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This study aims to examine how financial analysts evaluate other comprehensive income (OCI) information with a focus on the information content and economic substance of OCI gain and loss.

This study conducted a 2 × 2 between-subject experiment by manipulating profitability (net profit or net loss) and OCI (OCI gain or loss). A total of 103 equity research analysts participated in the experiment.

The results show that when the company suffers a net loss, the presence of unrealized gain in OCI appears to cause concern for analysts, in that they assigned a lower valuation to the OCI gain company than the OCI loss company. However, in the cases where the company is profitable, analysts appeared to respond to the direction of OCI (i.e. gain or loss) and incorporated the directional information in their valuation judgment.

The experimental results complement prior archival research on OCI valuation. This study extends prior work on OCI’s decision usefulness, improves understanding of the impact of OCI on firm valuation and contributes to the ongoing debate about whether OCI is viewed as a performance measure. The findings indicate that the effect of OCI gains or losses is most pronounced when the company experiences a loss. During such instances, analysts may interpret a combination of net loss and OCI gain as a potential indicator of earnings management opportunities. Consequently, they may perceive it as a signal of deteriorating future financial performance.

This paper aims to examine whether firms meeting or just beating an earnings benchmark engage in tone management in earnings conference calls to complement earnings management in the UK context. It also investigates whether the audience tone in beating or just meeting earnings fails to predict future performance.

This study was performed using a sample of non-financial UK firms listed in the FTSE 350 index over the period 2010–2015.

The findings show that firms that exercise more earnings management to meet or just beat earnings are positively associated with the abnormal tone during earnings conference calls. The outcomes also reveal that the audience’s tone of firms meeting or just beating an earnings benchmark fails to predict future performance. This confirms the effectiveness of the tone management in managing the perception of audience.

This study highlights the need for increased accountability by firms on earnings conference call. It also supports academics and practitioners in understanding the management discretion used in reporting and communication during the earnings conference call. Overall, the results of this study are beneficial for regulators, policymakers and professionals, regarding confirming the need for the earnings conference calls to be regulated.

To the best of the authors’ knowledge, this is the first study that examines the association between earnings management and tone management in the UK earnings conference calls. It adds to the existing literature by examining the self-serving behaviour of managerial tone during earnings conference calls within a sitting in which meeting or just beating a benchmark is used. Unlike several studies that explain the behaviour of tone as a signalling strategy, this study reveals that the tendency of impression management behaviour can explain the tone management.

Even though the end-user satisfaction construct has gained prominence as a surrogate measure of information systems performance assessment, it has received scant formal treatment and empirical examination in the data analytics systems field. In this respect, this study aims to examine the vital role of user satisfaction as a proxy measure of data analytics system performance in the financial engineering context.

This study empirically validated the proposed model using primary quantitative data obtained from financial managers, engineers and analysts who are working at Jordanian financial institutions. The quantitative data were tested using partial least squares-based structural equation modeling.

The quantitative data analysis results identified that technology quality, information quality, knowledge quality and decision quality are key factors that enhance user satisfaction in a data analytics environment with an explained variance of around 69%.

This empirical research has contributed to the discourse regarding the pivotal role of user satisfaction in data analytics performance in the financial engineering context of developing countries such as Jordan, which lays a firm foundation for future research.

This paper aims to examine the association between perceived firm risk and two reporting mechanisms: risk disclosure and earnings smoothing in the UK context.

This study juxtaposes three competing views, the “null”, the “divergence” and the “convergence” hypotheses, and empirically investigates whether risk disclosure and earnings smoothing affect firm perceived risk for a sample of large UK firms with rich and poor information environments. This study also uses the global financial crisis as an external shock on overall risk in the economy to investigate when and how managers use these two reporting mechanisms to shape the firm perceived risk.

This paper documents that risk disclosures have no significant effect on investors’ risk perceptions, consistent with risk disclosures containing boilerplate and generic statements about firm risk. This paper also finds that earnings smoothing reduces investors’ risk perceptions, reflecting investors’ interpretations about future firm performance. Additional tests reveal that earnings smoothing is not associated with perceived firm risk for firms with rich information environments and expanded risk disclosures. Furthermore, reporting smooth earnings decreases perceived firm risk following the global financial crisis. These findings are robust to alternative specifications and measures of earnings smoothing as well as post-filing perceived firm risk.

This study does not distinguish between the garbling role and the informational role of earnings smoothing. The risk disclosure measurement used in this study, developed based on UK annual reports, may limit the generalizability of findings to other countries.

The findings suggest that managers should revise their risk disclosure strategies to provide in-depth details on firm risk. Investors might require information and thorough assessment to evaluate investment risks when firms provide generic risk disclosures and smoothed earnings by consulting sources like financial intermediaries. Regulators should keep an eye on firms reporting boilerplate risk disclosures and on how smoothing earnings impacts the firm perceived risk following economic turmoil, to guide interventions that promote market stability.

The findings provide new insights into when and how managers use their financial reporting discretion to make firms appear less risky and, therefore, influence investors’ risk perceptions.

This chapter focuses on how alternative data can change the nature of financial forecasting through improved short-term forecasting techniques and decreased informativeness from longer term sources. Increased use of social media data leads the charge in transforming this transition. Alternative data are data not from standard financial statements or formal reports. This chapter looks at alternative data from new sources (e.g., social media, Internet of Things [IoT], and digital footprints) and alternative data from new collection methods like web scraping for textual analysis, image analysis, and vocal analysis). It first discusses standard data in financial forecasting. Next, this chapter examines alternative data in financial forecasting. Finally, it discusses alternative data used in studying finance more broadly.

