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The extant literature examines the interactions between funding liquidity and market volatility on the equity market. This paper extends the literature and investigates the interactions between funding liquidity and market volatility in the options market. The paper employs the Bayesian structural vector autoregression framework to examine the effects of funding liquidity shock to volatility demand, uncertainty, and risk aversion. We find that positive feedback exists between contraction in funding liquidity and volatility demand, uncertainty, and risk-aversion. Our results are robust to alternate specifications of uncertainty and risk-aversion measures, and alternative ordering of variables. [ABSTRACT FROM AUTHOR]

This paper establishes a predictive relationship between financial vulnerability and volatility in emerging stock markets. Focusing on China and India and utilizing GARCH-MIDAS models, we show that incorporating financial vulnerability can substantially improve the forecasting power of standard macroeconomic fundamentals (output growth, inflation and monetary policy interest rate) for stock market volatility. The findings have significant implications for investors to improve the accuracy of volatility forecasts. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the impact of COVID‐19 on the volatility of stock prices in India with the help of a generalized autoregressive conditional heteroscedasticity model. Daily closing prices of stock indices, Nifty and Sensex from September 3, 2019 to July 10, 2020 has been used for the analysis. Further, the study has been attempted to make a comparison of stock price return in pre‐COVID‐19 and during COVID‐19 situation. Findings reveal that the stock market in India has experienced volatility during the pandemic period. While comparing the result during COVID period with that of the pre‐COVID, we found that the return on the indices is higher in the pre‐COVID‐19 period than during COVID‐19. [ABSTRACT FROM AUTHOR]

This paper intends to study and highlight the change in behavior of volatility of Indian stock market on the introduction of derivatives as a financial instrument, the announcement of union budget every year and the Lok Sabha (lower house of the Indian parliament) elections conducted during 1994-2012. Applying cointegration test between the S&P CNX Nifty and the FUTIDX index, it has been noticed that spot and futures markets are cointegrated with each other. Applying a dummy variable, TGARCH model, this paper aims to examine the impact of the above factors on the volatility of Nifty during the year 1994-2012. [ABSTRACT FROM AUTHOR]

This paper employs a combination of unit root tests and fractional integration technique to test for rational bubbles in Bombay Stock Exchange (BSE). It is indicated in the paper that evidence of a unit root in dividend yield is consistent with presence of rational bubbles in the stock prices. The results in the paper strongly support evidence of rational bubbles in BSE. Moreover, the paper also investigates the degree of conditional volatility persistence to show persistence of shocks to stock price volatility is short-termed. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to investigate the cointegration and volatility spillover dynamics between the USA and South Asian stock markets, namely, India, Pakistan and Sri Lanka. The main objective of this study is to provide the knowledge about integration of financial market and volatility spillovers before, during and after global financial crisis to investors, fund managers and policy-makers. Design/methodology/approach: The Johansen and Juselius cointegration test, Granger Causality test and bivaraite EGARCH model have been applied in this study to examine integration and volatility spillovers between selected stock markets. Findings: The findings show that long-term integration between the USA market and South Asian emerging stock markets. It is found that USA stock market has causal relationship with emerging stock markets in short-term. The findings of EGARCH model reveal that asymmetric volatility spillover effects significant in all selected stock markets in pre, during and post-crisis periods. Furthermore, significant volatility spillover is found from stock markets of USA to all selected South Asian markets during and post-crisis periods. However, volatility spillovers from USA to India and Sri-Lanka markets are significant, while insignificant in case of Pakistani market in pre-crisis period. Overall, we find that returns and volatility spillover effects are higher in financial crisis period as compared to non-financial crisis period. Practical implications: The findings of this paper have important implications for investors, portfolio managers and policy-makers. They can take potential benefits from international portfolio diversification by considering all these facts. The understanding and knowledge of across volatility transmission help them to maximize the gains from diversification and minimize the risk. Policy-makers can develop such strategies which protect the markets of these economies from future financial crisis. Originality/value: Although in finance literature numerous studies have been conducted on integration between different stock markets, most of the studies investigated the integration and volatility spillovers between developed stock markets. However, many studies also analyzed the integration among emerging stock markets in literature review but it is hard to find studies in the context of South Asian stock markets on the effect of global financial crisis on stock markets. The main contribution of this study is to investigate the stock markets integration and volatility transmission between the USA and South Asia by considering the effect of recent 2007 US subprime financial crisis. [ABSTRACT FROM AUTHOR]

This paper tried to investigate the behavior of volatility of Indian stock market keeping in mind, the US subprime crisis. Daily data from 1st April 2007 to 31st July 2010 on S&P CNX Nifty is used for analysis. This paper has used ARCH and GARCH framework for studying behavior of volatility of Indian stock market. The paper has also used threshold GARCH for describing asymmetric properties of stock return volatility. In particular, the objective of the study was to examine the short-term and long-term volatility spillover effects of the US sub-prime crisis on Indian stock market using component GARCH model. The results from the various GARCH models can be used to forecast more accurate volatility which can be used for various purposes like portfolio allocation and option valuation. The results established that stock return volatility of Indian stock market is characterized by persistence, asymmetric properties and permanent component of conditional variance is highly persistent. [ABSTRACT FROM AUTHOR]

