Event Days Research Articles

Cross-border ripples: investigating stock market responses to Israel-Hamas conflict in trading partner nations using event study method

PurposeThe study will add to the current discourse on the Israel-Hamas conflict by examining the impact of the war on the stock markets of trading partners. Stock market returns inevitably rise as globalization keeps integrating financial markets and economies around the world. Thus, the impact of war is assessed across a range of indicators that are similar in some way, such as geographic location, political climate or economic standing. Thus, the goal of this study is to investigate how the Israel-Hamas war affects trading partner countries' stock performance.Design/methodology/approachEvent study methodology is applied using Morgan Stanley Capital Index (MSCI) as a benchmark index. The influence of the Israel-Hamas war on the world's major stock markets is evaluated using a market model. The study takes into account Israel and its 23 trading partners. To capture the locational asymmetry in the outcome, the countries are further categorized according to their geographic locations. The official declaration of war came on October 7, 2023, a non-trading day. Consequently, October 9, 2023, is designated as the event day in this study. The data was gathered between January 1, 2023, and December 31, 2023, with an estimation period of 140 days taken into account to minimize bias.FindingsAsymmetric response is shown among the nations due to their economic standing, geographic proximity and trading links with Israel. While Austria, Greece, Egypt, Palestine and Israel had the greatest negative effects, Argentina, Japan and Chile saw significant beneficial effects. The remaining nations had little effect. The market quickly adjusted itself, eliminating anomalous returns.Research limitations/implicationsTaking into account the topic's criticality, the current work has certain limits. The study has used the daily data to limit its reach to the stock market exclusively. In the future, academics can combine high-frequency stock market data with data from other macroeconomic variables, such as currency or different commodities markets, to further their research. Furthermore, a cross-national comparison of the impact in terms of direction and intensity regarding developing global groups such as I2U2, LEVANT, BRICS, MIKTA, SCO, NATO, SAARC and OECD can provide a more comprehensive understanding in this context. To gain insight into the durability and adaptation of financial systems over time, longitudinal studies could be conducted to monitor the long-term effects of geopolitical crises on the stock markets of trading partner countries.Practical implicationsBy better managing investment portfolios and evaluating potential risks associated with trading partners involved in such conflicts, investors and businesses can lessen the impact of geopolitical tensions on stock market performance. These results contribute to our understanding of how geopolitical conflicts affect stock markets.Originality/valueThis research provides an extensive analysis of the global impact of Israel-Hamas tensions on stock market volatility by taking into account trading partners. This allows for the investigation of how various market structures and economic systems react to geopolitical turmoil. The present study is one of the first attempts to look into how disturbances in one region might affect continents to better understand the dynamics of global trade and economic interdependencies.

Mass Gathering Events at an Event Hall in Osaka Are a Non-direct Risk of Admission to a Neighboring Emergency Hospital.

The influence of planned mass gathering events on surrounding residents is not understood sufficiently. The purpose of this study was to investigate how events at an event hall affect a neighboring emergency hospital throughout the year. This was a single-center, retrospective, observational study conducted on all patients who presented to the emergency department from January 1 to December 31, 2019. The event hall is located 200 meters from the hospital, and various events such as music concerts and professional baseball games are held at the hall throughout the year. We collected patient information from the electronic medical records. The factors associated with hospitalization were assessed using a multivariable logistic regression analysis. This study comprised 18,907 patients who visited our emergency department. The number of patients on event days was 9,981 and that on no-event days was 8,922. The mean (SD) number of patients visiting on event days was 56.4 (14.9), and that on no-event days was 47.5 (14.1) (p<0.05). The multivariable logistics regression analysis showed age (adjusted odds ratio (AOR): 1.03; 95% confidence interval (CI): 1.03-1.04), male gender (AOR: 1.21; 95% CI: 1.13-1.31), transportation by emergency medical services (AOR: 2.56; 95% CI: 2.37-2.75), rain days (AOR: 1.14; 95% CI: 1.04-1.23), and event day (AOR: 1.11; 95% CI: 1.02-1.20) to be independent risk factors of hospitalization. In this study, we found that event day was one of the independent risk factors of admission to the hospital from the emergency department.

