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The purpose of this study is to introduce a matching function approach to analyze matching in financial reporting.

The matching function is first analyzed analytically. It is specified as a multiplicative Cobb-Douglas-type function of three categories of expenses (labor expense, material expense and depreciation). The specified matching function is solved by the generalized reduced gradient method (GRG) for 10-year time series from 8,226 Finnish firms. The coefficient of determination of the logarithmic model (CODL) is compared with the linear revenue-expense correlation coefficient (REC) that is generally used in previous studies.

Empirical evidence showed that REC is outperformed by CODL. CODL was found independent of or weakly negatively dependent on the matching elasticity of labor expense, positively dependent on the material expense elasticity and negatively dependent on depreciation elasticity. Therefore, the differences in matching accuracy between industries emphasizing different expense categories are significant.

The matching function is a general approach to assess the matching accuracy but it is in this study specified multiplicatively for three categories of expenses. Moreover, only one algorithm is tested in the empirical estimation of the function. The analysis is concentrated on ten-year time-series of a limited sample of Finnish firms.

The matching function approach provides a large set of important information for considering the matching process in practice. It can prove a useful method also to accounting standard-setters and other specialists such as managers, consultants and auditors.

This study is the first study to apply the new matching function approach.

European countries are likely to increasingly adopt integrated reporting (IR) voluntarily, after the 2014/95/EU Directive is revised and other initiatives are implemented. Therefore, the present study provides insights on the relevance of IR in voluntary contexts by exploring analysts' reactions to the release of integrated reports in diverse institutional settings.

Drawing on voluntary disclosure theory, a quantitative empirical research method is used to explore the moderating role of country-level institutional characteristics on the associations between voluntary IR release and analyst forecast accuracy and dispersion.

IR informativeness is not uniform in the voluntary context and institutional settings play a moderating role. IR release is associated with increased consensus among analyst forecasts. However, in countries with weak institutional enforcement, a reverse association is detected, indicating that analysts rely largely on IR where the institutional setting strongly protects investors. Although a strong institutional setting boosts the IR release usefulness in terms of accuracy, it creates noise in analyst consensus.

Academics can appreciate the usefulness of voluntary IR across the institutional enforcement contexts.

Managers can use these findings to understand opportunities offered by IR voluntary release. The study recommends that policymakers, standard setters and regulators strengthen the institutional enforcement of sustainability disclosure.

This study is a unique contribution to recent calls for research on the effects of nonfinancial disclosure regulation and on IR “impacts”. It shows on the international scale that IR usefulness for analysts is moderated by institutional patterns, not country-level institutional characteristics.

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

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

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

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

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

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

The purpose of this study is to investigate whether audit quality is associated with the speed with which managers revise earnings forecasts to arrive at the actual earnings through the lens of the auditor selection theory. This study examines this relationship in a unique institutional setting, Japan, where nearly all managers disclose earnings forecasts.

The authors pioneer an empirical proxy to capture the speed of management forecast revisions based on well-established principles from the finance and disclosure literatures. This proxy is tested alongside other disclosure proxies (namely, accuracy, frequency and timeliness) to assess the influence of audit quality on managerial forecasting behavior.

This empirical analysis shows that forecast revision speed is higher for firms that select higher-quality auditors. While firms that select higher-quality auditors revise forecasts in a more timely fashion, these firms revise less frequently. Moreover, the authors find that the influence of audit quality on forecast revisions is asymmetric. Specifically, the analysis of downward forecast revisions shows that higher-quality auditors are associated with firms that disclose bad news via forecasts revisions faster, more frequently and in a more timely fashion. However, the analysis of upward forecast revisions shows that higher-quality auditors have no effect on the speed with which firms disclose good news via forecast revisions, even though they are associated with less frequent but more timely forecast revisions. These findings have important implications for prior studies that consistently document an asymmetric response of the stock market to good news and bad news.