This paper examines the stock market volatility and FIIs for the period (2004 -- 2010). The volatility of NIFTY index influenced by the investment inflows of FIIs is modeled using a time series ARIMA approach. The empirical results calibrated through these models are analytic in several fronts. The paper further models and forecasts the index using the data set, where Foreign Institutional Investment (FII), Nominal Effective Exchange Rate (NEER) and Call money rate are considered as the exogenous variables. Finally, the empirical findings show that if the net FII flow is auto regressed with FII flow of various lag periods then it does not have significant influence on the monthly-volatility of the index. The paper also proposes the possible reasons supporting the empirical observations. [ABSTRACT FROM AUTHOR]

Stock markets around the world experienced a massive collapse during the first wave of COVID-19. Roughly in the month of January 2021, the second wave of COVID-19 struck in India, reaching its peak in May, and by the end of May, the active cases started to decline. A third wave is again predicted by the end of 2021, and as such, the COVID-19 pandemic seems to have become a periodic phenomenon over the last couple of years. Therefore, the study of the behavior of the stock market as well as that of the investors becomes very interesting and crucial in this highly volatile and vulnerable market trend. Motivated by these facts, in the present paper, the researcher develops a model for portfolio management, using curve-fitting techniques and shows that this model can encounter the market volatility efficiently in the context of the Indian stock market. The portfolio is designed based on data taken from the National Stock Exchange (NSE), India, during 1 January 2020 to 31 December 2020. The performance of the portfolio in real-life situation during 1 January 2021 to 21 May 2021 is examined, assuming investments are made according to the proposed model. [ABSTRACT FROM AUTHOR]

The epidemic of COVID-19 has impacted the entire global stock market in an unforeseen manner. Due to the uncertainties that occurred in the global economy; the financial market of India also responded to the pandemic and experienced significant volatility. This study empirically explores the effect of COVID-19 on the Indian stock market, considering the COVID-19 scenario. This research explores, employing the regular closing prices of indices like Nifty, the volatility of these indices over the period from 3 September 2019 to 10 July 2020. In addition, the report sought to make a quantitative review of the stock market return in the pre-COVID-19 and COVID-19 situations. The volatility of the indexes is captured using the GARCH model. The results indicate that the Indian stock market has encountered uncertainty during the pandemic era. When c the findings are compared with those of the pre-COVID-19 phase, the author found that before the COVID-19 phase, the returns were higher than during COVID-19.During the first lockout period, from 24 March to 6 April, the returns of both stock markets touched the bottom line. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the forecasting performance of ex-post an ex-ante volatility forecasts against realized return volatility of various time horizon. The competing volatility forecasts are implied volatility, RiskMetrics and GJR-GARCH; the empirical results uncover that implied volatility dominates the other volatility forecast in the prediction of future realized return volatility. The in-sample forecast suggests that ex-ante volatility best explains the future market volatility. The non-overlapping sampling procedure gives the more robust estimate of volatility forecasts, the results reveals that implied volatility forecasts of all horizon appears positive unbiased forecaster of realized volatility. Moreover, the instrumental variable estimation in the presence of error-in-variable clears that implied volatility is free from measurement error; OLS estimates remains more consistent than the 2SLS estimates. The information content of implied volatility encourages the exchanges to construct the implied volatility indices and volatility products on underlying volatility index. [ABSTRACT FROM AUTHOR]

This paper examines the volatility pattern in Indian stock markets during the time period January 1, 2011 to March 31, 2014 using the daily closing prices of two stock indices, S&P BSE Sensex and CNX Nifty. This paper uses asymmetric GARCH models like Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH) to explain the volatility. Considering the minimum values of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), TGARCH model is found to be a superior model for return volatility over EGARCH. The findings suggest that there is no volatility persistence as well as leverage effect in the data during the period under consideration. [ABSTRACT FROM AUTHOR]

Stock market volatility has always been an area of concern for market participants and policy regulators. Through this paper, an attempt has been made to model the volatility in the Indian equity market by employing the standard GARCH(1, 1) model. The paper also investigates whether the volatility on NSE has changed after the introduction of Volatility Index (India VIX) through the GARCH(1, 1) model with a dummy. Accordingly, the period of study for measuring the volatility has been split into two, i.e., the pre-IVIX introduction period (January 1, 2000 to October 31, 2007) and the post-IVIX introduction period (November 1, 2007 to August 31, 2016). The results of GARCH(1, 1) model with a dummy reveal that the volatility of the spot market has declined after the introduction of IVIX in India. In addition, the results of standard GARCH(1, 1) models provide evidence that recent news has a greater impact on the spot market changes in the post-IVIX introduction period. [ABSTRACT FROM AUTHOR]

The primary objective of this paper is to develop a family of GARCH models, combining them with popular Recurrent Neural Network (RNN) models, which can capture the high nonlinear relationships between past return innovations and conditional variance, which is overlooked by standard GARCH models. The next objective is to apply Markov Switching GARCH model and see the differences in the predictive accuracy (according to AIC and BIG criteria and in two viewpoints: MSB and MAD) between the standard GARCH models, GJRGARCH model, RNN-GARCH models and Markov Switching GARCH model by comparing their out-of-sample forecasts. The dataset consists of a series of daily returns obtained from the National Stock Exchange (NSE) for the Indian Equity Markets. The results indicated that the proposed RNN-GARCH model and RNN-Markov Switching models are accurate and quick prediction methods. [ABSTRACT FROM AUTHOR]