The Saltzman–Lorenz Exchange in 1961: Bridge to Chaos Theory

Abstract A single-day meeting between two theoretical meteorologists took place in 1961 at the Travelers Research Center (TRC) in Hartford, Connecticut. The two scientists were Barry Saltzman and Edward Lorenz, former proteges of V. P. Starr at Massachusetts Institute of Technology (MIT). Several years before this meeting, Lorenz discovered the following profound result: extended-range weather forecasting was not feasible in the presence of slight errors in initial conditions. The model used was the geostrophic form of a two-level baroclinic model with 12 spectral variables. These results were presented a year earlier at the first symposium on numerical weather prediction (NWP) in Tokyo, Japan, and met with some skepticism from the NWP elite, dynamical meteorologists, and pioneers in operational NWP. Lorenz held faint hope that Saltzman’s recently developed model of Rayleigh–Bénard convection would produce the profound result found earlier. One of the numerical experiments executed that eventful day with Saltzman’s seven-mode truncated spectral model produced an unexpected result: inability of the model’s seven variables to settle down and approach a steady state. This occurred when the key parameter, the Rayleigh number, assumed an especially large value, one associated with turbulent convection. And further experimentation with the case delivered the sought-after result that Lorenz had found earlier and now convincingly found with a simpler model. It built the bridge to chaos theory. The pathway to this exceptional result is explored by revisiting Saltzman’s and Lorenz’s mentorship under V. P. Starr, the authors’ interview with Lorenz in 2002 that complements information in Lorenz’s scientific autobiography, and the authors’ published perspective on Salzman’s seven-mode model.

The ACM Web Conference 2024 Report

The 33rd edition of The Web Conference was successfully held from May 13 to 17, 2024 at Resorts World Convention Centre, Singapore. It was held as in-person conference that also featured rich virtual elements. The first two days of the five-day event featured workshops, tutorials, special days, and symposia. The last three days were the main conference days dedicated to keynote speeches, parallel presentation sessions of research, industry and special tracks, as well as multiple poster and demo sessions. This brief report provides an overview with organization and program details and statistics from Conference Chairs and Program Committee Chairs. Further details can be found at https://www2024.thewebconf.org/. At the conclusion of this report, we express our deep gratitude to authors, volunteers, SIGWEB, steering committee, sponsors and supporters.

Serum Amyloid A and Haptoglobin concentrations in calves at first event of respiratory disease were not associated with subsequent risk of respiratory disease during the preweaning period

Bovine respiratory disease (BRD) causes decreased welfare and production losses and is a major reason for use of antimicrobials in dairy calves. Inflammatory markers released into the blood stream during BRD include acute phase proteins such as Serum Amyloid A (SAA) and Haptoglobin (Hp). This longitudinal observational study aimed to investigate whether the serum concentrations of SAA and Hp measured on the day of a detected mild clinical event of BRD, were associated the odds of developing recurrent BRD events requiring additional treatments in up to a 46-day follow-up period after the first event. A total of 65 preweaned dairy calves were observed for 46 days each in one Danish dairy herd. They were enrolled in this study in the age between 17 and 24 days of age and were followed for the following 46 days in total in which the calves potentially could develop an event of BRD. The calves were clinically assessed every other day using a Visual Analogue Scale (VAS), where a mild BRD event was defined as a calf that deviated from a normal and non-affected calf. The clinical signs included that the calf was less interested in its surroundings, slightly depressed, less bright, alert, and responsive with less clear eyes and using longer time to get up. The calf could have scruffy hair coat and drooping ears. Blood samples were collected on the day of the first mild BRD event that was only treated with a non-steroidal anti-inflammatory drug. A logistic regression model was performed to detect associations between having recurrent events of BRD and VAS, serum SAA and Hp concentrations at the day of the first BRD event and the follow-up period after the BRD event. Only the follow-up period after the first BRD event had a significant association with the odds ratio of having recurrent events of BRD of 2.3 for a 10-day difference in follow-up time after the BRD event.

The market reaction of energy companies to the announcement of the Russian–Ukrainian invasion

