Journal of Corporate Accounting and Finance最新文献

The growing interest in cryptocurrencies has brought this new means of exchange to the attention of the financial world. This study aims to investigate the effects that a cryptocurrency can have when it is considered as a financial asset. The analysis is carried out from an ex-post perspective, evaluating the performance achieved in a certain period by three different portfolios. These are the one composed only of equities, bonds and commodities, the second one only of cryptocurrencies, and the third one is a combination of these both ones and thus made up of all considered “traditional” assets and the most performing cryptocurrency of the second portfolio. For these purposes, the classic variance-covariance approach is applied where the calculation of the risk structure is done via the GARCH-Copula and GARCH-Vine Copula approaches. The optimal weights of the assets in the optimized portfolios are determined through Markowitz optimization problem. The analysis mainly showed that the portfolio composed of cryptocurrency and traditional assets has a higher Sharpe index, from an ex-post perspective, and more stable performances, from an ex-ante perspective. We justify our selection of the Markowitz approach over conditional VaR and expected shortfall due to their heightened sensitivity to unsystematic extreme events in crypto markets.

Although prior research has recently begun to examine the effects of independent director reputation incentives and the benefits of having a lead independent director, no study has considered the combined impact: the reputation incentives of lead independent directors. This study integrates these emerging streams of research to investigate whether the reputation incentives of lead independent directors affect audit fees. We find that firms with a lead independent director who has relatively low reputation incentives are associated with audit fees that are 4.39% higher than firms with a lead independent director who has neutral reputation incentives, consistent with auditors viewing these firms as riskier. We also find that this association is driven by auditors who are not industry specialists. Our results continue to hold when using an entropy balancing approach and when conducting other robustness tests.

Following the financial crisis, business practice and regulatory have become much more interested in corporate disclosure on risk and risk management. The crises necessitate enhancing corporate governance (CG) processes, risk disclosure, reporting, and accounting. This paper aims to empirically analyze specific components of disclosure quality that could be associated with the likelihood of mitigating earnings management (EM) practices. The Bursa Malaysia website, Bloomberg, and the annual reports of the listed firms were utilized as the sources for the data. Descriptive statistics and GLS methods of panel regression were the analytical techniques used in the current investigation. Corporate data of the listed firms on Bursa Malaysia covering financial periods of 2011–2022 were used to examine the research hypotheses. The findings from the panel regression suggested that internal control system disclosure (ICSD) and intellectual capital disclosure (ICD) both have negative and significant associations to the likelihood of EM practices. However, the findings also established negative but insignificant relationships between corporate risk disclosure (CRD), corporate voluntary disclosure (CVD), and the likelihood of EM practices across the sample. This study has implications to companies striving to satisfy shareholders and attract potential investors. The authors add to the growing body of literature on quality disclosure to the larger body of CG literature. Additionally, the study is original as it is the first to consider four qualities (internal control system disclosure, corporate risk disclosure and corporate voluntary disclosure, and voluntary ICD in the Malaysian context of EM practices.

This study examines how investors of S&P 500 firms react to the SEC's mandatory climate disclosure proposal announced on March 21, 2022. The result of the event study with a 3-day window [−1,1] shows a negative 1.1% market reaction to the proposal. The cross-sectional analysis shows that better ESG performers, higher sales growth firms, and firms with higher Tobin's Q alleviate the negative equity market reactions to the proposal. This study shows how equity market participants react to more stringent ESG-related disclosure and how the response may relate to S&P 500 firms’ ESG performance, growth, and market performance.

We intend to show the directional volatility spillovers between the European short term interbank lending rates (3-month Euro Interbank Offered Rate [EURIBOR] and Euro Short-Term Rate [ESTR]) and the Hungarian Budapest Interbank Offered Rate (BUBOR) and Euro-Hungarian Forint exchange rate. To determine the extent to which the variables affect each other's volatilities we build a five-variable vector autoregression (VAR) and determine the spillover table like in Diebold-Yilmaz's 2012 work. This methodology is preferred to a simple impulse response function (IRF) because we manage to avoid the problem of non-orthogonal innovations via the generalized forecast error variance decomposition framework. The issue of variable ordering, therefore, does not arise. We focus on three episodes of increased volatility in Hungarian and European short-term interest rates: Q3–Q4 of 2019, Q1 of 2020 and Q3 of 2022. These episodes correspond to volatility spikes in EU markets that to some extent had a measurable spillover effect on Hungarian interbank rates. We find that on average, across the entire sample of 957 observations, about 6.3% of the volatility forecast error variance in all five European and Hungarian variables comes from spillovers. The total and directional spillovers over the sample are extremely low. We conclude that the European Central Bank's surprise policy decisions have a marginal impact on Hungarian interbank rates. We also find that BUBOR is primarily a net receiver of spillovers from the MAX short-term government bond benchmark rather than the EURIBOR—this disproved our initial considerations.