Black and Scholes model was developed for valuing the options in derivatives market in the year 1973. This model became the prime tool for pricing options but because of its deficiencies it forced researchers to find out new model for pricing options (Rubinstein, 1985; Hull and White, 1987; Wiggins, 1987; Dumas, Fleming and Whaley, 1998). Option pricing is proven to be very challenging task during high volatility situations whereas Black and Scholes option pricing model is not proven a successful predictor for determining approximate price of the options. Even empirical evidences support that Black and Scholes model produces some biasness in estimating the prices. The main objective of this paper is to find out the efficiency of the Black and Scholes option pricing model for predicting the option prices at Indian Stock Exchanges for which data set from Indian Stock Exchanges will be chosen, market price of option contracts are considered as sample for the year 2008-2015. The actual market price will be compared with the price derived with the help of Black and Scholes model formula. [ABSTRACT FROM AUTHOR]

This paper is an attempt to examine the presence of herd behavior in the stock market of India, which is one of the emerging economies of the world. The study uses the measures suggested by Christie and Huang (1995) and Chang et al. (2000) on National Stock Exchange data. Empirical results based on daily and monthly data indicate that during periods of extreme price movements, equity return dispersions tend to increase rather than decrease, thus providing evidence against the presence of herding in the Indian stock market for the years 2000-2012. Owing to reforms in Indian stock market and the increased presence of institutional players, investors' behavior seems to be more rational, facilitating the application of rational pricing models in the Indian stock markets. [ABSTRACT FROM AUTHOR]

Firstly this research paper aims at discussing how the economic scenario post 1990s forced the Indian economy to open up with the three triggers of Liberalisation, Privatisation and Globalisation. This further discusses the opening of economy for the foreign investors under the given scenario. It narrates the positives and negatives of FIIs in India in terms of their impact on the Indian economy. Secondly it also studies the movement of Indian stock market i.e. BSE Index vs. FIIs investment. Thirdly and more importantly this paper has also made a herculean efforts for studying the impact of FIIs investment on the volatility of Indian stock market on the basis of daily as well as monthly data (from 2000 to 2012). For daily data 3000 observations have been used and for monthly data 156 observations have been used. GARCH and ARCH techniques have been applied for the same. The time period from 2000 to 2012 has been divided into two phases i.e. pre crisis period from 2000 to 2008 and post crisis period from 2009 to 2012. It has been found in the study that FIIs flows have had an impact on the volatility of the Indian stock market in the pre crisis as well as post crisis period. [ABSTRACT FROM AUTHOR]

The Foreign Institutional Investors (FIIs) have emerged as noteworthy players in the Indian stock market and their growing contribution adds as an important feature of the development of stock markets in India. FII is allowed to enter into our country only through stock exchanges either in the form of equity or debt. It makes an impact on the rise or fall of SENSEX, since FII is allowed to be purchased or sold daily. This paper attempts to study the impact of market openings to FIIs, on Indian stock market behavior. India announced its policy on 8th March 2001 for FII investments in equity and related instruments. Using stock market data related to Bombay Stock Exchange, for both before and after the FIIs policy announcement day. An empirical examination has been conducted to assess the impact of the market opening on the return and volatility of stock return. This Research paper is mainly divided into two parts. Firstly researcher has examined impact on stock prices & average return before and after event day. And secondly it's been examined change in volatility in the Indian stock market by comparing variances of return for the event period under study. We have tried to cover one year time period before and after the event day to understand the exact validity and reliability of the result. Moreover the sample size of our study is 500 days daily market return. However validity of results and empirical tests has been taken place by applying Wilcoxon-Mann -Whitney test, also called as the rank sum test. Finally results indicate that there are no significant changes in the Indian stock market average returns and volatility of stock prices returns after changes in percentage of investment from 24% to 49%. [ABSTRACT FROM AUTHOR]

Foreign institutional investors (FIIs) play a vital role in the stock market of a country and Indian stock markets are no exception to this. FIIs bring liquidity, buoyancy and growth in stock markets but at the same time they also enhance the level of volatility and instability. Over past few years the stock markets in India have shown an impressive growth. The stock market indices are making new strides and increasing number of shares are making new highs. Following India's impressive growth story, increasing corporate profitability and competitiveness, and better integration with the world economy, the investment by foreign institutional investors (FIIs) in the stock markets of India has gone up tremendously. Investment decisions of foreign institutional investors in India are affected by so many factors. Investment behavior of domestic institutional investors (DIIs) is one such important factor. This research paper is an attempt to analyze the impact of domestic institutional investors on the investment decision of foreign institutional investors in India. In other words, this study explores whether Domestic Institutional Investors affect the investment decisions of Foreign Institutional Investors in India or not. For this purpose, researchers have used regression analysis. Mutual fund investments have been taken as proxy for investment by DIIs. Investment patterns of FIIs and DIIs have been divided into eight variables i.e. FII Equity Purchases, FII Equity Sales, FII Debt Purchases, FII Debt Sales, MF Equity Purchases, MF Equity Sales, MF Debt Purchases and MF Debt Sales respectively. The study reveals that investment decisions of DIIs affect the investment decisions of FIIs. [ABSTRACT FROM AUTHOR]

