A Closer Look at Correction for False Discovery Bias When Making Multiple Comparisons

Facts and Fictions About Handling Multiple Comparisons.

This paper conducts a comparative analysis on the variability of firm-level abnormal returns in Egypt and the United States (US) amidst three different recent global hazardous events (political, economic, and health). Moreover, it determines the impact of firm-level characteristics in reducing firms’ abnormal returns and identifies the most vulnerable industries during crises in both countries. The paper methodology is conducted in two stages on the selected sample for US and Egypt stock markets, DJIA and EGX30 indices, respectively. The first stage is an event study approach to determine the amplitude and direction of the response of the US and Egypt abnormal returns to each of the studied crises. The second stage encompasses cross-sectional regressions to study the impact of firm-level characteristics and vulnerable industries on the highest significant abnormal stock returns for each event in each country. This study has theoretical and practical contributions. To our knowledge, this is the first study to demonstrate the higher abnormal stock returns of the developing stock market, Egypt, compared to the developed stock market, US, in both health and economic crises under all different time intervals except the examined political crisis. Moreover, emerging and developed countries’ businesses should provide attentive management of this study’s significant firm-level characteristics to strengthen firms’ exogenous shock absorbency. Furthermore, this study’s identification of the most vulnerable industries in each market paves the way for developing supportive policies for these industries resulting in healthier and safer financial markets amidst crises. Keywords: Abnormal Returns, Stock Markets, Crises, Egypt, United States

Research Objective - This research was conducted to test whether the government's announcement about Covid-19 was responded to by the capital market with the differences in abnormal returns and stock trading volume before and after the announcement. Methods - The research sample was 660 public companies, listed on the Indonesia Stock Exchange in 2020. The Wilcoxon sign rank test was used to test the research hypothesis, because the data was not normally distributed. Findings – Abnormal stock returns have been proven to have significant differences before and after the Covid-19 announcement. Even stock trading volume activity was shown the same result. The results show significant differences before and after the Covid-19 announcement. The test results for each sector show different abnormal returns before and after the announcement of Covid-19 in the various industries, consumer goods, and basic & chemical industries, while for trading volume activity there are differences only in the consumer goods sector. Theoretical and Policy Implications – The results can be used for decision making for policy makers to resolve the impact of the pandemic, especially on the sectors most affected by the pandemic. The research can also help potential investors in making investment decisions in the future. Research Novelty – This research was conducted on all companies listed on the Indonesian Stock Exchange in 2020 to see the impact of Covid-19 on the entire industrial sector due to the pandemic.

Objective: to examine the effect of signaling the characteristics of business combinations through material facts on the abnormal returns of companies listed on the Brazilian stock exchange. Methods: the study’s final sample comprises 675 observations from 2010 to 2021, collected from the Refinitiv database and the Securities and Exchange Commission website. To analyze the impact on abnormal returns, calculated using the market model and the asset pricing model, the event study methodology was applied with an 11-day event window. Results: the characteristics of business combinations are significant for the Brazilian stock market, resulting in positive abnormal returns. However, no distinctions were observed regarding the type of combination, payment method, or whether a subsidiary conducted the transaction. Notably, when goodwill is signaled, abnormal returns are positive and higher than those without disclosure. Conclusions: The characteristics of business combinations are relevant to the Brazilian stock market, with the information signaled to investors being more impactful than the type of information disclosed. This research highlights the importance of signaling business combination characteristics for managers and informs external users when speculating on such transactions.

PurposeThe purpose of this paper is to examine stocks that are most actively discussed by online posters and see if the messages posted about these stocks have information or if they are just noise.Design/methodology/approachThis study uses messages posted on TheLion.com, which reports a real time list of the ten most actively discussed stocks. The stocks in this list at the daily market close during 2005‐2006 are examined. An event study is performed to estimate the daily abnormal returns on these stocks. Contemporaneous and lead–lag regressions of abnormal returns against message posting activities are performed.FindingsOnline posters prefer thinly traded micro‐cap stocks. On average, there is an abnormal return of 19.4 per cent on a stock the day it is one of the ten most talked about stocks. The number of messages posted about a stock on a given day is not only positively related with the stock's abnormal return on that day but it also positively predicts the next day's abnormal return.Research limitations/implicationsIt may be interesting to examine if the investor sentiment expressed in online messages has predictive power for micro‐cap stocks.Practical implicationsThe results provide evidence to regulators that online talk affects stock prices. They show investors that there are inefficiencies in the stock market. They also suggest that corporate managers, especially of small firms, should monitor the stock message boards.Originality/valueThis study focuses on the micro‐cap stocks favored by online posters and finds that online talk has the power to predict the next‐day returns.