PurposeThis study aims to empirically analyze the market response of energy companies to the Russian-Ukrainian invasion. Additionally, it examines the comparison of market reactions between companies in NATO member countries and non-member countries.Design/methodology/approachThis study utilizes a sample of 1,511 energy sector companies. To achieve the research objectives, two methods are employed. First, an event study is used to analyze the market reaction using Cumulative Abnormal Return (CAR) to the announcement of Russia's invasion of Ukraine on February 24, 2022 (event day) within an event window of (−30, +30). Second, a cross-sectional analysis is conducted to compare the responses of companies in NATO member countries with those in non-member countries.FindingsThe findings of this study reveal that energy companies worldwide reacted positively both before and after the announcement of the invasion, with significant reactions observed in companies from the Americas, Europe, and Asia &amp; Pacific regions. However, the Middle East and Africa markets did not show significant reactions. Furthermore, the study indicates that most developed and emerging markets responded positively, likely due to the increase in energy commodity prices during the war. Moreover, the market reaction of companies in NATO member countries was stronger compared to other markets.Originality/valueThis study contributes to the existing literature by being the first to examine the impact of the Russian invasion of Ukraine on the energy sector, while categorizing markets as developed, emerging, and frontier. It also specifically explores the market reaction of energy companies in NATO member countries, providing unique insights into the differential responses within the energy sector.

ESG News Sentiment and Stock Price Reactions: A Comprehensive Investigation via BERT

In this paper, we examine in a systematic manner how investors react to the sentiment of instant ESG news. Instead of acquiring proprietary ESG news or events datasets directly from specific ESG data providers, we extract fresh ESG news directly from a plethora of raw news articles. We showcase how the latest development in NLP (i.e. the BERT model) can be applied to build a comprehensive and fresh ESG news dataset, and how company ESG news sentiment can be efficiently recognized by a machine. Overall, we find that the market reacts to ESG news based on news sentiment. On the event day, positive ESG news has an average abnormal return of 0.31% while negative ESG news leads to a mean value of -0.75\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$-0.75$$\\end{document}%. More interestingly, we find that the impact of ESG news may depend on the company’s historical ESG record. The negative impact of negative ESG news has less severe consequences for companies with an overall better ESG record, while the positive impact of positive ESG news may be more pronounced for companies with a worse ESG record.

Do bromine and surface-active substances influence the coastal atmospheric particle growth?

New particle formation (NPF) is considered a major source of aerosol particles and cloud condensation nuclei (CCN); however, our understanding of NPF and the subsequent particle growth mechanisms in coastal areas remains limited. This study provides evidence of frequent NPF events followed by particle growth in the middle Adriatic Sea during the summer months at the coastal station of Rogoznica in Croatia. To our knowledge, this is the first study to report such events in this region. Our research aims to improve the understanding of NPF by investigating particle growth through detailed physicochemical characterization and event classification. We used a combination of online measurements and offline particle collection, followed by a thorough chemical analysis. Our results suggest the role of bromine in the particle growth process and provide evidence for its involvement in combination with organic compounds. In addition, we demonstrated the significant influence of surface-active substances (SAS) on particle growth. NPF and particle growth events have been observed in air masses originating from the Adriatic Sea, which can serve as an important source of volatile organic compounds (VOC). Our study shows an intricate interplay between bromine, organic carbon (OC), and SAS in atmospheric particle growth, contributing to a better understanding of coastal NPF processes. In this context, we also introduced a new approach using the semi-empirical 1st derivative method to determine the growth rate for each time point that is not sensitive to the nonlinear behavior of the particle growth over time. We observed that during NPF and particle growth event days, the OC concentration measured in the ultrafine mode particle fraction was higher compared to non-event days. Moreover, in contrast to non-event days, bromine compounds were detected in the ultrafine mode atmospheric particle fraction on nearly all NPF and particle growth event days. Regarding sulfuric acid, the measured sulfate concentration in the ultrafine mode atmospheric particle fraction on both NPF event and non-event days showed no significant differences. This suggests that sulfuric acid may not be the primary factor influencing the appearance of NPF and the particle growth process in the coastal region of Rogoznica.

Seemingly manipulated anomaly: Evidence from corporate site visits

We find that the stock prices of some firms are suspected to be manipulated by the market in the CSV disclosure event scenario. An anomaly in the daily cumulative abnormal returns (CARs) of these “suspicious” CSVs is documented. Around the suspicious CSVs, the CAR trending upward (downward) one month before the event day, temporarily declining (increasing) on the event day, and then trending upward (downward) one year after the event day. We refer to this seemingly manipulated anomaly as the CSV manipulative effect. Based on a unique data set of CSVs to listed firms in China, we obtain the following main findings. First, the CSV manipulative effect is not caused by other company announcements disclosed around the CSV event date, and the probability of manipulative effect brought by CSVs is significantly greater than that brought by other company announcements. Second, factors related to market manipulation significantly affect the CSV manipulative effect. Third, we construct a machine learning model to detect the CSV manipulative effect and find that it is capable of detecting this effect. Fourth, the portfolio constructed by the CSV manipulative effect performs better than the portfolio constructed by the momentum or reversal effect.

