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The purpose of this paper is to examine changes in stock returns, liquidity, institutional ownership, analyst following and investor awareness for companies added to and deleted from the Dow Jones Industrial Average (DJIA) index. Previous studies report conflicting evidence regarding the market reactions to changes in the DJIA index membership.

This study uses the event-study methodology to calculate abnormal returns and trading volume around the announcement and effective days of DJIA index changes from 1929 to 2015. It also tests for significant changes in liquidity, institutional ownership, analyst following and investor awareness in the 1990–2015 period. Multivariate regressions are used to perform a simultaneous analysis of competing hypotheses.

This study resolves the mixed results of previous DJIA index papers by documenting different stock price and trading volume reactions over the 1929–2015 period. Focusing on the most recent period, 1990–2015, the study finds that stocks added to (deleted from) the index experience a significant permanent stock price gain (loss). The observed stock price reaction seems to be associated with changes in liquidity proxies thus lending support for the liquidity hypothesis.

Limited data availability for the periods prior to 1990 prevents this study from identifying the exact reasons for different stock price and trading volume reactions across subperiods of the 1929–2015 period.

This study provides the most comprehensive examination of market reactions to changes in the DJIA index and resolves the mixed results of previous studies. A better understanding of market reactions around the DJIA index changes can help both individual and institutional investors with developing effective trading strategies and index managing companies with designing optimal announcement policies.

This paper aims to explore the interaction between investor attention and green security markets, including green bonds and stocks.

This study takes the Baidu index of “green finance” as the proxy for investor attention and constructs several generalized prediction error variance decomposition models to investigate the interdependence. It further analyzes the dynamic interaction between investor attention and the return and volatility of green security markets using the rolling time window.

The empirical analysis and robustness test results reveal that the spillovers between investor attention and the return and volatility of the green bond market are relatively stable. In contrast, the spillover level between investor attention and the green stock market displays significant time-varying and asymmetric effects. Moreover, the volatility spillover between investor attention and green securities is vulnerable to major financial events, while the return spillover is extremely sensitive to market performance.

The conclusion further expands the practical application and theoretical framework of behavioral finance in green finance and provides a new reference for investors and regulators. Besides, this study also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management in green securities.

This paper aims to investigate Chinese bull and bear markets. The Chinese stock market has experienced a long period of bear cycle from early 2000 until 2006, and then it fluctuated greatly until 2010. However, the cyclical behaviour of stock markets during this period is less well established. This paper aims to answer the question why the Chinese stock market experienced a long duration of bear market and what factors would have impacted this cyclical behaviour.

By comparing the intervals of bull and bear markets between stocks and indices based on a Markov switching model, this paper examines whether different industries or A- and B-share markets could lead to different stock market cyclical behaviour and whether firm size can determine the relationship between the firm stock cycles on the market cycles.

This paper finds a high degree of overlapping of bear cycles between stocks and indices and a high level of overlapping between the bear market and a fraction of stock with increasing stock prices. This leads to the conclusion that the stock performance and trading behaviour are widely diversified. Furthermore, the paper finds that the same industry may have different overlapping intervals of bull or bear cycles in the Shanghai and Shenzhen stock markets. Firms with different sizes could have different overlapping intervals with bull or bear cycles.

This paper fills the literature gap by establishing the cyclical behaviour of stock markets.

This paper explored the new features of emerging stock markets, in order to point out the most associated indicators of increasing stock return volatility, which may lead to instability of emerging markets. The study covers a sample of five geographical areas of emerging economies, including Mexico, Korea, South Africa, Turkey, and Malaysia. It used the backward multiple‐regression technique to examine the relationship between monthly changes of stock price indices as dependent variable and the associated predicting local as well as international variables, which represent possible causes of increasing price volatility and initiating crises in emerging stock markets. The study covered monthly data for a period of forty‐eight months from January 1997 to December 2000. The study revealed that stock trading volume and currency exchange rate respectively represent the highest positive correlation to the emerging stock price changes; thus represent the most predicting variables of increasing price volatility. International stock price index, deposit interest rate, and bond trading volume were moderate predicting variables for emerging stock price volatility. While changes in inflation rate showed the least positive correlation to stock price volatility, thus represents the least predicting variable.