The authors provide evidence on the relationship between audit quality and management earnings forecasts using a novel and intuitive measure that captures forecast revision speed. This measure speaks to the growing interest in understanding the notion of speed and timing of voluntary disclosures. This study provides a more robust and comprehensive measure of the speed with which managers revise their earnings forecasts to arrive at the actual earnings. Furthermore, this study is among the first to document an asymmetric effect of audit quality on the type of news disclosed in forecast revisions.

This paper aims to study the impact of audit quality on the components of executive cash compensation. It is predicted that as audit quality improves, greater emphasis will be placed on the incentive components of cash compensation, and lower emphasis on the salary (fixed) component. Specifically, it is predicted that as audit quality enhances, greater emphasis will be placed on earnings and sales revenues in determining executive cash compensation. Using auditor specialization as a proxy for audit quality, empirical support is provided for all of our predictions.

This paper provides empirical support with agency theoretic predictions.

This paper developed the following hypotheses: H1 – in executive cash compensation, more weight is being placed on earnings-based measures as auditor specialization improves; H2 – in executive cash compensation, more weight is also being placed on sales revenues as auditor specialization improves; H3 – in executive cash compensation, salary levels decrease as auditor specialization improves; and H4 – the impact of auditor specialization on the weight on earnings, sales and the salary levels is lower in the post-Sarbanes–Oxley Act (SOX) period compared to pre-SOX period.

First, the article limits itself to cash compensation, while current executive compensation is largely made of equity. Second, the measure of audit quality used, ‘national level auditor specialization’, may not be as effective in the post-SOX era.

Compensation committees should pay attention to audit quality (in whatever way it may be proxied by) in determining executive compensation.

This is the first paper to show that audit quality not only improves the earnings response coefficient in firm valuation but also enhances the weight placed on earnings (and sales revenues) in executive compensation.

The objective of this paper is to investigate the direction of the causal relationship between dividend policy (DP) and earnings management (EM).

This research utilizes the panel data analysis to investigate the causal relationship between EM and DP. It provides empirical insights based on a sample of 280 French nonfinancial companies listed on the CAC All-Tradable index during the period of 2008–2015. The study initiates with a Granger causality examination on the unbalanced panel data and employs a dynamic panel approach with the generalized method of moments (GMM). It further estimates the empirical models simultaneously using the three-stage least squares (3SLS) method and the iterative triple least squares (iterative 3SLS) method.

The estimation of our various empirical models confirms the presence of a bidirectional causal relationship between DP and EM.

Our study highlights the prevalence of EM in the French context, particularly within DP. It underscores the need for regulatory bodies, the Ministry of Finance, external auditors and stock exchange organizers to prioritize governance mechanisms for improving the quality of financial information disclosed by companies.

This research is, to the best of our knowledge, the first is to extensively investigate the reciprocal causal relationship between DP and EM in France. Previous studies have not placed a significant emphasis on exploring this bidirectional link between these two variables.

Confidence intervals play a crucial role in economics and finance, providing a credible range of values for an unknown parameter along with a corresponding level of certainty. Their applications encompass economic forecasting, market research, financial forecasting, econometric analysis, policy analysis, financial reporting, investment decision-making, credit risk assessment and consumer confidence surveys. Signal-to-noise ratio (SNR) finds applications in economics and finance across various domains such as economic forecasting, financial modeling, market analysis and risk assessment. A high SNR indicates a robust and dependable signal, simplifying the process of making well-informed decisions. On the other hand, a low SNR indicates a weak signal that could be obscured by noise, so decision-making procedures need to take this into serious consideration. This research focuses on the development of confidence intervals for functions derived from the SNR and explores their application in the fields of economics and finance.

The construction of the confidence intervals involved the application of various methodologies. For the SNR, confidence intervals were formed using the generalized confidence interval (GCI), large sample and Bayesian approaches. The difference between SNRs was estimated through the GCI, large sample, method of variance estimates recovery (MOVER), parametric bootstrap and Bayesian approaches. Additionally, confidence intervals for the common SNR were constructed using the GCI, adjusted MOVER, computational and Bayesian approaches. The performance of these confidence intervals was assessed using coverage probability and average length, evaluated through Monte Carlo simulation.

