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The purpose of this study is to compare market reactions to the change in the demand by index funds between large and small company stocks by examining the transition of the S&P 500, S&P 400 MidCap and S&P 600 SmallCap indexes from market capitalization to free-float weighting. This unique information-free event allows not only avoiding confounding information signaling and investor awareness effects but also comparing the effect of the decrease in demand on stocks of different sizes.

This study uses the event study methodology to calculate abnormal returns and trading volume around the full-float adjustment day. It also tests for significant changes in institutional ownership and liquidity. Multivariate regressions are used to examine the relation of liquidity changes and price elasticity of demand to the cumulative abnormal returns around the full-float adjustment day.

This study finds significant decreases in stock price accompanied with significant increases in trading volume on the full-float adjustment day, and significant gains in quasi-indexer institutional ownership and liquidity. The main finding is that cumulative abnormal returns around the event period are related to changes in the number of quasi-indexer and transient institutional shareholders, not to changes in liquidity or price elasticity of demand.

This study provides the first comprehensive comparison analysis of stock market reactions to the decline in demand between large and small company stocks. As an important implication for future studies of the index effect, changes in institutional ownership should be considered in the analysis.

This study aims to explore the impact of controversial firms’ corporate sustainability assessments on their risk exposure according to the environmental, social and governance (ESG) paradigm.

This study conducts a cross-sectional study using the ordinary least squares approach to test how corporate social responsibility practices affect firms’ risk exposure, testing the three single impacts of ESG components and the impact of an overall ESG assessment. This study considers the largest Standard & Poor’s (S&P) 500 stock market index companies and focus on a double-risk measurement – systematic and idiosyncratic – developing an empirical study on 132 controversial companies listed on the S&P index.

Empirical findings indicate that the overall ESG assessment and the environmental and social sub-dimensions decrease idiosyncratic firm risk. At the same time, no significant results are found according to the systematic risk component.

This study fits into the domain of risk management research, investigating whether additional and non-financial disclosures regarding sustainability issues decrease information asymmetries, improving investors’ decision-making and stakeholders’ relations. Prior literature has shown limited evidence on the relationship between corporate social performance (CSP) and firm risk based on controversial companies. The main contribution is to consider the controversy as an independent factor from the industry sector, given that the implications of CSP actions and practices are mainly firm-specific.

Assessing the research performance of researchers offers inducement toward excellence in research. This study aims to analyze the research productivity of the most prolific authors of Pakistan considering their trends toward publications, citations and collaboration.

Top 100 authors from the top 10 Pakistani universities from Web of Science over the 10 years with the rigorous data cleaning process were selected. Scientometric analysis techniques were carried out to evaluate the research profile of these authors.

The findings revealed that majority of the productive authors were male working in the position of Professor in the physical sciences area. The publications and citations gradually increase with time. They preferred to collaborate for their publications, while first authorship publications were found less in number. Moreover, the propensity to collaborate at the international level increases double-fold from the first five years to the next five years period. In addition, the position of the authors was explored among different performance metrics. The finding exhibits variation in the ranking of authors among them. The impact of numbers of authors, funding status, publication of articles, presence of collaboration and international collaboration on the dependent variable and citation count was insignificant. However, the publication of review papers has a significant impact on the citation counts.

Findings have significant implications for policymakers to make maximum opportunities for researchers to strengthen linkages for collaboration and increase the funding prospects.

Studies on this topic are scarce, and therefore, this study provides useful recommendations to researchers and institutes to improve research productivity.

Stock market performance is paramount to every country, as it signifies economic growth, business performance, wealth maximization, savings deployment and consumer confidence. This study investigates the disparities in the market performance of listed firms in Romania. This study also examines whether the COVID-19 crisis affected market performance.

The data were collected from 69 firms listed on the Bucharest Stock Exchange (BSE) from 2018 to 2022, belonging to 11 sectors. This study used several methods to achieve its objectives. Difference tests were considered to analyze the performance of Romanian companies before and during the COVID-19 crisis, as well as across sectors. Regression analysis was also conducted to estimate the effect of the COVID-19 crisis and classification type on Romanian companies' performance. Additional analyses were performed to verify the findings of the present study.

The study’s findings indicate a clear difference in market performance between the pre-crisis and crisis periods. The COVID-19 pandemic had an adverse and significant impact on market performance. However, after the market contraction in the early stage of the COVID-19 pandemic outbreak, the stock market outperformed the pre-pandemic capitalization levels and the regional and global indices evolution. Furthermore, there was a difference in market performance across sectors. In particular, the communication services sector has specifically demonstrated accelerated growth.

This research examines the variation in the market performance of companies before and during the COVID-19 pandemic and across different sectors. It also provides evidence of the potential impact of COVID-19 on firms' market performance. This research contributes to a better understanding of how sectors perform during times of crisis.

The study intends to determine the environment, social and governance (ESG)'s impact on the firm's value. In addition, how ownership concentration (OC) and transparency and disclosures (TD) influence the impact of firm's ESG on its valuation (firm value).

The relevant panel data with a sample of 78 Indian firms for five years (2016–2020) are gathered. Both linear and nonlinear connections of firm's ESG with its value are tested. In addition, TD and two components of OC (stakes of promoters and institutional investors) are empirically tested as moderators on the connectivity of the firm's ESG with its value.