In general, any one known to stock market is acquainted with the phenomenon of bull and bear phases, but whether the traders or investors put air to these phases while making a decision to buy, sell, or stay invested. The present paper attempts to identify and analyse the two most popular market phases, i.e. bull and bear, for better investment decisions with the use of Bry and Boschan Algorithm and time series data. Further, it seeks to analyse the distributional characteristics of the variances in stock returns and search evidence of asymmetries, if any, in volatility under different market conditions which may help to shed light on the bull and bear phases of Indian equity market. The study arrange for evidence that in bull markets, stock prices run far ahead of earnings and for fairly long periods of time. The paper indicates 12 bull and bear phases in the Sensex and Nifty during the sample period of 19 years with the associated factors responsible for the shift of bull and bear market phases. The results provide considerable support for the view that markets choose to ignore adverse possibilities and react with zest to favourable possibilities and market declines can partly be explained by increases in risk. [ABSTRACT FROM AUTHOR]

This paper presents an empirical analysis of the relationship between trading volume and stock return volatility in the Indian stock market. The initial analysis focus upon the volume-price change relationship. The relationship between price change and trading volume, irrespective of the direction of the price change, is significant across three alternative measures of daily trading volume for the aggregate market and individual stocks. Furthermore, evidence is found supporting the hypothesis that the volume-price change slope for negative returns is smaller than the slope for positive returns, thereby supporting an asymmetric relationship. Trading volume is then examined in the context of conditional volatility using a GARCH framework. The findings show a reduction in the significance and magnitude of the conditional variance equation coefficients, and a reduction in the persistence of variance when trading volume is added as an exogenous variable. Hence, there is prima facie evidence that if trading volume proxies for the rate of information arrival, then ARCH effects and much of the persistence in variance can be explained. [ABSTRACT FROM AUTHOR]

The paper attempts to explain the association between Foreign Institutional Investor (FII) flows to Indian equity markets and option implied Volatility Index (VIX). Prior studies involving the relationship between FII flows and realized volatility provide contradictory findings and are largely inconclusive. Little empirical work is found to explain the relationship between FII flow and expected volatility as measured by the option implied VIX. We find evidence that India VIX does not have any influence on FII flows to Indian equity markets. Instead, there is evidence of significant reverse causality. The results indicate that the collective perception in the minds of investors about future volatility is fueled by FII flows. [ABSTRACT FROM AUTHOR]

Volatility forecasting is an important area of research in financial markets and immense effort has been expended in improving volatility models since better forecasts translate themselves into better pricing of options and better risk management. In this direction, the present paper attempts to model and forecast the volatility (conditional variance) of the S&P CNX Nifty index returns of Indian stock market, using daily data for the period from January 1, 1996 to January 29, 2010. The forecasting models that are considered in this study range from the simple GARCH(1, 1) model to relatively complex GARCH models, including the Exponential GARCH(1, 1) and Threshold GARCH(1, 1) models. Based on out-of-sample forecasts and a majority of evaluation measures, the results show that the asymmetric GARCH models do perform better in forecasting conditional variance of the Nifty returns rather than the symmetric GARCH model, confirming the presence of leverage effect. The findings are consistent with those of Banerjee and Sarkar (2006) that relatively asymmetric GARCH models are superior in forecasting the conditional variance of Indian stock market returns rather than the parsimonious symmetric GARCH models. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to empirically investigate whether call auctions which batch orders for simultaneous execution, may restrain stock market volatility. Design/methodology/approach - The authors use high-frequency data to investigate volatility changes following the suspension of opening and closing call auctions on the National Stock Exchange (NSE) of India in 1999. The authors evaluate this issue by considering both modelled and realised volatility. Using a GARCH approach the authors model intra-day volatility for the trading days preceding and succeeding the auction suspension. The authors also scrutinise return distributions to look for volatility changes during different parts of the day. Findings - When interpreted collectively, the empirical results suggest that the auction suspension was followed by reduced volatility particularly in the middle of the trading day and at the closing. Practical implications - Given that auctions are often incorporated in trading systems with the aim of curtailing volatility, the main conclusion, that the auction suspension was followed by lower volatility, has important practical inferences. Auctions cannot be automatically relied on to reduce volatility. The intricacies of the auction protocol and their interaction with ancillary market microstructure features may impact on auction efficacy. Originality/value - The paper adopts a novel approach towards assessing the effectiveness of auctions by considering an unusual occurrence of an auction suspension. The empirical setting enables a clear comparison of the respective regimes since these periods do not materially differ in other subsidiary aspects. This is a noteworthy factor, since the empirical contexts considered in prior studies, often feature several simultaneous changes. [ABSTRACT FROM AUTHOR]