Natural disaster often brings damage to the economy, including the decrease of stock’s market value. For this reason, this study aims to determine the effect of the tsunami earthquakes in Lombok in 2018 on abnormal returns and cumulative abnormal returns of insurance companies. This study used the event study approach, with three days window period after the three tsunami earthquakes from July to August 2018. The sample of this study is the stock price of 14 insurance companies listed on the Indonesia Stock Exchange. To test whether abnormal return exists, a one-sample t-test was used on the average abnormal and cumulative returns. The results show that the tsunami earthquake disasters in Lombok in 2018 have a significant effect on cumulative abnormal returns of insurance companies stocks, and this effect even bigger on the third tsunami. This finding shows that the market reacts to continuous disaster by considering the earthquake as negative information and thus decrease the stock price. This study implies that investors may buy the stocks after the disaster to get a cheaper price or hold the stocks to avoid loss.
 Keywords: abnormal return; event study; Lombok tsunami earthquake; signaling theory

This study develops a structural equation model linking both abnormal stock returns and abnormal trading volume to unexpected changes in accounting ratios that result from the issuance of annual accounting data. The three contributions of this study are as follows: (a) a simultaneous investigation of both the price and the trading activity stock market reactions to the issuance of annual financial statements; (b) the application of a measurement model to depict the changes in a firm's financial characteristics, which result from the issuance of financial statements; and (c) a causal model structure is developed, estimated, and tested. Through overidentification of the model, the hypothesized model structure is evaluated. Instead of investigating the price and trading activity reactions separately, as was done in previous studies, the two reactions are modeled simultaneously and are linked. A measurement model is hypothesized to aggregate the unexpected changes in 13 financial ratios into the unexpected changes in 4 latent financial dimensions: liquidity, leverage, profitability, and activity. The structural model then links the unexpected changes in the financial dimensions to abnormal stock market returns and trading volume. The 13 equations of the measurement model and the 2 structural equations are estimated simultaneously using LISREL, a full information maximum likelihood estimation procedure. The model is estimated, and the hypothesized model configuration recreates 82% of the generalized variance in the observed data. The individual parameter estimates show that the major source of variation in abnormal returns is the unexpected changes in profitability. None of the unexpected changes in the financial dimensions are found to be significantly linked directly to abnormal trading volume. Instead, the link is indirect through the relationship between abnormal returns and abnormal volume.

The aim of this study is to analyze and compare the abnormal earnings announcement returns of «concentrated» and «diversified» U.S. REITs from 2000 to 2017. Using a unique property-level dataset, we analyze the impact of geographic concentration on the relative performances of real estate investments trusts (REITs). More precisely, we focus on financial analysts’ forecast accuracy, market-level uncertainty, REIT-level uncertainty and synchronicity. First, we document the coverage, the accuracy and the bias of financial analysts’ earnings forecasts on «concentrated» and «diversified» REITs. Our results report that the level of accuracy and the level of optimism are statistically different for these two categories. Second, we observe that abnormal stock returns, abnormal trading volume and abnormal volatility may be related to the level of geographic concentration and synchronicity. Our results shed a new light on the potential link between the level of geographic concentration, or home bias at home, and the level of information on stock markets.

This study aims to determine the impact of political issues on market reaction when announcing the results of the 2019 Indonesian president and vice president election. The population in this study are all companies listed on the LQ45 Stock Index on the Indonesia Stock Exchange from February 2019 to July 2019. Sample taken by using the census method of 45 companies. The type of data used is quantitative and qualitative data obtained from secondary sources collected by the nonparticipant observation method. To test the information content, this study uses an event study approach. In this study there were two periods of events tested, namely the announcement of the results of the presidential and vice presidential elections in 2019 based on the quick count of the Survey Institute and the real count of the General Election Commission. To test the significance of abnormal returns the One Sample Test is used. The results of this study indicate that at the time of the announcement of the general election results based on the Survey Institute's quick count, there was a significant positive average abnormal return on the second day after the event date, while at the announcement of the general election results based on the General Election Commission's real count, there was no abnormal average significant return after the event date. The results concluded that the market must carefully search for information and be able to predict situations that are influenced by political issues to avoid risk. Keywords: event study, abnormal return, market reaction, political issues DOI : 10.7176/EJBM/12-3-15 Publication date: January 31 st 2020

This study examined the impact of deceptive advertising on the abnormal stock returns of firms. Using an event study analysis with 101 cases from the FTC database over the period 1987–2005, the FTC rulings on deceptive advertising were found to have the negative effects on the abnormal stock returns of firms. Among the firm-specific factors examined in this study, the amount of advertising expenditures played a role in alleviating the impact of deceptive advertising on the abnormal stock returns, and the firms charged with consent agreements alone were found to lose less firm value than those charged with additional actions by the FTC. Results also showed that the negative effects on the abnormal stock returns created by the FTC actions did not quickly disappear afterwards. These results imply that marketing managers should exercise caution in designing advertising messages that may or may not intend to violate the FTC rules and regulations on deceptive advertising.

