CNX Nifty out of the (Fifteen) sampled indices.

Testing the Random Walk Model in Indian Stock Markets

The present study attempts to examine the random movements in stock indices in the Indian equity market. It tests the random walk hypotheses in daily, weekly and monthly returns of six Indian stock market indices from January 2000 to October 2009. The indices considered for the purpose of the study include Nifty, CNX Nifty Junior, NSE 500, SENSEX, BSE 100 and BSE 500. The study uses Jarque-Bera (JB) Test for testing normality in return series. It also applies Box Pierce Q-Statistics and Ljung-Box (LB) statistics, and Augmented Dickey-Fuller (ADF) test to test whether return series follow random walk or not. The results indicate that there are no random movements in share indices. However, when we apply Lo and MacKinlay (1988) variance ratio test under the assumptions of both homoskedasticity and heteroskedasticity, we observe contradictory results. It is also found that sometimes heteroskedasticity is the source of non-random behavior in share indices.

Information transmission between small and large stocks in the National Stock Exchange in India: An empirical study

Abstract The study investigates return and volatility spillover effects between large and small stocks in the national stock exchange in India using daily index data on S&P CNX Nifty, CNX Nifty Junior and CNX Midcap. The VAR model together with the variance decomposition (VDC) and the impulse response function (IRF) analysis have been employed to uncover both casual and dynamic relationship between the large stocks and small stocks. The results show that there are very significant return spillovers from the market portfolio of large stocks to the portfolio of small stocks. To investigate the volatility spillover the study has used standard BEKK model and asymmetric BEKK model. Although, based on the standard BEKK model we have observed unidirectional volatility spillovers from the portfolio of large stocks to the portfolio of small stocks, the finding was less reliable. The more reliable finding, which is based on asymmetric BEKK model, is that there is bidirectional volatility spillover between the portfolio of large stocks and the portfolio of small stocks.

Impact of Futures and Options on the Underlying Market Volatility: An Empirical Study on S&P CNX Nifty Index

This paper provides a theoretical background to and empirical evidence of the impact of futures and options on the spot market volatility. This study is based on both closing and opening price returns. The sample data consist of daily opening and closing price returns of S&P CNX Nifty, Nifty Junior and S&P 500 index from January 1, 1997 to March 31, 2005. Earlier studies have used different time-series techniques like GARCH, IGARCH, ECM, OLS, etc. to access the impact of derivatives on the spot market volatility. The present study uses family of GARCH techniques to capture the time-varying nature of volatility and volatility clustering phenomenon in the data. The empirical evidence suggests that there are no significant changes in the volatility of the spot market of the S&P CNX Nifty Index, but the structure of the volatility has been changed to some extent. However, the study also found that the new information is assimilated into prices more rapidly than before, and there is a decline in the persistence of volatility since the inception of futures trading.

Revisiting Volume-Volatility Relationship: Evidence from India

Positive relationship between trade volume and return volatility is a well-known empirical verified regularity in the financial research. Several studies examined what causes to volume-volatility to evolve and numerous theoretical explanations have been developed to predict/explore this relationship (see Karpoff (1987) and Board et al (1990) for a number of reasons why price-volume affiliation is positive). However, the recent literature provides evidence of revisiting the volume-volatility relationship as volatility and transaction counts relationship. So far no study examines the role of transactions frequency over and above volume in explaining the volatility; hence, the present study attempts to uncover the relevance of transaction counts for Indian stock market. Specifically, the study considers component stocks of Indian barometer indices, NSE Nifty and Nifty Junior, for the period 2005. In addition, study measures volatility by five minute intra day volatility apart from traditional absolute and squared price changes. Volume is measured as average trade size. The basic hypotheses that the number of transactions drives the volatility rather than the volume has been examined by the cross-sectional averages of Nifty & Nifty Junior stocks after running time series regressions.

Derivatives Trading and Volatility - A Study of the Indian Stock Markets

Equity derivatives trading started on June 9, 2000 with introduction of stock index futures by Bombay Stock Exchange (BSE). National Stock Exchange (NSE) also commenced its trading on 12 June, 2000 based on S&P Nifty. Subsequently, other products like stock futures on individual securities, index options and options on individual securities were introduced. This paper tries to examine the impact of derivatives trading on the volatility of S&P Nifty and BSE Sensex using ARCH/GARCH technique. It also examines the behaviour of volatility of other indices such as Nifty Junior, NSE 200, S&P Nifty 500, BSE-100 and BSE-200 to see whether the market wide volatility has declined over the sample period. Further, surrogate indices like BSE100 and Nifty Junior are used to assess whether the introduction of derivatives per se has been instrumental or the volatility has plummeted in line with general fall in market wide volatility. The results established that introduction of futures and options have negligible or no effect on the volatility as evident from GARCH (1, 1) model. When surrogate index taken into consideration S&P Nifty showed decline in volatility while BSE Sensex exhibited rise in volatility. EGARCH model indicates fall in volatility in case of all indices.