We investigate the causal relationships between volatility implied in Major Market Index (MMI) options and its component stocks' options from January, 1987 to October, 1989. We find that MMI implied volatility Granger causes component stock implied volatility for all twenty component stocks, which is consistent with the hypothesis that changes in volatility in index options markets leads volatility in underlying component (cash) markets. When we further analyze the sample by subperiod, we find that the causal relationships are insignificant in the period after the October 1987 crash, which is consistent with the hypothesis that exchange and regulatory actions taken after the crash weakened the influence of index options markets on cash markets. Trading strategies and programs involving stock index options and futures have been blamed for increasing volatility of the stock market. Indeed, trading in index futures and options markets has been blamed for much of the drop in stock prices in the crash of October 1987. After the crash, regulators took several actions to reduce the influence of futures and options market volatility on cash market volatility. If regulators' fears were legitimate and their efforts were successful, the volatility linkage between index options markets and their underlying cash markets should have been weakened. This paper provides two important contributions to our understanding of the volatility implications of index options markets. First, we examine the causality relationships between index and component stock implied volatility to assess whether or not changes in volatility in the index option market lead changes in volatility in the underlying component stock markets. Second, we test whether the causal relationships differ before and after the October 1987 crash to assess whether or not regulatory actions after the crash caused a change in these relationships. We measure volatility using implied standard deviations (ISDs) from options on the Major Market Index (MMI) and its component stocks. We form time series of ISDs for both the MMI and its component stocks, and then apply Granger causality tests to the series. For the full sample period of January 1987 to October 1989, we find that changes in index ISDs do Granger cause changes in component stock ISDs for all twenty component stocks, evidence consistent with the notion that volatility in index option market leads volatility in the component (cash) market. When we analyze the sample by subperiod, however, we find that the significant Granger causality holds only in the period before the October 1987 crash. Post‐crash subperiods show insignificant causality relationships, which suggests that efforts taken by exchange officials and regulators to reduce the influence of volatility in the index options and futures markets on cash market volatility were successful. The remainder of the paper is structured as follows. In Section I we discuss the potential for causal relationships between index option markets and their component markets and review related literature. Section II contains a discussion of our methodology and a description of our data. Section III contains a discussion of our results and Section IV concludes.

A composite sentiment index (CSI) from quantitative proxy sentiment indicators is likely to be a lag sentiment measure as it reflects only the information absorbed in the market. Information theories and behavioral finance research suggest that market prices may not adjust to all the available information at a point in time. This study hypothesizes that the sentiment from the unincorporated information may provide possible market leads. Thus, this paper aims to discuss a method to identify the un-incorporated qualitative Sentiment from information unadjusted in the market price to test whether sentiment polarity from the information can impact stock returns. Factoring market sentiment extracted from unincorporated information (residual sentiment or sentiment backlog) in CSI is an essential step for developing an integrated sentiment index to explain deviation in asset prices from their intrinsic value. Identifying the unincorporated Sentiment also helps in text analytics to distinguish between current and future market sentiment.

Initially, this study collects the news from various textual sources and runs the NVivo tool to compute the corpus data’s sentiment polarity. Subsequently, using the predictability horizon technique, this paper mines the unincorporated component of the news’s sentiment polarity. This study regresses three months’ sentiment polarity (the current period and its lags for two months) on the NIFTY50 index of the National Stock Exchange of India. If the three-month lags are significant, it indicates that news sentiment from the three months is unabsorbed and is likely to impact the future NIFTY50 index. The sentiment is also conditionally tested for firm size, volatility and specific industry sector-dependence. This paper discusses the implications of the results.

Based on information theories and empirical findings, the paper demonstrates that it is possible to identify unincorporated information and extract the sentiment polarity to predict future market direction. The sentiment polarity variables are significant for the current period and two-month lags. The magnitude of the sentiment polarity coefficient has decreased from the current period to lag one and lag two. This study finds that the unabsorbed component or backlog of news consisted of mainly negative market news or unconfirmed news of the previous period, as illustrated in Tables 1 and 2 and Figure 2. The findings on unadjusted news effects vary with firm size, volatility and sectoral indices as depicted in Figures 3, 4, 5 and 6.

The related literature on sentiment index describes top-down/ bottom-up models using quantitative proxy sentiment indicators and natural language processing (NLP)/machine learning approaches to compute the sentiment from qualitative information to explain variance in market returns. NLP approaches use current period sentiment to understand market trends ignoring the unadjusted sentiment carried from the previous period. The underlying assumption here is that the market adjusts to all available information instantly, which is proved false in various empirical studies backed by information theories. The paper discusses a novel approach to identify and extract sentiment from unincorporated information, which is a critical sentiment measure for developing a holistic sentiment index, both in text analytics and in top-down quantitative models. Practitioners may use the methodology in the algorithmic trading models and conduct stock market research.