Retail participation in Indian markets has remained at very low levels due to the perception about market risk. This academic research paper to evaluate and understand the level of risk involved in Indian equity market and to make retail investing community understand its impact on returns when invested for a long tenure. Paper is not intended to motivate retail investor to take more risk in stock market but is about informing and educating with the help of various statistical and financial tools, to understand how the negative impact of volatility gets reduced over a period of time. Retail investment decisions are often based on market noise, ad-hoc and short term in nature. Negative impact due to high volatility can not only result in losses for small investor but it takes away their courage and motivation to invest further. Study is to understand the necessity to switch to the decisions which are economic fundamental focused and long term in nature, so as the fruits of economic growth are more evenly distributed and are enjoyed by small and retail investors. [ABSTRACT FROM AUTHOR]

The Markowitz portfolio optimization model, popularly known as the Mean-Variance model, assumes that stockreturns follow normal distribution. But when stock returns do not follow normal distribution, this model wouldbe inadequate as it would prescribe sub-optimal portfolios. Stock market literature often deliberates that stock returns are non-normal. In such context the Markowitz model would not be sufficient to estimate the portfolio risks. The purpose of this paper is to expand the original Markowitz portfolio theory (mean-variance) via adding the higher order moments like skewness (third moment about the mean) and kurtosis (fourth moment about the mean) in the return characteristics. The research paper investigates the impact of including higher moments using multi-objective programming model for portfolio stock selection and optimization. The empirical results indicate that the inclusion of higher moments had a considerable impact in estimating the returns behavior of portfolios. The portfolios optimized using all the four moments, generated higher returns for the given level of risk in comparison to the returns of the Markowitz model during the study period 2000-2011. The results of this study would be immensely useful to fund managers, portfolio managers and investors as it would help them in understanding the Indian stock market behavior better and also in selecting alternative portfolio selection models. [ABSTRACT FROM AUTHOR]

Macroeconomic stability is crucial not only for economic growth but also for the living standards and investments in a market economy. The macroeconomic variables like crude oil price, gold price, exchange rate, inflation and stock returns are highly correlated to each other and are highly volatile, and the volatility in one market spills over to other markets. This paper analyses the dynamic causality between crude oil price, exchange rate and BSE Sensex and their volatilities in India. The daily data on macro variables for 14 years between January 2006 to March 2019 is used in the GARCH estimation of causal effects of volatility spillovers. The GARCH estimates show that the volatility and volatility spillover of one market cause volatility and volatility spillovers in other markets in India. The crude oil price and exchange rate volatility and volatility spillovers cause volatility in BSE Sensex. The volatility in BSE Sensex is highly overdone by internal shocks of the stock market itself. [ABSTRACT FROM AUTHOR]

The paper seeks to explore possible volatility transmission mechanism within the economy, if any for Indian stock market in recent years. Specifically, it tries to explore whether sectoral shocks are being transmitted to the market and vice versa. The capital goods and the consumer durable sectors are the two most predominant sectors, their contribution to the volatality of SENSEX being the most. Among the major findings, this paper discerns that market to sector volatility transmission has been more prominent in case of BSE SENSEX than BSE200; while sector to market volatility transmission has been more significant in case of BSE200. Most of the market volatility is coming from the variability in capital goods sector and consumer durable sector. However, the IT sector has an insignificant impact on market volatility and its variability is hardly influenced by that of market. Hence, even in this era of globalization, IT sector remains an isolated sector, while traditional sectors remain the most important ones. [ABSTRACT FROM AUTHOR]

Derivatives trading is always at the center of discussion in any financial phenomenon. It has been discussed, argued and defended in many forms as to how the derivatives trading has brought distress and crisis in financial market. While a few derivatives disaster stories were enough to bring the entire business of derivatives under the limelight and make every one worry about unknown risks associated with derivatives, it has gained popularity as a measure of risk mitigation too. This paper explores the impact of futures trading of Bank Nifty Index on the underlying cash market of the sectoral index of Bank Nifty. This is an attempt to study how the onset of futures trading has affected that particular industry in terms of inducing or stabilizing volatility in the spot market. Moreover, the informational efficiency and market integration of the spot market have also been analyzed as a result of futures trading in that segment. GARCH model with futures dummy has been used to analyze the impact of futures trading on spot Bank Nifty Index volatility during the period 2000 to 2013. Two separate GARCH models have been fitted in the pre- and post-futures period to examine the relationship between new information release and spot market volatility following the onset of futures trading. The study has shown that over the time, index futures trading improved the overall performance of the spot market of banking sector by providing better exposure to global factors, by quicker information assimilation, and by reducing the persistence of volatility. [ABSTRACT FROM AUTHOR]

