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The purpose of this research is to investigate the short-term capital markets' reactions to the public announcement first local detection of novel corona virus (COVID 19) cases in 12 major Asian capital markets.

Using the constant mean return model and the market model, an event study methodology has been implied to determine the cumulative abnormal returns (CARs) of 10 pre and post-event trading days. The statistical significance of the data was assessed using both parametric and nonparametric test statistics.

First discovery of local COVID 19 cases had a substantial impact on all 12 Asian markets on the event day, as shown by statistically significant negative average abnormal return (AAR) and cumulative average abnormal return (CAAR). The single factor ANOVA result has also demonstrated that there is no variability among 12 regional markets in terms of short-term market responses. Furthermore, there is little evidence that these major Asian stock market indices differ significantly from the FTSE All-World Index which might suggest possible spillover impact and co-integration among the major Asian capital markets. The study further discovers that market capitalization and liquidity did not have any significant impact on market reaction to announcement.

The study's contribution might have been compromised by the absence of socio-demographic, technical, financial and other significant policy factors from the analysis.

These findings will be considerably helpful in tackling this unprecedented epidemic issue for personal and institutional investors, industrial and economic experts, government and policymakers in assessing the market in special circumstances, diversifying risk and developing financial and monetary policy proposals.

This paper is the first to examine the effects of local COVID 19 detection announcement on major Asian capital markets. This study will add to the literature by investigating unusual market returns generated by infectious illness outbreaks and the overall market efficiency and investors' behavioral pattern of major Asian capital markets.

This paper investigates the stock market reaction to three different events related to the UEFA Champions League – the announcements of draws, odds and match results. The aim of the paper is to test whether these events are informative for stock market operators, i.e. whether they produce abnormal returns.

Applying the event study methodology, the authors investigate the stock market reaction before (at two events: the draw date and on the release of betting odds) and after the matches of 11 listed soccer teams in the period 2003–2019. The authors also conduct OLS regression analyses in order to disentangle the impact of firm specific variables and match characteristics on cumulative abnormal returns.

This paper finds that match outcomes affect the stock market performance of listed teams, while the announcements of draws and odds do not. More specifically, the market does not consider match outcomes involving wins and ties as informative events, while it penalizes losing teams. Moreover, investor reactions to events related to the UCL competition depend more on match characteristics than on company specific variables.

The study enriches the ongoing debate about the impact of soccer team results on stock market performance in several ways: using the widest time span ever adopted in this area; focusing on UCL, which is the most important soccer competition played by private clubs; disentangling for the first time the effects of draws, odds release and sporting outcome on stock returns of listed soccer clubs.

The purpose of this paper is to research how corporate communication regarding a specific corporate event (i.e. Tesla’s tweets about a new product) as well as the framing of both the event itself and the market reactions therewith in the news media influence the formation of the share price of the respective company over time. In so doing, the study provides insights into the nature of market-moving information and the role of financial news flows in shaping market reactions in today’s high-frequency news and information environment.

Using a multi-method case study approach, combining quantitative intraday event studies with a qualitative text analysis of financial online news and tweets by Elon Musk and Twitter, the authors shed light on the complex interaction between market events, financial information and stock market reactions. The analysis covers a period of four days, encompassing the announcement and introduction of the new battery pack for Model S and X by Tesla as well as the accompanying and follow-up reporting by the financial news media.

Findings show that market reactions are driven by business events and expectations among the market rather than the follow-up reporting by financial news media. Financial online news instead seems to heavily rely on Elon Musk’s attention-triggering news to sustain its 24-h airtime with a variety of reporting tools, keeping the highly demanded audience engaged. Eventually, Twitter accounts of media visible companies and personalities, such as Tesla and its CEO Elon Musk, have been found to be useful market information sources for day traders and shareholders to trade at a profit.