Using Twitter trust network for stock market analysis

Exposure to surgery and anesthesia in early childhood has been found to be associated with an increased risk of behavioral deficits. While the US Food and Drug Administration (FDA) has warned against prenatal exposure to anesthetic drugs, little clinical evidence exists to support this recommendation. This study evaluates the association between prenatal exposure to general anesthesia due to maternal procedures during pregnancy and neuropsychological and behavioral outcome scores at age 10. This is an observational cohort study of children born in Perth, Western Australia, with 2 generations of participants contributing data to the Raine Study. In the Raine Study, the first generation (Gen1) are mothers enrolled during pregnancy, and the second generation (Gen2) are the children born to these mothers from 1989 to 1992 with neuropsychological and behavioral tests at age 10 (n=2024). In the primary analysis, 6 neuropsychological and behavioral tests were evaluated at age 10: Raven's Colored Progressive Matrices (CPM), McCarron Assessment of Neuromuscular Development (MAND), Peabody Picture Vocabulary Test (PPVT), Symbol Digit Modality Test (SDMT) with written and oral scores, Clinical Evaluation of Language Fundamentals (CELF) with Expressive, Receptive, and Total language scores, and Child Behavior Checklist (CBCL) with Internalizing, Externalizing, and Total behavior scores. Outcome scores of children prenatally exposed to general anesthesia were compared to children without prenatal exposure using multivariable linear regression models adjusting for demographic and clinical covariates (sex, race, income, and maternal education, alcohol or tobacco use, and clinical diagnoses: diabetes, epilepsy, hypertension, psychiatric disorders, or thyroid dysfunction). Bonferroni adjustment was used for the 6 independent tests in the primary analysis, so a corrected P value <.0083 (P = .05 divided by 6 tests, or a 99.17% confidence interval [CI]) was required for statistical significance. Among 2024 children with available outcome scores, 22 (1.1%) were prenatally exposed to general anesthesia. Prenatally exposed children had higher CBCL Externalizing behavioral scores (score difference of 6.1 [99.17% CI, 0.2-12.0]; P = .006) than unexposed children. Of 6 tests including 11 scores and subscores, only CBCL Externalizing behavioral scores remained significant after multiple comparisons adjustment with no significant differences found in any other score. Prenatal exposure to general anesthetics is associated with increased externalizing behavioral problems in childhood. However, given the limitations of this study and that avoiding necessary surgery during pregnancy can have significant detrimental effects on the mother and the child, further studies are needed before changes to clinical practice are made.

This study presents data on abnormal stock return movements with simple calculations. The result of deep analysis using event study method from major stocks in each sector, prove that There is negative response by the market to the student demonstration during the end of September 2019 that create abnormal return condition until it gets back to be normal in the middle of October. The sectors studied include the banking sector, construction, infrastructure, consumer needs, media, industrial materials, machinery, mining, and health care. Stock returns in Indonesia with inefficient market conditions are vulnerable to issues. Capital markets tend to be easily influenced by political and macroeconomic conditions, but even though the condition of return is abnormal, investors still have the potential to get favourable results.&#x0D; Keywords: Stock market, Market efficiency, Event study, Stock Price, Stock Returns

Nuclear magnetic resonance (NMR) spectroscopy-based metabonomics is of growing importance for discovery of human disease biomarkers. Identification and validation of disease biomarkers using statistical significance analysis (SSA) is critical for translation to clinical practice. SSA is performed by assessing a null hypothesis test using a derivative of the Student's t test, e.g., a Welch's t test. Choosing how to correct the significance level for rejecting null hypotheses in the case of multiple testing to maintain a constant family-wise type I error rate is a common problem in such tests. The multiple testing problem arises because the likelihood of falsely rejecting the null hypothesis, i.e., a false positive, grows as the number of tests applied to the same data set increases. Several methods have been introduced to address this problem. Bonferroni correction (BC) assumes all variables are independent and therefore sacrifices sensitivity for detecting true positives in partially dependent data sets. False discovery rate (FDR) methods are more sensitive than BC but uniformly ascribe highest stringency to lowest p value variables. Here, we introduce standard deviation step down (SDSD), which is more sensitive and appropriate than BC for partially dependent data sets. Sensitivity and type I error rate of SDSD can be adjusted based on the degree of variable dependency. SDSD generates fundamentally different profiles of critical p values compared with FDR methods potentially leading to reduced type II error rates. SDSD is increasingly sensitive for more concentrated metabolites. SDSD is demonstrated using NMR-based metabonomics data collected on three different breast cancer cell line extracts.

The Leverage Effect on Stock Returns