The GCI approach demonstrated superior performance over other approaches in terms of both coverage probability and average length for the SNR and the difference between SNRs. Hence, employing the GCI approach is advised for constructing confidence intervals for these parameters. As for the common SNR, the Bayesian approach exhibited the shortest average length. Consequently, the Bayesian approach is recommended for constructing confidence intervals for the common SNR.

This research presents confidence intervals for functions of the SNR to assess SNR estimation in the fields of economics and finance.

The use of social media tools by companies is common, but the links between the use of multiple social media tools by companies and stock price changes are largely unknown. Therefore, this study aims to analyze the value-relevance of social media activities on Facebook (FB), Instagram (IG), LinkedIn (LI), Twitter (TW) and YouTube (YT).

Stock market data and hand-picked social media data in this study were collected from Finland, a small language area with consistent International Financial Reporting Standards (IFRS) reporting practices, in the expectation of better comparability and lower noise in the data.This study uses correlation, regression and factor analyses for a sample of 105 Finnish public limited companies listed on the Nasdaq Helsinki stock exchange.

This paper finds evidence that social media activity is an important area of analysis and that the activity and popularity of a company in social media are value-relevant variables in forecasting stock prices.

Not all social media activities are necessarily equally important for managers and investors. Focus on visual messages in social media is recommended.

The findings of this study highlight the value-relevance of using multiple visual social media channels, particularly IG and YT. This paper suggests avenues for future research and for analyzing social media information.

The purpose of this paper is to evaluate the influence of the informational environment on the relevance of accounting information in companies traded in stock exchanges of emerging markets.

For this purpose, the authors calculated indicators based on figures derived from the financial statements and variables that sought to capture the influence of the economic and institutional environment. The sample consisted of publicly traded companies from 20 countries classified as emerging by Standard & Poors. Macroeconomic information was obtained through the International Country Risk Guide database. The analysis period ranged from 2004 to 2013, excluding missing data, variables considered as outliers, besides the exclusion of data from companies that presented negative equity.

It was observed that the financial variables presented signs consistent with the literature, except for the price-to-book variable and the asset change variable. The inclusion of variables related to the accounting informational environment offered evidence that the more opaque the accounting environment in the country, the lesser the ability of the profits to portray the variations of stock returns. The variable that captured the adoption of international standards was consistent with expectations, i.e. the adoption of international standards would increase the quality of accounting information, showing a positive signal. Moreover, the variable aggressiveness of the earnings was statistically significant and negative, consistent with the literature.

The variables earnings smoothing and aversion to losses did not show the expected behaviour though, highlighting the possible limitations of these proxies used to capture the opacity of the earnings.

When institutional moderators were included, it was observed that the adoption of the IFRS standards positively affected the relationship, which is more relevant when the accounting figures were under its aegis. Recently, countless nations’ transition to international accounting standards has been justified by the need to use high-quality reporting standards. The research sought to contribute to strengthen this dimension, presenting evidence that the dummy variable included to capture the adoption of international standards had a positive effect on the relationship.

Using the next-day and next-week returns of stocks in the Korean market, we examine the association of option volume ratios – i.e. the option-to-stock (O/S) ratio, which is the total volume of put options and call options scaled by total underlying equity volume, and the put-call (P/C) ratio, which is the put volume scaled by total put and call volume – with future returns. We find that O/S ratios are positively related to future returns, but P/C ratios have no significant association with returns. We calculate individual, institutional, and foreign investors’ option ratios to determine which ratios are significantly related to future returns and find that, for all investors, higher O/S ratios predict higher future returns. The predictability of P/C depends on the investors: institutional and individual investors’ P/C ratios are not related to returns, but foreign P/C predicts negative next-day returns. For net-buying O/S ratios, institutional net-buying put-to-stock ratios consistently predict negative future returns. Institutions’ buying and selling put ratios also predict returns. In short, institutional put-to-share ratios predict future returns when we use various option ratios, but individual option ratios do not.