The Impact of Alcohol-Related Presentations to Emergency Departments on Days with a Public Holiday or Sporting Event: A Retrospective Cohort Study.

The consumption of alcohol within the Australian community continues to rise, impacting care delivery in already over-burdened emergency departments (EDs). This study aimed to examine the impact of alcohol-related presentations (ARPs) to EDs on days with a public holiday or sporting event. A retrospective cohort study was undertaken using routinely collected health data pertaining to patient presentations diagnosed with an alcohol-related disorder (ICD-10-AM code F10) to two EDs in Queensland, Australia from January 1, 2016 - December 31, 2020. Descriptive and inferential statistics were used to describe and compare ARPs on event days versus non-event days and uncomplicated versus other ARPs on event days only. Of all 5,792 ARPs, nine percent (n = 529) occurred on public holidays or sporting event days. When compared by day type, type of presentation, mode of arrival, and day of week differed between event and non-event days. On event days, uncomplicated ARPs differed to other ARPs, with uncomplicated ARPs being younger, having shorter median length-of-stay (LOS), and less likely to be admitted to hospital. In this multi-site study, public holidays and sporting events had a noteworthy impact on ARPs to EDs. Focused refinement on the clinical management of uncomplicated ARPs is warranted to inform future resource allocation, including on event days.

Dust events characterization from visibility, trends and Dust Adversity Index in the Canary Islands for the period 1980–2022

Dust events in the Canary Islands have been documented since the late 19th century. However, during the past few years, several severe dust episodes have occurred in the Canary Islands, resulting in significant impacts on various sectors, such as aviation, air quality, and health, among others. These recent severe events have drawn the attention of both scientists and the general population, raising questions about whether these episodes are now more frequent and more severe. This study analyzes 483 dust events recorded in the Canary Islands over the last 40 years.Data analysis reveals that the average number of dust event days per year is approximately 24 days, and these events have an average duration of 1.8 days, both of which show a statistically significant decreasing trend over the series. Seasonal examination indicates that events occurring in the first and fourth quarters of the year have twice the duration of those in the other quarters. Furthermore, on an annual basis, events in the first quarter exhibit negative trends in both average and minimum visibilities. This suggests that dust events in the Canary Islands are becoming shorter in duration but more intense in terms of visibility.In this article, the Dust Adversity Index (DAI) is introduced to objectively compare the severity of events. Finally, anomalies in geopotential have been utilized to determine the prevailing synoptic patterns during dust events. It is evident that the dominant synoptic pattern during the first and fourth quarters of the year consists of a low cut-off system located to the west of the Canary Islands and a high-pressure system to the north of the Iberian Peninsula.

Adolescents Who Do Not Endorse Risk via the Patient Health Questionnaire Before Self-Harm or Suicide

Given that the Patient Health Questionnaire (PHQ) item 9 is commonly used to screen for risk of self-harm and suicide, it is important that clinicians recognize circumstances when at-risk adolescents may go undetected. To understand characteristics of adolescents with a history of depression who do not endorse the PHQ item 9 before a near-term intentional self-harm event or suicide. This was a retrospective cohort study design using electronic health record and claims data from January 2009 through September 2017. Settings included primary care and mental health specialty clinics across 7 integrated US health care systems. Included in the study were adolescents aged 13 to 17 years with history of depression who completed the PHQ item 9 within 30 or 90 days before self-harm or suicide. Study data were analyzed September 2022 to April 2023. Demographic, diagnostic, treatment, and health care utilization characteristics. Responded "not at all" (score = 0) to PHQ item 9 regarding thoughts of death or self-harm within 30 or 90 days before self-harm or suicide. The study included 691 adolescents (mean [SD] age, 15.3 [1.3] years; 541 female [78.3%]) in the 30-day cohort and 1024 adolescents (mean [SD] age, 15.3 [1.3] years; 791 female [77.2%]) in the 90-day cohort. A total of 197 of 691 adolescents (29%) and 330 of 1024 adolescents (32%), respectively, scored 0 before self-harm or suicide on the PHQ item 9 in the 30- and 90-day cohorts. Adolescents seen in primary care (odds ratio [OR], 1.5; 95% CI, 1.0-2.1; P = .03) and older adolescents (OR, 1.2; 95% CI, 1.0-1.3; P = .02) had increased odds of scoring 0 within 90 days of a self-harm event or suicide, and adolescents with a history of inpatient hospitalization and a mental health diagnosis had twice the odds (OR, 2.0; 95% CI, 1.3-3.0; P = .001) of scoring 0 within 30 days. Conversely, adolescents with diagnoses of eating disorders were significantly less likely to score 0 on item 9 (OR, 0.4; 95% CI, 0.2-0.8; P = .007) within 90 days. Study results suggest that older age, history of an inpatient mental health encounter, or being screened in primary care were associated with at-risk adolescents being less likely to endorse having thoughts of death and self-harm on the PHQ item 9 before a self-harm event or suicide death. As use of the PHQ becomes more widespread in practice, additional research is needed for understanding reasons why many at-risk adolescents do not endorse thoughts of death and self-harm.

The Astroworld tragedy as an argument for proactive crisis management

PurposeThe Astroworld concert tragedy is used as an example of crisis (mis)management and the potential utility of the 4R model. Although the 4R model has been implemented in high-risk emergency management situations, it is useful in the PR field because of its actionable approach, creating a way for practitioners to prepare for and manage crisis situations.Design/methodology/approachThis is an analysis of the crisis that occurred at Astroworld, spanning preparation, day-of events, casualties and enduring reputational impact. The paper applies the 4R method to the Astroworld tragedy to show how it could have lessened or even prevented the tragedy. Finally, the SCCT model is used to explain why the official post-crisis statements were ineffective.FindingsSocial media has heightened the importance of a quick and effective organizational response to risk and crisis situations because poor responses can go viral quickly. However, social media also provides intelligence and crowd sourced information that can inform PR practitioners of emerging crisis scenarios. It is also an underutilized tool for two-way communication during crises.Practical implicationsThe 4R approach is beneficial to general practitioners as it simplifies crisis best-practices, something essential for quick action. As our world changes and becomes less predictable, practitioners must have a clear plan to protect their organizations and the public surrounding them. This approach includes reduction, readiness, response and recovery, which are all essential in crisis communication.Originality/valueThe 4R method has not been explored or applied in the PR field. This paper highlights how the model has been utilized in the emergency management field and illustrates the way 4R can serve the PR field.

Stock market response to natural disasters: Does corporate sustainability performance make difference?

This study aims to examine the short-term price reactions of the stocks listed on Borsa Istanbul (BIST) after the severe earthquake of February 6, 2023, that happened in the southeastern region of Türkiye covering 11 provinces and causing more than 50,000 fatalities. Using a sample of 450 companies listed on the BIST All Index, this study estimates the abnormal returns (ARs) of stocks by employing an event study methodology. Using BIST 100 companies as a sub-sample, this study also explores whether sustainability performance creates resilience against downside risk after the earthquake. The results of the market model and the mean-adjusted model show that on the event day, most of the sectors had negative and significant ARs, while only the non-metal mineral products had positive and significant ARs. Most of the sectors continued to decline in the following 10 days except basic metal and non-metal mineral products sectors. The telecommunications sector was the most negatively affected sector in both models after the event day as it has underperformed in ensuring uninterrupted access to communication. The findings also indicate that firms in the financial sector that have higher sustainability performance are more resilient in responding to the disaster.

Wastewater surveillance to assess cocaine and methylenedioxymethamphetamine use trends during a major music festival in Brazil.

Wastewater-based epidemiology was applied in northeastern Brazil during a dance festival, revealing that cocaine consumption doubled during the event days. The daily drug loads were 0.95 ±0.03 to 11.4±0.4g/day for BE, 1.8±0.4 to 7.6±0.3g/day for COC, 0.04 ±0.02 to 0.19 ±0.02 g/day for COE, and 0.08 ±0.02 to 0.80 ±0.02 g/day for MDMA.

