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This paper aims to assess, from an empirical perspective, the research question if public media reports which relate concrete banks to concrete allegations of money laundering have an adverse impact on banks stock prices and what are the drivers of such impact?

The paper makes use of event study methodology and uses the constant mean and the market model. The event window is calibrated towards a five-day window, and the estimation window has a length of 90 days, in line with best academic practices. Drivers are identified by correlation analysis. and the market model uses ordinary least squares regression.

The application of event study methodologies yields the results that stock prices of affected banks generate, at the date of the news appearance, statistically significant negative abnormal returns under both the market model and the constant mean model. As negative abnormal returns have been mainly found at the date of the event itself, the findings confirm that the impacts of money laundering may be severe but short natured. In addition, the paper finds that the identified negative abnormal returns may be driven by the banks’ size in terms of total assets, by the bank’s profitability in terms of return on assets and by the bank’s sustainability risk.

The findings have implications in terms of banking and supervisory practices. In specific, the findings help to argue that banking consolidation is needed to lower the impacts of AML cases, as stock prices of larger banks show less sensitivity. In addition, the findings could be used to determine financial sanctions against banks violating AML regulation. Finally, the findings imply that AML news can have severe and fast-moving financial stability considerations and are, therefore, important in crisis situations.

As there appears to be no substantial research that applies event study methodology to the money laundering context, the combination of research question and methodology has an innovative character. In addition, there is no clear literature on media and money laundering.

This paper examines the reaction of the Egyptian stock market to two substantial devaluations of the Egyptian pound (EGP) in 2022 and tests the informational efficiency of the Egyptian market.

The paper uses the event study framework to analyze the significance and direction of abnormal returns of the leading index of the Egyptian stock market (EGX30) on and around the devaluation days. It employs both the constant mean model and the market model to estimate the normal returns of the EGX30. Additionally, the paper uses data on two equity indices, one global and one for emerging markets, as benchmarks for normal returns.

The paper finds that the Egyptian stock market experienced significant positive abnormal returns on the devaluation days of the EGP in March and October of 2022, indicating a positive market reaction to the devaluation. Furthermore, evidence suggests that the Egyptian market may not be informationally efficient as significant positive abnormal returns were observed two weeks before and two weeks after the devaluation day, suggesting news leaks and delayed reactions, respectively.

This study is the first to examine the impact of the recent two devaluations of the EGP in 2022 on the Egyptian stock market. It complements existing literature by analyzing the immediate market reaction to two consecutive devaluations in an African country. Furthermore, the paper evaluates the efficiency of the Egyptian market in processing information related to exchange rates.

This paper aims to investigate the impact of banning cryptocurrencies on stock markets.

The paper uses an event study approach and data from stock market indices in nine countries that imposed a ban. It uses the constant mean model and the market model, with two different benchmarks for global returns, to analyze if any of the stock indices show abnormal returns on or around the announcement of a cryptocurrency ban.

The analysis shows that banning cryptocurrencies did not affect the returns of stock markets in any of the countries studied, indicating that the cryptocurrency market and stock markets are decoupled from each other, or the ban was not effectively implemented.

To the best of the author’s knowledge, this paper is the first to explore the potential spillover effect of a cryptocurrency ban on stock markets. It also bridges two strands of literature: the relationship between cryptocurrencies and traditional assets, and the impact of cryptocurrency regulation on their returns.

This paper aims to investigate the spillover effects of jump and crash events among Chinese nonfinancial firms.

This sample consists of more than 1.5 million weekly observations of over 3,000 Chinese listed firms over the period 1991–2015. The authors utilize univariate tests to compare the post-event performance of matched peer and non-peer control firms and cross-sectional regressions of their abnormal returns/cumulative abnormal returns (ARs/CARs) and returns on assets (ROAs).

The authors find that extreme risk-adjusted abnormal stock returns (stock price crashes and jumps) generate statistically significant ARs/CARs in the same directions in industry, size, leverage, and geographical location matched peer firms in Chinese stock market. Further tests reveal that peer firms' response to the crash event is pronounced more in the group of firms about which the information asymmetry is high between investors and firms.

Portfolio investors can adjust their portfolios accordingly by selling stocks of the matching rival firms during a crash period. Policymakers may develop policies so as to protect the interests of small investors in the events of crashes in the markets. They can reduce the information asymmetry between the firms and the investors by making information about the firms more transparent, so as to reduce the contagion in case of crash event.

This study has important implications for portfolio investment managers and policymakers.

To the best of authors' knowledge, this is the first study that combines the jump and crash events and attempts to assess their spillover effects on other firms in Chinese stock market.