According to French and Roll (1986), there is greater volatility when the market is open than when it is closed. That is to say, the time series volatility of prices, where each stock is considered individually as a univariate time series, is higher when the market is open than when it is closed. We extend this result in this paper by showing that the cross-sectional analogue of this statement is true as well. Indeed, one of our major findings is that there is greater cross-sectional dispersion in prices when the market is open than when it is closed. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to estimate time-varying conditional volatility, and examine the extent to which trading volume, as a proxy for information arrival, explain the persistence of futures market volatility using National Stock Exchange S&P CRISIL NSE Index Nifty index futures. Design/methodology/approach - To estimate the volatility and capture the stylized facts of fat-tail distribution, volatility clustering, leverage effect, and mean-reversion in futures returns, appropriate ARMA-generalized autoregressive conditional heteroscedastic (GARCH) and ARMA-EGARCH models with generalized error distribution have been used. The ARMA-EGARCH model is augmented by including contemporaneous and lagged trading volume to determine their contribution to time-varying conditional volatility. Findings - The paper finds evidence of leverage effect, which indicates that negative shocks increase the futures market volatility more than positive shocks of the same magnitude. In addition, the results indicate that inclusion of both contemporaneous and lagged trading volume in the GARCH model reduces the persistence in volatility, but contemporaneous volume provides a greater reduction than lagged volume. Nevertheless, the GARCH effect does not completely vanish. Practical implications - Research findings have important implications for the traders, regulatory bodies, and practitioners. A positive volume-price volatility relationship implies that a new futures contract will be successful only to the extent that there is enough price uncertainty associated with the underlying asset. Higher trading volume causes higher volatility; so, it suggests the need for greater regulatory restrictions. Originality/value - Equity derivatives are relatively new phenomena in Indian capital market. This paper extends and updates the existing empirical research on the relationship between futures price volatility and volume in the emerging Indian capital market using improved methodology and recent data set. [ABSTRACT FROM AUTHOR]

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 derivatives in Indian stock markets was perceived to increase volatility in the stock market by some researchers, at the same time some other researchers anticipated decline in volatility. This paper tries to study whether the Indian stock markets show some significant change in the volatility after the introduction of derivatives trading. The study has been undertaken with a comprehensive daily data set from January 1, 1996 to March 31, 2007. To measure the volatility GARCH (1, 1) model has been used. The results show that the presence of derivatives markets on S&P CNX Nifty have declined the volatility marginally, and less reduction of volatility in spot market seems that presence of uninformed traders' activities in derivatives market. Marginal volatility reduction in spot market is associated with the increase in market efficiency and improved market depth in post derivatives period. This identification rejects "destabilizing forces hypothesis and supports "market completion" hypothesis on derivatives. [ABSTRACT FROM AUTHOR]

This paper studies the impact of market opening to FIIs, on Indian stock market behavior. India announced its policy regarding the opening of stock market to FIIs for investment in equity and related instruments on 14th September 1992. Using stock market data related to Bombay Stock Exchange, for both before and after the FIIs policy announcement day. An empirical examination has been conducted to assess the impact of the market opening on the returns and volatility of stock return. We found that while there is no significant changes in the Indian stock market average returns, volatility is significantly reduced after India unlocked its stock market to foreign investors. [ABSTRACT FROM AUTHOR]

Purpose — The paper aims to study the impact of the introduction of Nifty index futures on the volatility of the Indian spot markets by use of econometric models. Design/methodology/approach — The study considered six measures of volatility, the dynamic linear regression model, and the GARCH models to investigate volatility in National Stock Exchange (NSE) Nifty prices both before and after the onset of futures trading. Findings — The GARCH analysis confirmed no structural change after the introduction of futures trading on Nifty, and found that whilst the pre-futures sample was integrated, the post-futures sample was stationary. Spot returns volatility is found to be less important in explaining spot returns after the advent of futures trading in NSE Nifty. Practical implications — The results imply that futures markets serve their prescribed role of improving pricing efficiency and improve the quality of information flowing to spot markets. This will enable investors to prudently structure their strategies investing in both spot and futures markets. Originality/value — This study is an original piece of work towards exploring the impact of the introduction of futures trading on cash market volatility in an emerging economy like India. [ABSTRACT FROM AUTHOR]

This paper evaluates the performance of conditional variance models using high-frequency data of the National Stock Index (S&P CNX NIFTY) and attempts to determine the optimal sampling frequency for the best daily volatility forecast. A linear combination of the realized volatilities calculated at two different frequencies is used as benchmark to evaluate the volatility forecasting ability of the conditional variance models (GARCH (1, 1)) at different sampling frequencies. From the analysis, it is found that sampling at 30 minutes gives the best forecast for daily volatility. The forecasting ability of these models is deteriorated, however, by the non-normal property of mean adjusted returns, which is an assumption in conditional variance models. Nevertheless, the optimum frequency remained the same even in the case of different models (EGARCH and PARCH) and different error distribution (generalized error distribution, GED) where the error is reduced to a certain extent by incorporating the asymmetric effect on volatility. Our analysis also suggests that GARCH models with GED innovations or EGRACH and PARCH models would give better estimates of volatility with lower forecast error estimates. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, we examine two important propositions for the Indian options market: (1) the relationship between implied volatility and moneyness referred to as volatility smile and (2) the potential determinants of the smile asymmetry. We use daily data for the S&P CNX Nifty index call and put options and the underlying market index for the calendar years 2004 and 2005. We find that the volatility functions exhibit a positive slope in the Indian context using alternative measures of moneyness, thus confirming the consistency of our findings. Our evidence on smile asymmetry is in contrast with findings for mature markets, which exhibit negative asymmetry profiles in general. This may be owing to differences in investors' behaviour and market microstructure between mature and emerging markets. We also show that historical volatility and time to expiration are the potential determinants of smile asymmetry in India, as is the case with international evidence. We feel that a strong theoretical foundation should be provided for this observable empirical phenomenon. [ABSTRACT FROM AUTHOR]

