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This study aims to explore the linkage between fluctuations in the global crude oil price and equity market in fast emerging economies of India and China.

The present research uses wavelet decomposition and maximal overlap discrete wavelet transform (MODWT), which decompose the time series into various frequencies of short, medium and long-term nature. The paper further uses continuous and cross wavelet transform to analyze the variance among the variables and wavelet coherence analysis and wavelet-based Granger causality analysis to examine the direction of causality between the variables.

The continuous wavelet transform indicates strong variance in WTIR (return series of West Texas Instrument crude oil price) in short, medium and long run at various time periods. The variance in CNX Nifty is observed in the short and medium run at various time periods. The Chinese stock index, i.e. SCIR, experiences very little variance in short run and significant variance in the long and medium run. The causality between the changes in crude oil price and CNX Nifty is insignificant and there exists a bi-directional causality between global crude oil price fluctuations and the Chinese equity market.

To the best of the authors’ knowledge, very limited work has been done where the researchers have analyzed the linkage between the equity market and crude oil price fluctuations under the framework of discrete wavelet transform, which overlooks the bottleneck of non-stationarity nature of the time series. To bridge this gap, the present research uses wavelet decomposition and MODWT, which decompose the time series into various frequencies of short, medium and long-term nature.

Muslim’s hope that the holy month of Ramadan will create something more valuable for them. Through fasting and good actions, they can get rewarded twice than they normally can achieve. With this motivation, the purpose of this paper is to investigate the holy month of Ramadan effect on the returns and volatility of the Shariah index in India.

Using the ordinary least square methods, this paper examines the impact of Ramadan effect on the returns of the Shariah index in India. This paper further investigates the impact of the holy month of Ramadan effect on the volatility of the Shariah index by applying GARCH-modified models. This paper categorizes the Ramadan days into three parts, namely God’s Mercy, God’s Forgiveness and Emancipation from hellfire to examine the relationship between the Ramadan effect and the returns and volatility of the Shariah index in India.

The results show that the returns during the month of Ramadan as a whole are statistically significant. The results further motivate that its last ten days have high influences than other days over the period. Finally, the study examines the Ramadan effect on volatility by applying GARCH modified models and finds an evidence of Ramadan effect during the first ten days of Ramadan month.

The positive impact of Ramadan increases on the days associated with higher worship intensity. The study provides an important information to the ethical investors to invest in the Shariah stocks during Ramadan days. This information is very useful for the investors to get an abnormal return during the Ramadan days.

The purpose of this paper is to examine the significance of gender diversity on corporate boards in India in the light of recent regulatory reform introduced in the Companies’ Act, 2013 which mandated the presence of at least one woman on the corporate boards of all the listed firms.

Based on a panel of 300 firm-year observations for 15 years from 2001 to 2015, regression analysis has been conducted to analyze the relation between gender-related variables of corporate boards with firm-specific financial characteristic, cost of equity (COE) and return on assets (ROA) of firms listed in CNX Nifty, a major financial market index of India.

The analysis indicates that boards with gender diversity explain a slightly more than 5.5 percent change in a firm’s COE and have a much higher impact of 45 percent on a firm’s ROA. The presence of female directors on the boards and their independence have a negative association with the COE, whereas the level of involvement of female directors on different committees has a positive association with the ROA.

The findings may help theorists in defining the right mix of female on the corporate boards in an emerging economy. Also, by taking input from the findings, regulators and industry can formulate policies to foster gender diversity on corporate boards in India.

This study considers the recent regulatory norm introduced in India. This issue has still not been discussed and analyzed by researchers in India. It attempts to explain the impact a gender diverse board can make on a firm’s performance. It also makes valuable recommendations to improve the norms intended to more effectively foster gender diversity on corporate boards in India.

The purpose of this paper is to examine the informational efficiency and integration simultaneously for select Asian and US stock markets while considering the impact of recent financial crisis.

Daily stock market data from 13 world markets covering the period of ten years (from January 1, 2000 to December 31, 2010) is tested using Run test, Unit root test, GARCH(1, 1) model, Pearson correlation coefficient, Johansen’s cointegration test and Granger causality test.

It is concluded that the markets under study are inefficient in weak form which creates the chances of earning abnormal returns for the investors. Furthermore, the markets are found to be correlated and integrated in long-run, which makes the international fund diversification insignificant. The degree of inefficiency, in general, is not affected by the recent financial crisis but the level of integration among stock markets is reduced with the effect of recent financial crisis.