The study is a response to recent discussions about the legitimacy of Twitter communication by CEOs or representatives of listed companies. The findings show that Twitter communication needs to be well considered in light of strict market regulations (e.g. SEC in the USA) regarding insider-trading and the publication of market-relevant information. In addition, corporate financial communication should avoid impetuous communication via social media channels as this could have deterrent effects on the market valuation of a listed company.

Using a sample of 9,898 firm-year observations from 1,821 unique Chinese listed firms over the period from 2004 to 2019, this study aims to investigate whether the market rewards meeting or beating analyst earnings expectations (MBE).

The authors use an event study methodology to capture market reactions to MBE.

The authors document a stock return premium for beating analyst forecasts by a wide margin. However, there is no stock return premium for firms that meet or just beat analyst forecasts, suggesting that the market is skeptical of earnings management by these firms. This market underreaction is more pronounced for firms with weak external monitoring. Further analysis shows that meeting or just beating analyst forecasts is indicative of superior future financial performance. The authors do not find firms using earnings management to meet or just beat analyst forecasts.

The authors provide evidence of market underreaction to meeting or just beating analyst forecasts, with the market's over-skepticism of earnings management being a plausible mechanism for this phenomenon.

The findings of this study are informative to researchers, market participants and regulators concerned about the impact of analysts and earnings management and interested in detecting and constraining managers' earnings management.

The authors provide new insights into how the market reacts to MBE by showing that the market appears to focus on using meeting or just beating analyst forecasts as an indicator of earnings management, while it does not detect managed MBE. Meeting or just beating analyst forecasts is commonly used as a proxy for earnings management in the literature. However, the findings suggest that it is a noisy proxy for earnings management.

The purpose of this research work is to examine the financial effect of supply chain disruptions (SCDs) caused by coronavirus disease 2019 (COVID-19) and how the magnitude of such effects depends on event time and space that may moderate the signaling environment for shareholder behaviors during the pandemic.

This study analyses a sample of 206 SCD events attributed to COVID-19 made by 145 publicly traded firms headquartered in 21 countries for a period between 2020 and 2021. Change in shareholder value is estimated by employing a multi-country event study, followed by estimating the differential effect of SCDs due to the pandemic by event time and space.

On average, SCDs due to pandemic decrease shareholder value by −2.16%, which is similar to that of pre-pandemic SCDs (88 events for 2018–2019). This negative market reaction remains unchanged regardless of whether stringency measures of the firm's country become more severe. Supply-side disruptions like shutdowns result in a more negative stock market reaction than demand-side disruptions like price hikes. To shareholder value, firm's upstream or downstream position does not matter, but supply chain complexity serves as a positive signal.

This study provides the first empirical evidence on the financial impact of SCDs induced by COVID-19. Combining with signaling theory and event system theory, this study provides a new boundary condition that explains the impact mechanism of SCDs caused by the pandemic.

Utilising a database that distinctly classifies firm-level ESG (environmental, social and governance) news sentiment as positive or negative, the authors examine the information flow between the two types of ESG news sentiment and stock returns for 20 companies listed on the Johannesburg Stock Exchange between 2015 and 2021.

The authors use Shannonian transfer entropy to examine whether information significantly flows from ESG news sentiment to stock returns and a modified event study analysis to establish how stock prices react to changes in the two types of ESG sentiment.

Using Shannonian transfer entropy, the authors find that for the majority of the companies studied, information flows from the positive ESG news sentiment to stock returns while only a minority of the companies exhibit significant information flow from negative ESG news sentiment to returns. Furthermore, the study’s findings show significantly positive (negative) abnormal returns on the event date and beyond for both upgrades and downgrades in positive ESG news sentiment.

This study is among the first in an African context to investigate the impact of ESG news sentiment on stock market returns at high frequencies.

This study aims to find the response by stock market against the announcements of quarterly earnings is empirically tested by exploiting event study methodology. Efficient market hypothesis (EMH) on Saudi stock exchange is also tried on.

The market model is applied to help gauge the expected returns and to illustrate abnormal returns around the event date.