The purpose of this paper is to quantify the extent to which the Malaysia-based equity investors can benefit from diversifying their portfolio into the conventional and Islamic Southeast Asian region and the world’s top ten largest equity indices (China, Japan, Hong Kong, India, the UK, the USA, Canada, France, Germany and Switzerland).

The multivariate GARCH-dynamic conditional correlation is deployed to estimate the time-varying linkages of the selected conventional and Islamic Asian and international stock index returns with the Malaysian stock index returns, covering approximately eight years daily starting from 29 June 2007 to 30 June 2016.

In general, in terms of volatility, the results indicate that both Asian and international Islamic stock indices are more or less volatile than its conventional counterparts. From the correlation analysis, we can see that both the conventional and Islamic MSCI indices of Japan provide more diversification benefits compared to Southeast Asian region, China, Hong Kong and India. Meanwhile, in terms of international portfolio diversification, the results tend to suggest that both the conventional and Islamic MSCI indices of the USA provide more diversification benefits compared to the UK, Canada, France, Germany and Switzerland.

The findings of this paper may have several significant implications for the Malaysia-based equity investors and fund managers who seek for the understanding of return correlations between the Malaysian stock index and the world’s largest stock market indices in order to gain higher risk-adjusted returns through portfolio diversification. With regard to policy implications, the findings on market shocks and the extent of the interdependence of the Malaysian market with cross-border markets may provide some useful insights in formulating effective macroeconomic stabilization policies in the efforts of preventing contagion effect from deteriorating the domestic economy.

This study explores the price and trading volume effects around the quarterly Dow Jones Islamic Market-GCC index (DJIM-GCC) revisions and investigates whether these reactions are driven by firms' fundamentals or by investors' perception of ethical screening.

The authors adopt an event study methodology to analyze the price and volume effects of Islamic indices redefinitions.

The results exhibit a positive (negative) price reaction for added (deleted) stocks. The authors also document an asymmetric volume response for index additions and deletions. The multivariate analysis of the cumulative abnormal returns reveals that the documented market reaction around Islamic index revisions is mainly related to the compliance attribution (withdrawal).

The approach allows to separate the market reaction arising from changes in firms' fundamentals from that induced by investors' perception of the attribution or withdrawal of a compliance certification. Moreover, the focus on the GCC region, where countries share the same cultural traits and perceive Islamic law identically excludes any social effect that would influence the market reaction due to cultural differences between countries.

The aim of this study is to compare volatility persistence with daily volatility and to analyze the asymmetry effect of volatilities in stock markets of emerging economies. Using daily observations of stock market indices of selected major emerging countries during the period of January 1, 2002 to December 31, 2018, the authors estimate the persistence, the half-life measure of volatility and the daily volatility of the return series using the GARCH model application. The authors also examine the leverage effect on stock market returns using the EGARCH model estimation. In addition, the authors investigate the impact of the 2008 global financial crisis on various volatility measures and the leverage effect of emerging stock market returns. The authors then examine and compare the different speeds of mean reversion, volatility persistence and leverage effects in the national stock market indices during the pre-crisis, crisis, and post-crisis periods. The authors hereby present evidence that the effects of negative shocks are significantly larger than those of positive shocks in emerging stock markets throughout their different sample periods.

The purpose of this chapter is to analyze the possible portfolio diversification opportunities between Asian Islamic market and other regions’ Islamic markets; namely USA, Europe, and BRIC. This study makes the initial attempt to fill in the gaps of previous studies by focusing on the proxies of global Islamic markets to identify the correlations among those selected markets by employing the recent econometric methodologies such as multivariate generalized autoregressive conditional heteroscedastic–dynamic conditional correlations (MGARCH–DCC), maximum overlap discrete wavelet transform (MODWT), and the continuous wavelet transform (CWT). By utilizing the MGARCH-DCC, this chapter tries to identify the strength of the time-varying correlation among the markets. However, to see the time-scale-dependent nature of these mentioned correlations, the authors utilized CWT. For robustness, the authors have applied MODWT methodology as well. The findings tend to indicate that the Asian investors have better portfolio diversification opportunities with the US markets, followed by the European markets. BRIC markets do not offer any portfolio diversification benefits, which may be explained partly by the fact that the Asian markets cover partially the same countries of BRIC markets, namely India and China. Considering the time horizon dimension, the results narrow down the portfolio diversification opportunities only to the short-term investment horizons. The very short-run investors (up to eight days only) can benefit through portfolio diversification, especially in the US and European markets. The above-mentioned results have policy implications for the Asian Islamic investors (e.g., Portfolio Management and Strategic Investment Management).