Individual/institutional investors, portfolio managers, corporate executives, policy makers and practitioners may draw meaningful conclusions from the findings of this type of researches while operating in stock markets. They can use such studies for the management of their existing portfolios as their portfolio management strategies may be, up to some extent, dependent upon such research work.

The originality of the present study lies in the fact that this paper is an attempt to fill the time gap of comprehensive researches on Asian and US markets and an effort to test stock market efficiency and integration simultaneously.

The purpose of this paper is to examine the long‐run relationship between the Indian capital markets and key macroeconomic variables such as interest rates, inflation rate, exchange rates and gross domestic savings (GDS) of Indian economy.

Quarterly time series data spanning the period from January 1995 to December 2008 has been used. The unit root test, the co‐integration test and error correction mechanism (ECM) have been applied to derive the long run and short‐term statistical dynamics.

The findings of the study establish that there is co‐integration between macroeconomic variables and Indian stock indices which is indicative of a long‐run relationship. The ECM shows that the rate of inflation has a significant impact on both the BSE Sensex and the S&P CNX Nifty. Interest rates on the other hand, have a significant impact on S&P CNX Nifty only. However, in case of foreign exchange rate, significant impact is seen only on BSE Sensex. The changing GDS is observed as insignificantly associated with both the BSE Sensex and the S&P CNX Nifty. The paper, on the whole, conclusively establishes that the capital markets indices are dependent on macroeconomic variables even though the same may not be statistically significant in all the cases.

This study emphasises on the impact of macroeconomic variables on the stock market performance of a developing economy, whose performance is measured by these variables.

The purpose of this paper is to test the long-term effects of price and volume with the help of Downward Sloping Demand Curve (DSDC) hypothesis, and also the short-term price and volume effects with the help of Price Pressure Hypothesis (PPH) for the index revisions on the S&P CNX Nifty 50 index.

In order to report the long-term and short-term effects, the current study reviews two testable hypotheses, namely, DSDC hypothesis and PPH. The study has used the event study approach by including GARCH (1, 1) conditional variance in the market model.

The results report that, the added stocks experienced a significant increase in price and volume on the effective date; whereas the deleted stocks experienced significant volume levels and insignificant price levels on the effective date. Accordingly, the study finds support in favor of PPH.

The study could not find evidence to support the most studied DSDC hypothesis.

Index reorganization presumably affects the fund managers, domestic as well as international investors. As a result, studying the effect of index changes is a subject of attention to academicians and investors alike.

The study contributes to the body of knowledge on index inclusion and exclusion effects by providing Indian evidence on long-term and short-term price and volume effects, and also documenting contrary results to the previous Indian and global research works.

The purpose of this paper is to investigate the interrelationships amongst the sector‐specific indices of the Qatar Exchange (QE) (i.e. Banking and Financial Institutions (BFI), Industrial (IND), Insurance (INS), and Services (SER)). More specifically, three key issues are explored in this study. First, the long‐run relationships amongst the sectors. Second, the short‐run causal relationships amongst them; and third, the relative degree of endogeneity/exogeneity of each sector.

To address the issues of interest, the author employs the econometric analyses of Johansen's multivariate cointegration, Granger's causality, and generalized forecast error variance decomposition. This battery of techniques gives the opportunity to examine the nature of both long‐ and short‐run intersectoral relationships in the QE. To augment the robustness of the empirical analysis, daily as well as weekly closing stock price indices for the four sectors of the Qatar Exchange are used, spanning the period from January 2, 2008 up to April 7, 2011.

Based on daily and weekly data, the results of Johansen's multivariate cointegration analysis suggest that the four sector indices of the QE share a long‐term equilibrium relationship. The Granger's causality analysis based on daily and weekly datasets provides clear evidence that the BFI sector seems to be a significant causal factor in regard to the price predictability of the remaining sectors in the short run, and that the SER sector surprisingly seems to have the least influential role. Finally, the results of the generalized forecast error variance decomposition analysis using daily data show that the IND and BFI appear to be the most exogenous sectors, whereas the SER and INS are the most endogenous ones. The results based on weekly data confirm the relative exogeneity of the BFI sector and the relative endogeneity of the SER sector.

The findings of this study hold practical implications for individual and institutional investors alike. The potential gains derived from cross‐sector diversification could be rather limited, given the significant degree of interrelationships found amongst the sector indices of the QE. Moreover, the composition of domestic portfolios based on sector‐level investments should be revisited, particularly after major events. The findings also bring some important insights for policymakers. Given the influential role played by the BFI sector in the Qatari economy, policymakers should design appropriate strategies that curb the spread of unanticipated shocks originating from this sector to its counterparts. Besides, due to the considerable degree of endogeneity of the SER sector, it is essential for policymakers to set up precautionary regulations, with the aim of minimizing its vulnerability to common shocks in turbulent times.