The global financial crisis (GFC) of 2007–2008 had far-reaching consequences for the global economy, triggering widespread economic turmoil. We use the event-study method to investigate whether investors priced the effect of significant events before the Lehman Brothers' bankruptcy in European and Asia-Pacific banks. Abnormal returns on the event days range from −4.32% to 5.03% in Europe and −5.13% to 6.57% in Asia-Pacific countries. When Lehman Brothers went bankrupt on September 15, 2008, abnormal returns averaged the lowest at −4.32% in Europe and −5.13% in Asia-Pacific countries. The significant abnormal returns show that Lehman Brothers' collapse was a turning point, and investors paid attention to the precrisis events as warning signs of the oncoming crisis.

This study aims to examine investor attention by exploring the trading behavior of investors in US-based exchange traded funds (ETFs) of countries active in the Federation Internationale de Football Association (FIFA) World Cups.

The present study employs event study methodology to measure abnormal returns and excess trading volume of country-specific ETFs during six FIFA World Cups. The sample of ETFs includes 19 participating countries.

Consistent with investor behavior that might be explained by attention effect, the study finds that country-specific ETFs from participating countries do indeed behave differently during FIFA World Cups events. The authors find significant evidence of abnormal trading volume and, albeit weaker, abnormal returns during cups.

This study contributes to the literature on investor behavior, linking investor attention with salient sports events.

This study examines the firm-level financial consequences caused by supply chain disruptions during COVID-19 and explores how firms' supply chain diversification strategies, including diversified suppliers, customers and products, moderate the negative effect on firm performance.

Based on data drawn from 222 publicly traded firms in China, the authors use event study methodology to estimate the effects of supply chain disruptions on the financial performance of affected firms. Regression analyses are conducted to examine the moderating effects of supply chain diversification.

Firms affected by supply chain disruptions during COVID-19 experienced a significant decline in shareholder value in two weeks and a subsequent decrease in operating performance in one year. Diversified suppliers, customers and products act as shock absorbers to alleviate the negative effects. Further regression shows a substitution effect between customer and product diversification. Cross-industry comparisons reveal that service firms experienced more loss than manufacturing firms. Customer diversification mitigates the adverse effects of supply chain disruptions for both manufacturing and service firms. Supplier diversification exerts a noteworthy role in manufacturing firms, while product diversification is beneficial for service firms.

The study provides empirical evidence on the magnitude of financial consequences of supply chain disruptions during COVID-19 in both the short term and long term and enriches the current understanding of how to build resilience from the supply chain diversification perspective.

The purpose of this paper is to examine if the announcement of corporate power purchase agreements (PPAs) induce significant effects on the electricity buyers' stock returns.

This is an event study based on the Fama French Five Factor Model which uses several significance tests and robust regression approaches.

The announced closing of corporate PPAs induces significant positive abnormal stock returns. This announcement effect is even more pronounced in case of virtual PPAs.

To the best of the author‘s knowledge, this study is the first which explictly investigates the announcement effects of corporate PPAs, which are closed between the owner of the renewable energy asset and the institutional end consumer. In addition, this study extends the event study approach by robust regression methods.

This paper examines the relationship between the extent and quality of the four dimensions of corporate social responsibility disclosure (CSRD) namely community, environment, workplace and marketplace with the long-run share price performance of Malaysian initial public offering (IPO) companies.

This study utilised secondary data by the content analysis of the annual reports and Datastream of 115 IPOs listed from 2007 to 2015 in Malaysia. The IPO’s performance was determined by calculating the return measures under the equally weighted and value-weighted schemes of the mean abnormal returns and buy-and-hold abnormal returns covering the three years post-listing using the event-time approach.

The findings demonstrate that Malaysian IPOs experience substantial overperformance and underperformance when both the IPO performance measures are benchmarked against the matched companies and market. The results indicated that the extent and quality of the community and environment CSRD dimensions are positively and significantly correlated to the IPO’s performance. On the other hand, the extent and quality of the workplace and marketplace CSRD dimensions are negatively and significantly correlated to the IPO performance.

Malaysian regulators could benefit from these findings in their endeavour to carry out a reform process on CSRD to improve its quality. The results of this study are important to investors, regulators, non-government organisations, communities and policymakers. They also enhance the understanding of companies about the importance of disclosing greater CSR information to improve their performance and profitability.

To the researchers' best knowledge, this study provides new insights into the association between CSRD and the performance of Malaysian IPO companies, which is considered important.

This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior.

Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors.

The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory.

The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds.