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The purpose of this paper is to examine the usefulness of statistical studies of financial reports and stock market data for improving corporate financial reports.

Analytical writing.

It is often claimed that statistical studies of co-variation between financial and stock market data can help set better financial reporting policy. Such co-variation, even when it can be estimated, tells us little about which financial reports help to make better financial decisions. A case in support of such claims remains to be made.

The readers are advised to be extremely careful in drawing inferences from studies of co-variation between accounting and stock market data for financial reporting policy.

Inference from accounting empirical studies to policy needs better rationale to avoid bad policy consequences.

This paper raises original questions about policy inferences from a large class of empirical research in accounting.

To better understand the impact of choosing a carbon data provider for the estimated portfolio emissions across four asset classes. This is important, as prior literature has suggested that Environmental, Social and Governance scores across providers have low correlation.

The authors compare carbon data from four data providers for developed and emerging equity markets and investment grade and high-yield corporate bond markets.

Data on scope 1 and scope 2 is similar across the four data providers, but for scope 3 differences can be substantial. Carbon emissions data has become more consistent across providers over time.

The authors examine the impact of different carbon data providers at the asset class level. Portfolios that invest only in a subset of the asset class may be affected differently. Because “true” carbon emissions are not known, the authors cannot investigate which provider has the most accurate carbon data.

The impact of choosing a carbon data provider is limited for scope 1 and scope 2 data for equity markets. Differences are larger for corporate bonds and scope 3 emissions.

The authors compare carbon accounting metrics on scopes 1, 2 and 3 of corporate greenhouse gas emissions carbon data from multiple providers for developed and emerging equity and investment grade and high yield investment portfolios. Moreover, the authors show the impact of filling missing data points, which is especially relevant for corporate bond markets, where data coverage tends to be lower.

While existing research explores the impact of audit market competition on audit fees and audit quality, there is limited investigation into how competition in the audit market influences auditors' writing style. This study examines the relationship between audit market competition and the readability of audit reports in Iran, where competition is particularly intense, especially among private audit firms.

The sample comprises 1,050 firm-year observations in Iran from 2012 to 2018. Readability measures, including the Fog index, Flesch-Reading-Ease (FRE) and Simple Measure of Gobbledygook (SMOG), are employed to assess the readability of auditors' reports. The Herfindahl–Hirschman Index (HHI) is utilized to measure audit market competition, with lower index values indicating higher auditor competition. The concentration measure is multiplied by −1 to obtain the competition measure (AudComp). Alternative readability measures, such as the Flesch–Kincaid (FK) and Automated Readability Index (ARI) are used in additional robustness tests. Data on textual features of audit reports, auditor characteristics and other control variables are manually collected from annual reports of firms listed on the Tehran Stock Exchange (TSE).

The regression analysis results indicate a significant and positive association between audit market competition and audit report readability. Furthermore, a stronger positive and significant association is observed among private audit firms, where competition is more intense compared to state audit firms. These findings remain robust when using alternative readability measures and other sensitivity checks. Additional analysis reveals that the positive effect of competition on audit report readability is more pronounced in situations where the auditor remains unchanged and the audit market size is small.

This paper expands the existing literature by examining the impact of audit market competition on audit report readability. It focuses on a unique audit market (Iran), where competition among audit firms is more intense than in developed countries due to the liberalization of the Iranian audit market in 2001 and the establishment of numerous private audit firms.

The recommendation of the analyst report is not only limited to a small number of ratings, but also biased toward a buy opinion with the absence of sell opinion. As an alternative to this, this paper aims to extract analysts' textual opinions embedded in the report body through text analysis and examine the profitability of investment strategies. Analyst opinion about a firm is measured by calculating the frequency of positive and negative words in the report text through the Korean sentiment lexicon for finance (KOSELF). To verify the usefulness of textual opinions, the author constructs a calendar-time based portfolios by the analysts' textual opinion variable of each stock. When opinion level is used, investment strategy has no significant hedged portfolio return. However, hedged portfolio constructed by opinion change shows significant return of 0.117% per day (2.57% per month). In addition, the hedged return increases to 0.163% per day (3.59% per month) when the opening price is used instead of closing price. This study show that the analysts’ opinion extracted from text analysis contains more detailed spectrum than recommendation and investment strategies using them give significant returns.

The determinants of investors’ sentiment based on secondary stock market proxies in many empirical studies are reported. However, to the best of our knowledge, no study undertakes investor sentiment drivers developed from primary survey measures by constructing an investor sentiment index (ISI) in relation to market drivers to date. This study aims to fill this research gap by first developing the ISI for the Indian retail investors and then examining which of the stock market drivers impacts such sentiment.

