Significant Negative Reaction Research Articles

Changes in the Perception of Error Announcements from the German Two-Tier Enforcement

AbstractWhen the German financial reporting enforcement was introduced in 2004, the legislator chose an innovative approach: He combined a private enforcement institution with a governmental agency while sanctioning was carried out solely by publicly announcing identified accounting errors. Subsequently, investors were confronted with up to then unprecedented ‘error announcements’ from the enforcement system. For a sample of 213 announcements from 2006 to 2019, the paper analyzes the adaptation process of investors to this new information. While significant negative market reactions around the announcement dates can be found for the whole observation period, the results also show that the investors’ views of the error announcements change over time. Especially in the early years, the observed market reactions are strongly linked to the impact of the accounting error on the firm’s financial situation. This link weakens over time and factors related to the nature of the error become more important to investors. In particular, errors that are attributable to the unjustifiable application of professional judgment lead to significantly more negative effects.

Prevalence of diabetes distress and its correlates among adults with type 2 diabetes mellitus in a primary health center of Bihar - A cross-sectional study.

Diabetes is a chronic disease associated with many complications. Approximately 20% of people living with diabetes suffer from some form of depression. "Diabetes distress" (DD) is used to describe the significant negative psychological reactions related to emotional burdens and worries specific to an individual's experience to manage severe, complicated chronic disease such as diabetes. To determine the proportion having DD and to identify the sociodemographic and morbidity related factors associated with the presence of DD among adults with Type2DM who are being treated at PHC Naubatpur, Bihar. This facility based cross-sectional analytical study was done over 3 months among 260 Type2DM patients attending PHC Naubatpur. Sociodemographic details and morbidity related details were collected followed by PAID questionnaire to assess DD. Around 60% of the participants were of age ≤60 years. Majority (63.8%) of the participants were having diabetes from past 1-10years. One-fourth (24.6%) of them were having score of ≥40, therefore having DD. Alcohol consumption and presence of diabetes complications in the participants were found to be independent predictors of DD. This study showed a high (24.6%) prevalence of DD. It is essential to identify high-risk patients with different mental health needs. Healthcare providers should focus on reducing DD and devise ways to increase self-care practices and coping skills.

Reaksi Pasar Modal terhadap Kenaikan Suku Bunga Acuan oleh The Fed tanggal 16 Juni 2022

The research aims to examine whether the Indonesian capital market reacts to the increase in benchmark interest rates by The Fed on June 16, 2022. The event study method is used with an observation period of 107 days, where 100 days are the estimation period and 7 days are the event period. The research sample consists of companies listed in the LQ45 Index from February 2022 to July 2022. The sampling method used is purposive sampling. Market reactions are measured by Cumulative Abnormal Return (CAR) using the mean adjusted model. Data analysis is conducted using the one-sample t-test. The results indicate that there is no significant negative reaction in the Indonesian capital market regarding the increase in benchmark interest rates by The Fed.

Development and psychometric evaluation of nurse’s intention to care for patients with infectious disease scale: an exploratory sequential mixed method study

AimsNurses who care for patients with infectious disease may experince significant stress and negative psychological reactions. The intention of nurses to care is a complex and multifaceted concept that is influenced by a range of factors. Therefore, this study was conducted to explain the concept of nurses’ intention to care for patients with infectious disease and then develop a reliable and valid scale to measure this concept accurately in Iranian nurses.DesignThis study is a cross-sectional study with a sequential-exploratory mixed-method approach from May 2022 to July 2023. The concept of nurses’ intent to care for patients with infectious disease was explain using deductive content analysis, and item pools were generated. In the sconed step the samples were 455 nurses. Data was collected by an online form questionnaire using a convenience sampling technique. In this step to determine the psychometric properties of nurse’s intention to care for patients with infectious disease scale (NICPS), face and content validity performed. Then construct validity was determined and confirmed using exploratory and confirmatory factor analysis followed by convergent and divergent validity respectively. Finally, scale reliability including stability and internal consistency were evaluated.ResultsThe finding showed that NICPS with seventeen items were classified into three factors namely “Social support” with seven items, “Spiritual motivation” with six items and “Job satisfaction” with four items. These three factors explained 56.14% of the total variance. The fit indices showed that the model has a fit and acceptable (TLI, CFI, IFI > 0.9; PNFI, PCFI > 0.5, REMSEA > 0.049, CMIN/DF = 2.477). Reliability revealed acceptable internal consistency and stability (> 0.7).ConclusionThe finding showed that NICPS has three factors in Iranian nurses. Nursing managers can use these results to provide training and support intervention for nurses in order to increase their intention to care for this patient. Also, the NICPS is a reliable and valid for evaluating this concept in future studies.

The Impact of The Russia-Ukraine War on The Dynamics of The Asean-5 Stock Market

The capital market can be defined as activities related to public offerings, securities trading, public companies, institutions, and certain professions. One of the factors considered in stock investment is the Efficient Market Hypothesis. The Efficient Market Hypothesis is a financial theory that discusses how asset prices in the market already reflect all available information. This study employs an approach to detect market reaction and market efficiency based on the event of the world oil price decline due to the Russian invasion of Ukraine on March 10, 2022, through excess or abnormal return, price impact, and fluctuation patterns observed using a multifractal model. The research results on the abnormal return of the ASEAN-5 stock index showed a significant negative reaction at t-5 and t-3 during the event of the world oil price decline due to the Ukraine and Russia war in 2022 and a significant positive reaction at t-0 during the event. The average abnormal return before and after the announcement of the world oil price decline due to the Ukraine and Russia war in 2022 showed a significant negative reaction, but there was no significant difference in price impact between before and after the event. The efficiency level of the stock index in ASEAN-5 did not show a significant difference after the announcement of the world oil price decline due to the Ukraine and Russia war in 2022.

THE BANKING SYSTEM OF UKRAINE IN WARTIME

This article aims to assess changes in the banking system of Ukraine in 2022 under martial law (at the macro level) and the vulnerability of banks to financial stress (at the micro level). The proposed method uses cluster analysis of the main ratios for banking stability based on the agglomerative hierarchical clustering algorithm.The analysis of changes at the macro level under martial law shows that anti-stress measures ensured that a significant negative stress reaction was avoided. The analysis of the vulnerability of banks to financial stress shows that a significant number of banks had problems with funding and turned to the Central Bank, but by the end of the year, the funding market had stabilized. The worst situation concerned non-performing loans, but most of those are covered by reserves. Changes in legislation in Ukraine under martial law provided almost 100% coverage of household deposits in banking institutions.

Value added tax and household consumption in Sub-Saharan Africa: Evidence from Nigeria and South Africa

This study focuses on Nigeria and South Africa and examines how value added tax (VAT) affects household consumption in sub-Saharan Africa. We use time series data from 1994 to 2021 as well as panel Autoregressive Distribution Lag (ARDL) regression through pooled mean group estimation. The findings show that in the long -run and with a 0.05 degree of materiality, VAT has a significant positive influence on household consumption and the exchange rate significantly depletes household consumption. In the short term, at 10% importance, VAT has a significant impact on household spending. According to the Error Correction Model (ECM), there will be a short-run return to equilibrium of 93.7%. According to the country specific results for Nigeria, VAT at 10% has a significant positive impact on CPI but at lag 3, CPI has a significant negative reaction to VAT and the Exchange rate (EXG). EXG has a significant positive influence on CPI at lags 1 and 2. For South Africa, CPI affects itself positively and significantly at lags 1 and 2 but VAT appears to be harmfully unimportant whereas EXG affects CPI positively and significantly at lags 1 and 3 but becomes minor at lag 2. The study concludes that VAT implications are detrimental to households in the short run despite having a positive impact in the long term. As a result, the study recommends adequate public awareness prior to VAT implementations as well as zero VAT for basic household goods and services in African regions that have yet to implement such policies.

Regime-based debt sustainability analysis: Evidence from euro area economies

This paper empirically studies non-linearities in debt sustainability analysis by resorting to the modern estimation technique of panel smooth transition regression (PSTR). We assess euro area debt sustainability by analysing the reaction of the primary balance to changes in public debt, relative to GDP respectively, in annual frequency from 2000–2019 in a panel framework. The PSTR allows to estimate the existence of a threshold in the behaviour of the reaction function, refrains from the country-wise perspective and applies a regime-switching model to detect non-linearities. Data is segregated into different regimes endogenously via a logistic regression. Our results show that there are two different regimes in the euro area: a high and a low debt regime. The estimated reaction coefficient for the low debt regime is statistically insignificant, whereas it is positive and statistically significant for the high debt regime. Further, for a sub-sample of highly indebted economies we find a statistically significant negative (positive) reaction coefficient for the low (high) debt regime.

Improving Operational Efficiency through Quality 4.0 Tool: Blockchain Implementation and Subsequent Market Reaction

Purpose: This article aims to observe and measure how modern and innovative blockchain technology improves the data quality and transparency and thus affect the stock prices of publicly traded companies after announcing its implementation in their operations. Additionally, the objective is to compare the results with control group of non-adopters. Methodology/Approach: We selected 30 public companies across various sectors, obtained daily stock price data, identified peer companies, and employed an event study approach to examine the statistical impact of blockchain adoption announcements. Findings: A significant negative reaction (-0.4%) was observed in stock prices the day following a blockchain adoption announcement, but overall, the market response was unsystematic, indicating no consistent reaction in stock prices post-announcement. Research Limitation/Implication: The event study approach assumes that markets are always efficient. This methodology has some limitations because we live in a world that is not perfect, and stock prices do not necessarily fully reflect all available information. Originality/Value of paper: Blockchain implementation is a current and intriguing subject that has attracted limited scholarly research. Each new study contributes valuable insights to the understanding of how this innovative technology impacts corporate operations. Furthermore, this research endeavours to draw comparisons between companies that have announced their adoption of blockchain and their non-adopters counterparts.

Cybersecurity Breach at a Big 4 Accounting Firm: Effects on Auditor Reputation

ABSTRACT Public company investors rely on the Big 4 audit firms to provide assurance over internal controls and financial reporting. What, then, would happen if one of these very assurance providers suffered its own cybersecurity breach? We examine such an event in the major data breach of Deloitte in 2017. Using U.S. data from 2014 to 2019, we find Deloitte suffered significant reputational damage postbreach. Specifically, audit clients and existing shareholders became less likely to approve of Deloitte as the company’s auditor. Deloitte also charged lower audit fees after the incident. Furthermore, Deloitte’s audit clients suffered significant negative market reactions postbreach. Our results suggest pervasive implications of cyberattacks on auditor reputation and support recent congressional efforts to expand regulation in this area.

Investor overreaction to political news: the case of Turkey

Purpose – Information underlies the stock price movements. There are lots of economic and political news that have an impact on the stock price. Unlike other studies (extensively considering economic news), this paper aims to detect abnormal returns resulting from important political news from 2010 to 2022 in Turkey. Methodology – To determine the abnormal returns-overreactions, this paper utilized the market-based event study approach and the results were corroborated by non-parametric test statistics. Findings – Crucial important news occurring between 2010-2022, led to statistically significant negative abnormal reactions the day before the event days. These results show that the banking sector dissociates negatively from reference market reaction. Conclusion – It is deduced that some investors got information about political events before the events day, and so they priced the information. This result implies that Semi- Strong Efficient Market Hypothesis is not valid. Keywords: Political events, event study, efficient market hypothesis, non-parametric test JEL Codes: G14,G21

BUSINESS DYNAMICS DURING THE COVID-19 PANDEMIC AT LIQUIDITY LEVEL BASIC CHAMICAL INDUSTRY AND CONSUMER GOODS COMPANIES IN INDONESIA

<p>Researchers want to prove the ratio of debt as well as turnover from inventory, receivables, working capital and also company size to liquidity and its impact during the covid-19 pandemic. The research sample uses basic Chemical industry and consumer goods listed on the IDX for the fourth quarter of 2019 to the first quarter of 2020. This research is quantitative research and secondary data consisting of quarterly financial reports on the IDX. Sampling was carried out using purposive sampling method and produced 135 samples of companies. The method used is the panel data regression analysis method. The results of the analysis show that only the debt ratio has a significant negative reaction on liquidity. Company size, accounts receivable turnover, inventory turnover and working capital turnover are not significant because the increase or decrease in the variable does not affect the level of liquidity. During this covid-19 pandemic, there is no change in the relationship between each independent variable to liquidity.</p>

The Value of the Capital Market Development-Bursa Research Scheme's (CBRS) Recommendation Changes in

This study analyses the changes in analyst recommendations in the Malaysian stock market from 2010 to 2018. Using samples of 668 upgrade recommendations and 495 downgrade recommendations, this study employs event study methodology to examine price performance by predicting abnormal returns using the market model. The findings indicate that significant positive stock price reactions occur following upgrade recommendations and significant negative stock price reactions occur following downgrade recommendations over a short-term and up to six-month period. Further analysis reveals no statistically significant difference in performance between analysts who are participants of the Capital Market Development Fund – Bursa Research Scheme (CBRS) and those who are not. This finding implies that, despite the significant market reaction to both upgrade and downgrade recommendations, CBRS’s financial analysts do not provide better analysis than those of non-CBRS analysts.

The effect of controlling person's illegalities on stock price returns: Evidence from Elman neural network model.

Controlling persons are the ultimate decision-makers of listed companies. Their illegalities have impacts on investors’ wealth, firm development, and capital market’s quality. Against this backdrop, we provide a quantitative analysis of the short-term stock price reaction to the criminal detention announcements of controlling persons throughout 2007–2019. We applied the Elman neural network (ENN) model into the classical event study methodology and demonstrated that the combination of them helps to improve the estimation accuracy of the stock price reaction. The results show that the stock price has a significant negative reaction to the criminal detention announcements of listed companies’ controlling persons on the announcement day, and the average reaction level is -6.67%. Additionally, the crisis communication measures of the firms could diminish the negative impact of such mandatory disclosure information on their stock price, but the effect is limited. Finally, the 31 companies in our sample cause a total loss of RMB 21.1 billion in market capitalization on the announcement day alone. The above results indicate that the impact of listed companies’ controlling persons on the capital market is tremendous, although the number of this group is small. Our work enriches the listed companies’ illegalities research and provides a reference for investors’ investment choices and follow-up decision making of regulatory authorities. It also provides some guidance for most of the researchers to further explore the application of data mining techniques in nonlinear problems.

Revisiting the Impact of Goals on Affect and Effort*

AbstractPerformance goals are one of the most prevalent management controls used in practice to address motivational concerns. Goals influence employees' affective state by enabling them to evaluate their performance against a standard and determine if their performance is satisfactory. The objective of this paper is to understand and extend the current management accounting literature on goals and their effect on employee effort via affect. I address this objective in three ways. First, I conduct a systematic review of the management accounting literature to determine what we know about goals and determine if the literature acknowledges the important effects that goals have on affect. From the literature review, I note the paucity of research that examines the affective consequences of using performance goals. Second, I discuss some of the prominent theories from psychology that explain the relationship between goals and affect and provide suggestions for research questions. Third, I develop an experimental manipulation using online participants to demonstrate that goal attainment and goal failure lead to significant positive and negative affective reactions, respectively. By sharing my research method, I provide a starting point that accounting researchers can employ to examine how affect can influence effort, which has an important causal linkage with performance outcomes.