Building upon the extant research and focusing on a relatively unexplored market, the paper represents a pioneer attempt to provide empirical evidence on the interdependence structure amongst the sector‐specific indices of the Qatar Exchange.

The purpose of this paper is to assess the informational efficiency of S&P CNX Nifty index options in Indian securities market. The S&P CNX Nifty index is a leading stock index of India, consists of 50 most frequently traded securities listed on NSE. For the purpose, the study covers a period of six years from 4 June 2001 (the starting date for index options in India) to 30 June 2007.

The informational efficiency of implied volatilities (IVs) has been tested vis‐à‐vis select conditional volatilities models, namely, GARCH(1,1) and EGARCH(1,1). The tests have been carried out for “in‐the‐sample” as well as “out‐of‐the‐sample” forecast efficiency of implied volatilities.

The results of the study reveal that implied volatilities do not impound all the information available in the past returns; therefore, these are indicative of the violation of efficient market hypothesis in the case of S&P CNX Nifty index options market in India.

The finance managers, in Indian context, should rely on conditional volatility models (especially the EGARCH(1,1) model) compared to IV‐based forecasts to predict volatility for the horizon of one week. The stock exchanges and market regulator (SEBI) need to take certain initiatives in terms of extending the short‐selling facility and start trading of volatility index (VIX) to enhance the accuracy of IV‐based forecasts.

The paper addresses an issue which is still unexplored in the context of Indian securities market and in that sense makes an important contribution to literature on microstructure studies.

The purpose of this paper is to understand the patterns of the implied volatility (IV) of the Indian index option market and its relationship with moneyness (called the volatility smile). Its goal is also to ascertain the determinants of IV.

For this purpose, IVs were computed from the daily call and put data of CNX Nifty index options from April 2004 to March 2014. The patterns of IVs were analysed using univariate parametric tests. Multivariate regression analyses were conducted to understand the relationships observed. Resultantly, vector autoregressions were performed to assess the determinants of IV.

The results suggested that there was asymmetric volatility across time and strike prices using alternative measures of moneyness. Furthermore, it was found that the IV of lower strike prices was significantly higher (lower) than that of higher strike prices for call (put) options. Put IV was observed to be higher than call IV irrespective of any attributes. The results further showed that current-month contracts have significantly higher IV than those for next month and those were followed by far-month contracts. Nifty futures’ volumes and momentum were found to be significant determinants of IV.

The behaviour of the volatility smile is important when accounting for the Vega risks in the portfolios of hedge fund managers. While taking a position, besides the Black-Scholes-Merton (BSM) model’s input factors, investors must consider the previous behaviour of volatility, a market’s microstructures and its liquidity for a put option contract. They must also consider the attributes of the underlying for a call option contract.

This is the first decadal study (the longest span of data for any international study on this subject) to confirm the existence of the volatility smile for the index options market in India. It examines and confirms the smile’s asymmetry patterns for different definitions of moneyness, as well as option types, the tenure of options contracts and the different phases of market conditions. It further helps to identify the determinants of IV and so has renewed importance for traders.

The purpose of this paper is to analyze the asymmetric contemporaneous relationship between implied volatility index (India VIX) and Equity Index (S & P CNX Nifty Index). In addition, the study also analyzes the seasonality of implied volatility index in the form of day-of-the-week effects and option expiration cycle.

This study employs simple OLS estimation to analyze the contemporaneous relationship among the volatility index and stock index. In order to obtain robust results, the analysis has been presented for the calendar years and sub-periods. Moreover, the international evidenced presented for other Asian markets (Japan and China).

The empirical evidences reveal a strong persistence of asymmetry among the India VIX and Nifty stock index, at the same time the magnitude of asymmetry is not identical. The results show that the changes in India VIX occur bigger for the negative return shocks than the positive returns shocks. The similar kinds of results are recorded for the Japan and China volatility index. Particularly, the analysis also supports that India VIX holds seasonality, on the market opening VIX observed to be at its high level, and on the subsequent days it remains low. The results on the options expiration unfold the facts that India VIX remains more normal on the day of expiration.

The asymmetric relation and seasonal patterns are quite useful to the volatility traders to price the financial assets when market trades in the high- and low-volatility periods.

There is a lack of studies of this kind in the context of emerging markets like India; hence, this is an attempt in this direction. The study provides an insight to the NSE to launch some derivative products (i.e. F & Os) on India VIX that can generate more liquidity in the market for the volatility traders.