This paper examines the impact of introduction of derivative securities on volatility of underlying stocks and index. Though the empirical evidence in international arena is mixed, the results of this study support the declining volatility hypothesis in context of the Indian stock market. It also indicates that derivatives have stabilizing effect and their introduction has led to decline in volatility of underlying assets. The findings have largely remained the same when volatility has been examined with different diagnostic tools or for different sample periods. Finally, these findings provide rationale for introduction of futures and option contracts on more stocks as they contribute to enhancing the efficiency of underlying stock market. The study has important policy implication on the derivatives markets. The study making a favourable case of empirical evidence for deepening the derivatives segement in India. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the trading activity in options market based on information about expected future volatility in spot market. We employ Common Implied Volatility as a measure of expected volatility and options volume and changes in Open Interests as measures of options trading activity. We first test for simultaneous information flow in the two markets using multiple regression technique. Next, we test for information based or hedge based use of options using Trivariate Vector-auto Regression framework. We further consider the classes of options moneyness and the market trends in our analysis to examine if the trader's preference of options changes with change in description of options intrinsic value and market environment. We use daily closing data of S&P CNX Nifty Index options traded on National Stock Exchange, India. We, for the most part, find negative and significant relationship in contemporaneous regression suggesting active trading by arbitrageurs. A feedback relationship is observed in vector auto regression analysis suggesting that options are traded in India for both information based trading and hedging purposes. We also observe the relationship to be varying when market trends and classes of options moneyness are considered. This indicates that traders are not indifferent in their choice of trading venue when market conditions and factors change. The results of this study are helpful for traders in managing the risk and return of their portfolio based on volatility forecast. This study is distinctive as it examines the scarcely researched area of volatility informed trading in an emerging market set up. [ABSTRACT FROM AUTHOR]

This paper proposes a hybridized framework of Support Vector Machine (SVM) with K-Nearest Neighbor approach for Indian stock market indices prediction. The objective of this paper is to get in-depth knowledge in the stock market in Indian Scenario with the two indices such as, Bombay Stock Exchange (BSE Sensex) and CNX Nifty using technical analysis methods and tools such as predicting closing price, volatility and momentum of the stock market for the available data. This hybrid model uses SVM with different kernel functions to predict profit or loss, and the output of SVM helps to compute best nearest neighbor from the training set to predict future of stock value in the horizon of 1 day, 1 week and 1 month. The proposed SVM and KNN based prediction model is experienced with the above mentioned distinguished stock market indices and the performance of proposed model has been computed using Mean Squared Error and also been compared with recent developed models such as FLIT2NS and CEFLANN respectively. The limitation of both of those existing models undergoes complex weight updating procedures, whereas, proposed SVM-KNN hybridized model scales relatively well to high dimensional data and the trade-off between classifier complexity and error can be controlled explicitly and have better prediction capability. [ABSTRACT FROM AUTHOR]

Emerging markets equity indexes are usually seen as high return with a high degree of volatility associated with them. However, this should not be the case, if you choose high-quality firms that have increasing returns and lower volatility. The intent of this paper is to introduce the risk weighted alpha (RWA) indexation method that helps identify stocks that have stable increasing returns with lower volatility. In order to review this method in the context of emerging markets scenario, this paper takes the example of the Sensex index listed on the Bombay Stock Exchange (BSE) that comprises India's top 30 stocks by market capitalisation. Results show that some stocks like Hindustan Lever do show increasing returns and lower volatility. The RWA Sensex index outperforms the BSE Sensex index, while still maintaining a beta that is the same as that in the BSE Sensex index. [ABSTRACT FROM AUTHOR]

The present paper empirically examines the theoretical linkage between stock market volatility and macroeconomic volatility in emerging Indian stock market covering the data period from July 1996 to March 2013. Unlike the previous studies, the present study investigates the issue with two stage estimation techniques. Conditional volatility is extracted by employing univariate autoregressive conditional heteroskedasticity models. Further, multivariate VAR model along with impulse response function, block exogeneity and variance decomposition are carried out to analyze the relationship between stock market volatility and macroeconomic volatility. Data on macroeconomic variables namely output, foreign institutional investments, exchange rate, short term and long-term interest rates, broad money supply, inflation and stock market indices BSE Sensex and NSE Nifty are used for analysis. The findings suggest a linkage between macroeconomic volatility and equity market volatility. [ABSTRACT FROM AUTHOR]

This study examines the impacts of domestic and counter-terrorist attacks on India's securities markets after collecting time series data of SENSEX and NVIX during the period 1980-2015 for the empirical work. We employ the conditional volatility framework to estimate stock market volatility around the terrorist events, presenting empirical results that corroborate earlier studies and report a significant impact of terrorist activities on investors' sentiment. Stock market volatility remains volatile for pre- and post-terrorist events. This paper is the first empirical research investigating the impact of terrorist attacks on stock market performance in an emerging economy like India, such as stock returns and investors' fear-gauge-index (NVIX). The implications of the study underpin a forward-looking direction on stock market volatility and investors' behavior towards risky capital investment decisions. [ABSTRACT FROM AUTHOR]