How Individual Investors React to Negative Events in the FinTech Era? Evidence from China’s Peer-to-Peer Lending Market

Inexperienced individual investors are the main players in the emerging FinTech industry, and also suffer from frequent negative events in the markets. With 3,110 negative events and 467,594 transaction data of China’s peer-to-peer lending market from 2015 to 2018, this paper analyzes how different types of platform negative events affect the decision-making of individual investors. We find that individual investors only have a significant negative reaction to moral hazard exposure events such as platforms absconding, with relatively ignorance of other types of negative events. The negative effect is rapid but short-lived, and shows differences among platforms of different background and attributes. By the mediation analysis, we find that public attention can be a mediator and explain the pattern of the impact that absconding events have on individual investors. Related risk prevention, regulation, investor education issues are discussed and further suggestions are also put forward for both individual investors and regulators.

An analysis of the impact of President Trump’s tweets on the DJIA and S&P 500 using machine learning and sentiment analysis

We analyze the immediate impact of President Trump’s tweets on two US stock market indices using a 30-minute event window for each tweet and intra-day market data. The tweets and intra-day market data, are used to study market reactions using sentiment analysis, and machine learning (ML) classification and regression. The results show a significant negative reaction when President Trump tweeted during open market hours. We also found that tweets with a strong positive or strong negative sentiment had positive market reactions. ML regressors use the tweets and market data to predict the post-tweet market index averages and post-tweet market trends.

The Information Content in Bonus Issue Announcements : Evidence from the Indian Corporate Sector

The bonus issue has remained the center of attraction among researchers within the finance literature due to its puzzling nature. This study tried to revalidate two hypotheses namely, information signalling hypothesis and liquidity hypothesis in the Indian stock market in context of bonus issue announcements. Price reaction and trading volume on and around the announcement as well as ex-date were investigated during the study period (2004 – 2016). The study also measured the market depth through augmented liquidity tests around these two dates. The findings of the study observed significant positive abnormal reaction on the day of announcement as well as ex-bonus date. The presence of significant positive abnormal reaction in the pre-announcement period indicated the existence of insider trading and/or information leakages. The significant negative price reaction observed during the post ex-bonus day indicated the presence of bonus stripping practices in the study period. The study observed abnormally high trading volume around the announcement date and the ex-bonus date. The augmented liquidity tests, that is, stock’s trading volume, stock’s relative trading volume, and liquidity ratio revealed that stocks traded on NSE experienced enhanced liquidity in the post bonus issue period. The empirical findings of the research were in line with the information signalling hypothesis and liquidity hypothesis.

Index Informativeness: An Empirical Study on Indonesia Stock Exchange

This study aims to determine the market's reaction to the announcement of company list change’s at LQ45 Index, Jakarta Islamic Index (JII), and SRI-KEHATI Index. Sample of this research is company stocks that include in or exclude from LQ45 Index, JII, and SRI-KEHATI Index during the period 2009 to 2018. The results showed that in general in the sample group of companies included in the Index, no significant market reaction was found. For the sample group of companies excluded from the Index, significant negative market reactions were found from all the Index. Furthermore, there was no significant difference in market reaction was found, both in the sample group included and in the sample group excluded from the Index. Significant different market reaction were only found in the LQ45 Index and JII.

Did Comprehensive Assessment (CA) 2014 and Stress Test Exercise (STE) 2016 resolve information asymmetry?

The study investigates the informational value of the Comprehensive Assessment (CA) 2014 and the Stress Test Exercise (STE) 2016 by leveraging the literature on market reactions around scheduled announcements and by analyzing the trading patterns and volume-return co-movements around the announcements. We corroborate the theoretical implications from the literature and find a significant drop in trading for the whole sample before the CA 2014 results announcement illuminating the existence of information asymmetry. The significant rise in trading and volume-return correlations after the CA report indicates the resolution of the information asymmetry. The released information signaled the costs of the new regulatory regime by revealing the critical risk factors for the regulator. We find no characteristic trading patterns around the STE 2016 results announcement due to the specificity of the publication period, however observing only the price reactions, we uncover significant negative market reactions for the banks falling under the Single Supervisor Mechanism (SSM) umbrella suggesting the investors' awareness of the regulatory costs arising from the SSM. The study adds to the academic literature focused mainly on earning announcements by providing evidence for market reactions after regulatory announcements and delivers valuable implications for policymakers.