We propose an alternative rationale for why some firms employ veterans, driven not solely by benevolence but also by the prospect of enhanced outcomes. Financially, hiring veterans could correlate with improved stock market performance for the hiring company while aligning with corporate social responsibility (CSR) initiatives. Our study centers on the stock market performance of companies hiring veterans. It aims to underscore a lesser-known facet of the veteran employment discourse and its connection to the hiring firm's financial performance.

This paper evaluates the stock market performance of three VETS portfolios (made of companies that hire veterans) compared to the benchmark SPDR S&P 500 ETF. Using a modular approach, we create three VETS passive indices: VETSEW (equal-weighted index), VETSPW (price-weighted index) and VETSVW (value-weighted index). The study analyzes the annual returns, portfolio allocations, risk-adjusted performance metrics and style analysis of the portfolios from January 1, 2020, to December 31, 2022.

The findings indicate that all three VETS portfolios outperformed the benchmark, with higher ending balances and superior risk-adjusted ratios such as the Sharpe and Sortino ratios. Notably, the portfolios demonstrated resilience during challenging periods, including the COVID-19 pandemic, subsequent recovery and an inflationary period.

Limitations include the paper's focus solely on stock returns, suggesting a need for broader financial and management ratios. Moreover, a deeper exploration into how veterans contribute during turbulent times is suggested for further investigation. Although the study touches upon the financial performance of veteran-focused companies during challenging economic times, it does not extensively delve into the specific ways in which veterans add value under such circumstances, presenting an opportunity for further exploration.

Firms that employ veterans amid the COVID-19 pandemic demonstrate favorable risk-adjusted returns, underscoring the potential of veterans as valuable crisis-time assets. Our research further underscores the correlation between veteran hiring and enhanced financial prowess. These insights carry significant policy implications, including CSR initiatives for hiring veterans, skill translation and training and collaboration with veteran organizations.

The paper's findings suggest significant implications: (1) Policymakers could incentivize firms to hire veterans through tax benefits or grants, leveraging their skills for organizational resilience. (2) Collaborative efforts between policymakers and firms can promote responsible hiring, boosting a company's reputation through diversity and inclusion, positively impacting society. (3) Support for skill translation from military to civilian jobs is crucial. Programs certifying skills and tailored education aid veterans' successful transition into the workforce. (4) Collaborations between policymakers, veteran organizations and private sector entities can create networks, job placements and support systems for veterans' employment.

Numerous prior studies within the domain of corporate social responsibility have predominantly neglected the contributions veterans offer to businesses and the underlying reasons behind firms' decisions to employ them. Our research uniquely concentrates on the stock market performance of companies that choose to hire veterans.

The aim of this study is to examine the patterns of fraud present in Valeant’s 2014 and 2015 financial statements and determine through a risk management analysis whether these frauds could have been prevented. This analysis provides the opportunity to more effectively prevent financial statement fraud.

Data were collected from Valeant pharmaceuticals annual reports, financial statements reports and financial authority documentation. Based on these documents, this paper analyzes the different fraud schemes and investigate whether fraud could have been detected earlier by governance actors. In particular, this paper examines the firm’s financial statements three years before the fraud was detected by the Securities and Exchange Commission.

The analysis of financial statements reveals few clues and no alarming red flags three years before detection of the fraud. However, financial statement analyses were complex because of the many acquisitions the firm made in the years before.

This paper aims to contribute to the literature on fraud by investigating a case of financial statement fraud.

The study aims to investigate market reactions associated with the JUST 100 rankings published by JUST Capital, a non-profit organization, as well as differences in financial reporting quality and performance between selected firms and their industry peers.

This study uses a sample of 431 firms selected as the 100 America’s Most Just Companies between 2016 and 2020 by JUST Capital. This study performs both an event study to determine whether the rankings are useful to investors and cross-sectional regression analyses on the characteristics of selected firms compared to their peers.

This study finds that investors react positively to selected firms around the time of the release of the JUST 100 rankings, suggesting that the rankings are decision-useful. This study also finds that selected firms exhibit higher accounting quality and financial performance than their peers.

Rankings may not be free from bias because of JUST Capital’s ownership of an exchange-traded fund.

The findings validate the rankings as well as the methodology used by JUST Capital, as they show market participants value firms that engage in socially responsible actions through their commitment to positively impact five key stakeholder groups: employees, customers, communities, environment and shareholders.

To the best of the authors’ knowledge, this is the first study that shows the importance of the JUST 100 rankings for investment decisions. Considering the growing push for companies to disclose environmental, social and governance (ESG) activities, this study provides evidence to support ESG disclosure regulations.

Prior studies have found that managers adjust operational activities to tackle climate risk. However, the effects of climate risk on accounting practices are largely ignored in the literature. This paper investigates whether and how climate risk influences managers’ decision-making on the level of accounting conservatism and explains the results based on two competing channels: valuation demand and contracting demand.

Using firm level climate risk measures, we build a modified Basu (1997) model to conduct our econometric tests. In the baseline model, we use earnings before extraordinary items as the dependent variable, referred to as the earnings model. We control for different levels of fixed effect to identify the shocks of climate risk and mitigate potential concerns on endogeneity and bias in the model. A series of robustness tests provide supporting evidence for our baseline results and our explanation.

Using a sample of 35,832 firm-year observations on listed US firms over the period 2002 to 2019, we find that the perception of climate risk drives managers to choose the less conservative accounting policies. We conclude that the results are consistent with the valuation demand explanation but inconsistent with the contracting demand explanation.

The study provides additional evidence on how managers respond to climate risk by adjusting their corporate polices, specifically accounting policies. Our findings contradict the results of prior studies. We explain our results from a unique perspective. Overall, the study provides valuable insights for academics, investors, managers and policymakers.