This research explores the predictive power of the India VIX (volatility index) in emerging markets from April 2009 to March 2011. The results of the study show that the models including both the volatility indicator and the option market information have a stronger predictive power. With respect to the trading information from different types of investors in option markets, the trading information from the foreign institutional investors in option markets demonstrates a significantly positive relationship with the stock market volatility. In addition, the results of this paper also reveal that the India VIX GARCH volatility forecasting and stock index options are a strong indicator of future stock market volatility. The GARCH outperforms the historical volatility and the VIX volatility forecast in assessing the activities of Indian capital market. [ABSTRACT FROM AUTHOR]

This paper intends to study the impact of global meltdown of 2008 on the overall stock market volatility, and the change in the performance of 20 reputed companies, from four sectors, listed under the National Stock Exchange. An effort has been made to find out the status of recovery of these 20 companies after the global recession began in the last week of October 2008. The objective of this study is to find out the extent of loss suffered by these companies and the time taken by them for recovery. The analysis will be of use to investors as well as policy makers. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the dynamic linkages between BSE Banking, Power and IT sector during the one year period i.e. 2012 by using intraday daily data, which determine the intra-day volatility. The study carries out a broad analysis from descriptive statistics and then to inferential statistics to examine the difference in the average returns within these three sectors. The present work examines the volatilities in Indian Stock Market (BSE-banking, power and IT) by comparing the volatilities. Volatility estimation is important for several reasons and for different people in the market. Intraday volatility is also very much under control and has came down compared to past years. The issue of volatility and risk has become increasingly important in recent times to financial practitioners, market participants, regulator and researchers. Among the main concerns, which are currently expressed include: has the world's financial system become more volatile in recent times. [ABSTRACT FROM AUTHOR]

It has been almost a decade since the introduction of derivatives instruments in Indian bourses like Options and Futures trading replacing thereby age old Badla transactions and almost two decades since the introduction and implementation of liberalization, privatization and globalization policies in Indian economy. This has resulted in a sea change in growth and development of Indian economy and enhanced activity and trade in Indian stock markets. This paper examines and compares the reaction of futures and cash markets to the flow of information and tries to establish a lead-lag relationship between the two markets in terms of returns and volatilities being experienced by NIFTY and NIFTY futures indices in two different markets. Our results suggests that though there is a strong contemporaneous and bi-directional relationship among the returns in the spot and futures market, the spot market has been found to play comparatively stronger leading role in disseminating information available to the market, and therefore said to be more efficient. Apart from this, there is also interdependence (in both direction) and therefore symmetric spillovers among the stock return volatility in the spot and futures market. [ABSTRACT FROM AUTHOR]

The present paper is aimed at checking weak form of efficiency hypothesis for Indian stock market by using daily data for Bombay Stock Exchange, Sensitive Index (sensex) for the period July 1, 1991 to Dec. 29, 2006. The Indian stock market indicated efficiency as random walk hypothesis for sensex is accepted. The results of variance ratio test and unit root test are similar and accept the random walk for Indian stock market but the results from autocorrelation and Ljung Box (QLB) test reject the hypothesis of random walk. Since variance ratio test is more powerful than the other tests performed in the study, we go by the results of variance ratio test. The volatility persistence is due to the asymmetry in the availability of publicly available information other than historical prices of stock indices and private information, which is generally withheld by select groups such as mutual funds, management, financiers and stock exchange officials. [ABSTRACT FROM AUTHOR]

Globalisation and capital market reforms should result in improved market efficiency. This paper examines the efficiency of the Indian stock market from 1991-2002, the period which roughly coincides with the period after liberalisation, globalisation and initiation of capital market reforms. Runs tests and serial correlation tests of the BSE 200 index and 158 stocks support the view that the market is moving towards efficiency. However, efficiency increased in the period following reforms, but decreased slightly in the subsequent period. Volatility also decreased after the first few years and subsequently increased. This indicates that there is need for vigilance as the benefits of globalisation and reforms can be diluted by inefficiency and volatility due to domestic and international events and market manipulation. Also, maximum departure from normality and efficiency was observed with daily data and minimum with monthly returns. This should be kept in mind when interpreting and comparing results from studies using varying data intervals. [ABSTRACT FROM AUTHOR]

The paper analyzes the varying perceptions of stock price volatility of Indian capital markets along with identifying possible reasons for volatility and measures the degree of volatility. It is evident from the values of co-efficient of variation and standard deviation that the market capitalization of NSE was highly volatile or less consistent when compared to BSE. There was a greater crash in the market prices was on account of Kethan Parekh stock market scam, Coupled with bearish trend in the markets apart from various other factors. Number of companies listed has declined abnormally over a decade and the share of NSE as increased significantly and equaling with that of BSE listed companies. Volatility in number of shares traded daily on NSE and BSE varies between 1.90 to 1.24 and 2.00 to 1.32 respectively. This represents that the volatility rate in BSE is greater than that of NSE. Relevance of the budget on stock price volatility is diminishing every year because of the critical policy decisions are taken on a regular basis by the government. [ABSTRACT FROM AUTHOR]