New particle formation event detection with convolutional neural networks

New aerosol particle formation (NPF) events play a significant role in altering aerosol concentrations and dispersion within the atmosphere, making them vital for both climate and air quality research. The primary objective of investigating NPF events is to precisely determine their occurrence dates. In this study, we introduced the ConvNeXt model for the first time to identify NPF events, and compared its performance with two other deep learning models, EfficientNet and Swin Transformer. Our main aim was to automate an objective identification and classification of NPF events accurately. All three models employed transfer learning to effectively capture critical features associated with NPF. Our results demonstrated that the ConvNeXt model significantly outperformed the other models, achieving an impressive accuracy rate of 95.3% on event days, surpassing EfficientNet (92.8%) and Swin Transformer (94.9%). Furthermore, we performed tests using different ConvNeXt variants (ConvNeXt-T/S/B/L/XL) and different pre-training weights, revealing that different configurations of ConvNeXt models exhibited improved NPF event recognition capabilities. Finally, we conducted generalizability experiments using the ConvNeXt-XL model, achieving the highest accuracy of 96.4% on event days. This study not only underscores the recognition prowess of ConvNeXt models but also highlights their practical utility in accurately detecting NPF events in real-world scenarios. This contribution aids in advancing our comprehension of aerosol dynamics in atmospheric environments, providing valuable insights for climate and air quality research.

Why Small Actions Matter: Observations of Microleveraging and Event Service Operations During the Japan 2019 Rugby World Cup

The aim of this article is to examine how smaller operational actions and decisions contribute to the effective leveraging of the sport event resource. It is an empirical article, with a strong applied focus, using a mixed data collection methodology. Observational and interview data were collected on event day service delivery in a mix of stadiums, fan zones, and town environments, during the 2019 Rugby World Cup in Japan. The contribution of this article to events-related research is that it shows that while leveraging must be planned for at the strategic and tactical level, it is vital that the leveraging paradigm is used at the micro-operational level of event delivery. The findings illustrate how multiple smaller leveraging actions, by multiple stakeholders, help to achieve outputs and can build a foundation for achieving legacy outcomes, such as how positive visitor emotional experiences can become future leveraging fulcrum points.

Short term forecasting of persistent air quality deterioration events in the metropolis of Sao Paulo

Air pollution is one of the main environmental problems in metropolitan areas. Negative impacts to human health are intensified when poor air quality conditions persist for many consecutive days, with gradual accumulation of pollutants in the atmosphere. Persistent air quality deterioration events are typically associated with occurrence of stagnant atmospheric conditions and reach the regional scale. In this study, data-driven models were developed to forecast the occurrence of persistent air pollution events of inhalable particulate matter (PM10) and ozone (O3) in the metropolis of Sao Paulo, Brazil. On average, 8 events per year were observed between 2005 and 2022, comprising 73 event days per year. The logistic regression method was used in a supervised learning framework. Daily timeseries of surface weather variables were used as predictors. In the case of PM10, a consistent long-term decrease in the number events impacted the model performance. The PM10 model benefited from the restriction of the training set to recent years, with a significant increase in the model accuracy despite the reduction in the volume of data. The final models correctly reproduced the seasonal distribution of events, with overall accuracies of 0.92 and 0.87 for O3 and PM10, respectively, in 2022. Despite the fact that persistent exceedance events are relatively rare, the models were able to detect 81% and 97% of the event days in 2022, respectively for O3 and PM10. Daily maximum temperature was an important predictor, increasing the event odds by 483% (O3) and 84% (PM10). The classification models developed in this study can successfully forecast the occurrence of regional air pollution events concerning both primary and secondary air pollutants, which have different drivers for accumulation in the atmosphere. The models require simple input data and low computational resources, aiming to stimulate future usage by the general public and decision-makers, in order to mitigate exposure to harmful air pollutant concentrations.

Regional and periodic asymmetries in the effect of Russia-Ukraine war on global stock markets

This study aims to investigate regional and periodic asymmetries in the impact of the outbreak of the Russia-Ukraine war on global equity markets. Employing the event study methodology, the current study examines global stock market reactions within a 61-day window centred around the event day, i.e., February 24, 2022. MSCI equity indices of 47 sample countries have been utilized to ensure uniformity in the index development methodology. They provide broader coverage of global equity markets by including large and mid-cap companies, representing approximately 85% of the free float-adjusted market capitalization for each sampled country. The study extends the event window to 61 days to assess the enduring effects of the war over a relatively longer period. The research delineates regional and periodic asymmetries and posits that the impact of the war on a market is contingent upon its geographical proximity and trade relations with Russia and Ukraine. Additionally, the impact is stronger during a shorter window surrounding the event date but diminishes over the extended period.

Indian Stock Markets’ Reaction to the Nationwide Lockdown due to COVID-19: Evidence from Event Study Analysis

Indian Stock Markets’ Reaction to the Nationwide Lockdown due to COVID-19: Evidence from Event Study Analysis