The ISI is constructed using the mean scores of eight statements as formulated based on popular direct investor sentiment surveys undertaken across the world. Then, we use the multiple regression approach overall and for top 33.33% (high-sentiment) and bottom 33.33% (low-sentiment) investors based on the responses of 576 respondents on 18 statements (proxying eight study hypotheses) collected in 2016. Moreover, the demography-based classification based investors’ sentiment is examined to make our results more robust and in-depth.

On an overall basis, the IPO activities/issues and information certainty, trading volume and momentum and institutional investors’ investment activities market drivers significantly and positively impact retail investors is examined. However, only IPO activities/issues and information certainty influences both high- and low-sentiment investors. It is intriguing to report that nature of the stock markets show conflicting results for high- (negative significant) and low- (positive significant) sentiment investors.

The construction of the ISI from primary survey measure is for the first time in Indian context in relation to investigating the stock market drivers influential to retail investors’ sentiment. In addition, hypothesized market drivers are also unique, each representing different fundamental and technical characteristics associated with the Indian market.

The study aims to examine the appropriateness of the coefficient of elasticity of trading (CET) as a measure of liquidity using Nigerian stock market data. Given that liquidity is multidimensional, the CET is complemented with the popular measure of liquidity, turnover ratio to explore the causal relationship among the CET, turnover ratio and market return to determine their relevance in security valuation. In other words, an attempt is made to examine if either of these two measures of liquidity is a relevant factor in explaining stock market return.

The Toda-Yamamoto version of Granger causality test is applied to two sets of data on the Nigerian Stock Exchange (NSE). The available monthly time series data are from 2008 to 2019 while the annual data are from 1986 to 2018. The Toda-Yamamoto test is preferred because it is more robust to integration and cointegration of the variables.

The results of the Toda-Yamamoto version of the Granger causality test on monthly data reveal no causal relationship between CET and market return, turnover and market return and CET with turnover and market return. These results are consistent with those for several frontier countries reported by Rubio et al. (2005), Hartian and Sitorus (2015), Batten and Vo (2019) and Sterenczak et al. (2020). The results support the conclusion that the Nigerian economy is not fully integrated with the global economy. Market inefficiency due to order imbalances given the nature of the trading system can also explain the reported results. However, the results from annual data do not tally with the monthly results. There is causality running from CET to market return. There is also causality running from turnover to market return. Therefore, both CET and turnover are statistically significant causal predictors of market return. The results from annual data are consistent with those reported by Marozva (2019).

The key limitation is availability of high-frequency transaction-level data to researchers to consider many measures of liquidity that have been employed in developed countries. The research implication is that more researchers will be encouraged to conduct more studies on liquidity and how the study results can drive policy recommendations. The standard asymptotic distribution of underlying the Toda-Yamamoto approach has been found to lead to overrejection.

This study is the first to apply Toda-Yamamoto model on data from Nigeria to investigate the causal relationship between stock market return and liquidity proxied by the CET given the nature of the automated trading system (ATS) in use. The CET is also complemented with the turnover ratio to explore the multidimensional nature of liquidity and its causal relationship with market return. The study is also interpreted as a determination of the integration of Nigeria's economy with the global economy with its implication on investment diversification.

This study aims to explore the possibility that securities markets in selected African countries of Egypt, Kenya, Nigeria and South Africa play a significant role in capital accumulation using panel data analysis. This is done by exploring the relationship between gross fixed capital formation on the one hand and financial market development indicators on the other hand. Thus, the study aims to examine if stock market size and liquidity are determinants of capital accumulation.

The analysis is based on annual times series from 1991 through 2017 spanning four African stock markets. The analysis utilizes the fixed-effect and random-effect econometric models. The Durbin–Wu–Hausman test is used to choose between the two models.

The key results indicate that stock market capitalization is a positive determinant of gross fixed capital formation. The market value traded and turnover have no relationship with capital formation. Therefore, the role of stock African stock markets in promoting capital accumulation and, subsequently, industrial growth in Africa is seriously questioned.

Only a handful of studies have examined the role of the African securities market in promoting capital accumulation. This study is unique in which it focuses on the leading stock markets in the four corners of Africa. The markets are from Egypt in the north, South Africa from the south, Nigeria from the west and Kenya from the east. These four markets account for a significant segment of all African markets.

Given the importance of style allocation strategy under the outsourced chief investment officer (OCIO) structure, the authors examine the validity of style allocation strategies in the Korean stock market. The authors find that external investment agencies can improve performance by using newly suggested investment styles such as high dividend yield and low volatility as well as traditional styles. In addition, the authors find that the style combination strategies create economically large and statistically significant returns. Finally, empirical results indicate that factor timing strategies suggested in this study can improve the reward-to-risk ratio. In sum, the empirical findings indicate that external investment agencies under the OCIO structure can improve performance using active style allocation strategies.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.