The linear association of firm's ESG with its value is found insignificant. ESG is found to have a positive and nonlinear (U-shaped) impact on the value of the firms. TD does not moderate the connectivity of firm's ESG with its valuation (firm value). The higher stakes of promoters positively affect the association of firm's ESG with the valuation. However, the high stakes of institutional investors retard the ESG's influence on the firm value.

The study is on Indian firms for five years. A sample of more than one nation and a longer duration (10 years) could have helped better determine the associations among the variables. In turn, these limitations can be the present study's future scope. In addition, the authors find a lack of standardisation of the ESG scales, which is a problem in measuring it. Using standardisation scales of ESG for the analysis can also be future scope on the topic.

The investors would be wary of the level of ESG to influence the firms' value positively. Managers also need to be careful to have sincere efforts for ESG to reap its rich dividends. Policymakers may take cognisance that despite having board seats (in a few cases), institutional investors negatively (instead of positively as expected) influences the ESG's association with the firm's value. They may bring some guidelines or legislative changes to fix responsibility on the part of the institutional investors.

No study reports the linear and nonlinear association of ESG on the firm's value to observe clearer connectivity between the two. Similarly, no study is observed to have promoters and institutional investors as moderators on the association of firm's ESG with the valuation (firm value). Hence, the present study considerably augments the extant literature on the topic and its contribution.

Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

This case was researched using publicly available sources, including Mercury Systems financial filings and press releases, news stories about the seasoned equity offering, financial information from Bloomberg and industry information from IBISWorld Industry Reports and articles related to seasoned/secondary equity offerings, intangible asset valuation and the use of revolving lines of credit. Quotes are taken from Mercury financial reports and press releases and express the (optimistic) opinions of company executives.

Mercury Systems, a technology company in the aerospace and defense industry, announced a six million share seasoned stock offering in June 2019. This resulted in a 6% stock price decrease. A stock price decrease is a typical event when a firm announces the issuance of new common shares, but with Mercury Systems, there were concerns about how much money the firm needed to fund its strategy of growth through acquisitions. If internally generated funds were not sufficient, should the firm issue debt or have another seasoned equity issue? Students will look at the objectives and success of the most recent seasoned equity issue, determine future funds needs and how the firm should finance these needs.

This case is appropriate for undergraduate and graduate students in corporate finance electives. Typically, topics such as seasoned equity offerings are not covered in introductory courses, so this is recommended for finance electives. Even in advanced finance courses, sometimes there is insufficient time to cover seasoned equity offerings.

The purpose of this study is to identify the drivers and future scenarios of Iran’s Social Security Organization.

The research is applied in terms of orientation and mixed in terms of methodology. In this research, the methods of theme analysis, root definitions, fuzzy Delphi and Cocoso were used. The theoretical population is the managers and senior experts of the social security organization, and the sampling method was done in a judgmental way. The tools of data collection were interviews and questionnaires. The interview tool was used to extract the main and subdrivers of the research and develop the scenarios.

Through theme analysis, 35 subdrivers were extracted in the form of economic, sociocultural, financial and investment, policy, marketing, environmental and legal themes. Due to the large number of subdrivers, these factors were screened with fuzzy Delphi. Eleven drivers had defuzzied coefficient higher than 0.7 and were selected for final prioritization. The final drivers were prioritized with the CoCoSo technique, and the two drivers of social security holdings governance and state of government revenues had the highest priority. Based on these two drivers, four scenarios of prosperity, resilient social security, unstable development and collapse have been developed.

Some of the suggestions of the research are: using the capacity of FinTechs and financial startups to invest the government revenues of the organization, using digital technologies such as business intelligence for more efficient decisions and developing corporate governance in the organization.

This paper aims to investigate the impact of climate change news on the dynamics of US stock indices.

The empirical basis of the study was 3,209 news articles. Sentiment analysis was performed by a pre-trained bidirectional FinBERT neural network. Thematic modeling is based on the neural network, BERTopic.

The results show that news sentiment can influence the dynamics of stock indices. In addition, five main news topics (finance and politics natural disasters and consequences industrial sector and Innovations activism and culture coronavirus pandemic) were identified, which showed a significant impact on the financial market.

First, we extend the theoretical concepts. This study applies signaling theory and overreaction theory to the US stock market in the context of climate change. Second, in addition to the news sentiment, the impact of major news topics on US stock market returns is examined. Third, we examine the impact of sentimental and thematic news variables on US stock market indicators of economic sectors. Previous works reveal the impact of climate change news on specific sectors of the economy. This paper includes stock indices of the economic sectors most related to the topic of climate change. Fourth, the research methodology consists of modern algorithms. An advanced textual analysis method for sentiment classification is applied: a pre-trained bidirectional FinBERT neural network. Modern thematic modeling is carried out using a model based on the neural network, BERTopic. The most extensive topics are “finance and politics of climate change” and “natural disasters and consequences.”

The authors compare sentiment level with sentiment shock from different angles to determine which measure better captures the relationship between sentiment and stock returns.

This paper examines the relationship between investor sentiment and contemporaneous stock returns. It also proposes a model of systems science to explain the empirical findings.

The authors find that sentiment shock has a higher explanatory power on stock returns than sentiment itself, and sentiment shock beta exhibits a much higher statistical significance than sentiment beta. Compared with sentiment level, sentiment shock has a more robust linkage to the market factors and the sentiment shock is more responsive to stock returns.

This is the first study to compare sentiment level and sentiment shock. It concludes that sentiment shock is a better indicator of the relationship between investor sentiment and contemporary stock returns.