The results established that Saudi Stock Market does not bear semi-strong form of EMH. How efficient is the Saudi market is also reflected through evidence of significant abnormal returns and post-earnings announcement drift around earning announcements dates.

The authors have not used analysts’ forecast as the expected earnings which are the limitation. As mentioned earlier, the authors used the quarterly earnings of the previous year as a proxy and that proxy could have been replaced by analysts’ forecast. Another limitation is that the trading volume in the event window is not considered.

The behavior of Saudi capital market is of much concern, and the study of this with a perspective of EMH is the significance of this paper.

All stakeholders closely watch earnings announcements and its share price movement around the announcement date. Recently, Saudi Arabia has opened its doors to foreign investors, and big foreign investors are going to enter into Saudi capital market, and after their entry, the behavior of market could be different. In the authors’ opinion, this is the right time to study the efficiency of Saudi market before the entry of foreign investors.

This study is based on the gap created by EMH of Saudi market using event methodology, observed in the existing literature, and it will be a contribution to literature.

The purpose of this study is to investigate the impact of terrorist attacks on the volatility and returns of the stock market in Tunisia.

The employed sample comprises 1250 trading day from the Tunisian stock index (Tunindex) and stock closing prices of 64 firms listed on the Tunisian stock market (TSM) from January 2011 to October 2015. The research opts for the general autoregressive conditional heteroscedasticity (GARCH) and exponential generalized conditional heteroscedasticity (EGARCH) models framework in addition to the event study method to further assess the effect of terrorism on the Tunisian equity market.

The baseline results document a substantive impact of terrorism on the returns and volatility of the TSM index. In more details, the findings of the event study method show negative significant effects on mean abnormal returns with different magnitudes over the events dates. The outcomes propose that terrorism profoundly altered the behavior of the stock market and must receive sufficient attention in order to protect the financial market in Tunisia.

Very few evidence is found on the financial effects of terrorism over transition to democracy cases. This paper determines the salient reaction of the stock market to terrorism during democratic transition. The findings of this study shall have relevant implications for stock market participants and policymakers.

The purpose of this paper is to study whether switching trading venues create value in the Hong Kong stock market.

By using an event study, the paper investigates the abnormal returns (AR) earned by firms in the Growth Enterprise Market (GEM) relating to switching to the Main Board (MB). Two measures, turnover of the stock and Amihud’s (2002) illiquidity ratio, are used to examine the liquidity effects.

The switch is accompanied by a long-term increase in stock price for low liquidity firms only. High liquidity firms underperform with persistent negative excess returns after switching, while the transient negative excess returns in low liquidity firms reverse gradually. The results further show a significant increase in trading activity for low liquidity firms following the switch, while there is a significant decline in both trading activity and liquidity in firms with high liquidity. The overall results suggest that moving from GEM to the MB is beneficial to low liquidity firms but detrimental to high liquidity firms.

This study is the first to investigate whether moving from GEM to the MB creates value in the Hong Kong stock market.

The paper aims to measure the magnitude of the event-induced return anomaly around bonus issue announcement days in Turkey for recent years. Also, by describing the information content of these announcements with the current data, the study tries to find out the factors that cause return anomaly in Borsa Istanbul when firm boards release the bonus issue decision.

The paper conducts event study methodology for detecting market anomaly around bonus issue announcements. For the pairwise comparison purpose, t-test and one-way ANOVA methods are applied to examine if abnormal returns vary according to the information content of the announcements.

Announcement returns for bonus issues from internal resources outperform the issues that are distributed from last year's net income as bonus shares. Findings indicate different return behaviour among internal resources sub-groups. Findings also suggest that investors in Turkey welcome larger-sized issues, while cumulated returns for the initial offers significantly differ from the latter issues.

Findings are limited to the Turkish equity market. Also, the Public Disclosure Platform of Turkey, which is the main data source of the study, does not provide bonus issue announcements before 2010. Therefore, the previous year's data cannot be included in the analysis.

This paper is novel in terms of considering the main resources of the bonus issue in detail to measure the announcement's impact on stock returns.