This study explores the relationship between financial reporting quality and insurer governance, with the hypothesis that robust governance procedures exert better control over managers’ opportunistic behavior. The analysis is based on a dataset of insurer firms from 2014 to 2021. The econometric results obtained using the two-step system GMM technique reveal that the overarching influence of corporate governance on enhancing financial reporting quality is evident, with board and risk governance matters the most. Among individual governance attributes, the optimal board size, a higher proportion of independent directors, audit and risk committees’ size, and risk committee independence play a significant role in governing discretionary accruals. The efficacy of governance mechanisms considerably differs across life and non-life insurers, shedding light on the nuanced dynamics within the Indian insurance market. The results lend empirical support to resource dependency and agency theories within the Indian insurance sector. The implications suggest potential avenues for amending or redesigning governance norms with specificities of insurers and the ultimate goal of fostering an environment conducive to enhancing the reporting quality of Indian insurance firms.

Using a dataset comprised of US publicly traded firms from 2002 to 2018, this paper reveals a significantly negative relationship between social capital and stock price crash risk. Firms located in regions with higher levels of social capital tend to have lower stock price crash risk. This result holds after addressing potential endogeneity. The negative association is more prominent for firms located in rural areas, with greater R&D expenditure, with higher default risk, and during the time periods of non-financial crisis, respectively. The results of this study are robust to alternative measurements of stock price crash risk, index interpolation, index aggregation, and additional controls.

This study examines the effects of corporate governance (CG) on investment inefficiency for 506 Indian listed firms. Using new stipulations of CG and globally recognized governance practices, an overall corporate governance index (CGI) and five sub-indices such as board index (BINDEX), audit index (AINDEX), ownership index (OINDEX), nomination and remuneration index (NRINDEX), and disclosure index (DINDEX) were constructed. Employing newly developed governance indices along with firm-specific control variables, several pooled regression models were estimated. Robustness checks were conducted using two-step system GMM and an alternate measure of managerial investment efficiency. The pooled estimated coefficient of CGI and sub-indices (except OINDEX) on investment inefficiency, overinvestment and underinvest is found to be negative and significant suggesting that effective/robust governance at firm level reduces investment inefficiencies (improves investment efficiency) through effective supervision and monitoring thereby reducing the opportunistic behavior of managers.

Value driver trees (VDTs) are abstract, indicator-based representations of a business model. Although they are conceptual models by nature, no systematic and unified approaches to their modeling exist to date. In fact, a heterogeneous understanding of their conception and methodological implementation has been established. The goal of this study is to provide more clarity in this regard by examining the semantics (the question of “what?”) and syntax (the question of “how?”) with respect to VDT modeling. For this purpose, a structured literature review was conducted in which a collection of 161 VDTs was evaluated. Based on an extended taxonomy design process, the typical model constructs of VDTs were extracted. As a result, a so-called VDT Model Classification was derived, which structures 34 model constructs into three dimensions with eight categories. This classification establishes a clearer understanding of the model constructs and their representation, thereby providing a conceptual framework for a unified and more substantiated “vocabulary” for VDT modeling. Finally, a research agenda has been formulated that generally addresses the role and future application potential of VDTs and, in particular, describes the next steps toward a sound notation for modeling VDTs.

Retraction: Ding, H. (2024). International expansion and audit opinion shopping: A signaling perspective. The Journal of Corporate Accounting & Finance. https://doi.org/10.1002/jcaf.22700

The above article, published online on 14 February 2024 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the author, journal Editor-in-Chief Damir Tokic and Wiley Periodicals LLC. The retraction has been agreed following a report by the authors that confirmed methodological errors which produced incorrect regression results in the published article. Because the errors affect the full empirical tables, the results are fundamentally impacted, and the author and Editor-in-Chief agree that the article must be retracted.