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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.

This study’s goal was to identify how several markets have developed over time and what determinants have influenced this process, based on adaptive markets hypothesis (AMH). In this regard, the authors consider that agents are driven by the seeking for abnormal returns to stay “alive” and their environment could somehow modify their decision-making processes, as well as influence the degree of efficiency of the market.

The authors collected the daily closing-of-the-market index from 50 countries, between 1990 and 2022. The sample includes emerging countries, developed countries and frontier markets. Then, the authors ran multilevel modeling using Hurst exponent as an informational efficiency metric estimated by two different moving windows: 500 and 1,250 observations (approximately 2 and 5 years).

The results indicate that the efficiency of the markets is not constant over time. The authors also have identified that markets follow a cyclical pattern of efficiency/inefficiency, and they are currently in a period of convergence to efficiency, possibly explained by the increase in computational capacity and speed of the available information to agents. In addition, this study identified that country characteristics are associated with market efficiency, considering institutional factors.

Studies of this nature contribute to the literature, considering the importance of better comprehension of market efficiency dynamics and their determinants, specially observing other theories on the relationship between information and markets (like AMH), which work with other investor assumptions than those used by efficient market hypothesis.

This study analyzes the impact of the information environment (IE) and credit default swap (CDS) transaction costs on information transmission between the stock and CDS markets. Using the daily regression analysis on the Korean firm’s stock and CDS data from 2004 to 2023, the results show that companies with superior IE in the stock market exhibit a larger and more sensitive total information flow from the stock market to the CDS market. Companies with lower transaction costs in the CDS market demonstrate faster information flow. In the case of companies with superior IE, fundamental information is reflected in stock prices with high weight and thus the CDS spreads change reflecting information about stock prices. According to this study’s findings, the primary factor influencing the information flow from the stock market to the CDS market is the information environment of the company in the stock market, rather than transaction costs in the CDS market.

The authors examine the role of analysts’ prior experience of forecasting for firms exposed to epidemics on analysts’ forecast accuracy during the COVID-19 pandemic.

The authors examine the impact of analysts’ prior epidemic experience on forecast accuracy by comparing the changes from the pre-COVID-19 period (calendar year 2019) to the post-COVID period extending up to March 2023 across HRE versus non-HRE analysts. The authors consider a full sample (194,980) and a sub-sample (136,836) approach to distinguish “Recent” forecasts from “All” forecasts (including revisions).

The study's findings reveal that forecast accuracy for HRE analysts is significantly higher than that for non-HRE analysts during COVID-19. Specifically, forecast errors significantly decrease by 0.6% and 0.15% for the “Recent” and “All” forecast samples, respectively. This finding suggests that analysts’ prior epidemic experience leads to an enhanced ability to assess the uncertainty around the epidemic, thereby translating to higher forecast accuracy.

The finding that the expertise developed through an experience of following high-risk firms in the past enhances analysts’ performance during the pandemic sheds light on a key differentiator that partially explains the systematic difference in performance across analysts. The authors also show that industry experience alone is not useful in improving forecast accuracy during a pandemic – prior experience of tracking firms during epidemics adds incremental accuracy to analysts’ forecasts during pandemics such as COVID-19.

The study findings should prompt macroeconomic policymakers at the national level, such as the central banks of countries, to include past epidemic experiences as a key determinant when forecasting the economic outlook and making policy-related decisions. Moreover, practitioners and advisory firms can improve the earning prediction models by placing more weight on pandemic-adjusted forecasts made by analysts with past epidemic experience.

The uncertainty induced by the COVID-19 pandemic increases uncertainty in global financial markets. Under such circumstances, the importance of analysts’ role as information intermediaries gains even more importance. This raises the question of what determines analysts’ forecast accuracy during the COVID-19 pandemic. Building upon prior literature on the role of analyst experience in shaping analysts’ forecasts, the authors examine whether experience in tracking firms exposed to prior epidemics allows analysts to forecast more accurately during COVID-19. The authors find that analysts who have experience in forecasting for firms with high exposure to epidemics (H1N1, Zika, Ebola, and SARS) exhibit higher accuracy than analysts who lack such experience. Further, this effect of experience on forecast accuracy is more pronounced while forecasting for firms with higher exposure to the risk of COVID-19 and for firms with a poor ex-ante informational environment.

The purpose of this paper is to investigate whether Islamic stock indexes outperform conventional stock indexes, in terms of informational efficiency and risk, during the recent financial instability period.

The paper uses a state space model combined with a standard GARCH(1,1) specification while taking into account structural breakpoints. The authors allow for efficiency and volatility spillovers to be time-varying and consider break dates to locate periods of financial instability.

Empirical results show that Islamic stock indexes are more volatile than their conventional counterparts and are not totally immune to the global financial crisis. As regards of the informational efficiency, the results show that the Islamic stock indexes are more efficient than the conventional stock indexes.

Resulting evidence of this paper has several implications for international investors who wish to invest in Islamic and/or conventional stock markets. Policy makers and even academics and Sharias researchers should as well take preventive measures in order to ensure the stability of Islamic stock markets during turmoil periods. Overall, prudent risk management and precocious financial practices are relevant and crucial for both Islamic and conventional financial markets.

The originality of this study is performed by the use of time-varying models for volatility spillovers and informational efficiency. It considers structural break dates that think about the dynamic effect of informational flows on stock markets. The study was developed in a global framework using international data. The global analysis allows avoiding country specific effects.

The purpose of this paper is to explore two distinct subsets of dynamic capabilities that need to be deployed when pursuing innovation through inter-organizational activities, respectively, in the contexts of broad networks and specific alliances. The authors draw distinctions and explore potential interdependencies between these two dynamic capability reservoirs, by integrating concepts from the theoretical perspectives they are derived from, but which have until now largely ignored each other – the social network perspective and the dynamic capabilities view.

The authors investigate nanotechnology-driven R&D activities in the 1995–2005 period for 76 publicly traded firms in the electronics and electrical equipment industry and in the chemicals and pharmaceuticals industry, that applied for 580 nanotechnology-related patents and engaged in 2,459 alliances during the observation period. The authors used zero-truncated Poisson regression as the estimation method.

The findings support conceptualizing dynamic capabilities as four distinct subsets, deployed for sensing or seizing purposes, and across the two different inter-organizational contexts. The findings also suggest potential synergies between these subsets of dynamic capabilities, with two subsets being more macro-oriented (i.e. sensing and seizing opportunities within networks) and the two other ones more micro-oriented (i.e. sensing and seizing opportunities within specific alliances).

The authors show that firms differ in their subsets of dynamic capabilities for pursuing different types of inter-organizational, boundary-spanning relationships (such as alliances vs broader network relationships), which ultimately affects their innovation performance.

The authors contribute to the growing body of work on dynamic capabilities and firm-specific advantages by unbundling the dynamic capability subsets, and investigating their complex interdependencies for managing different types of inter-organizational linkages. The main new insight is that the “linear model” of generating more innovations through higher inter-firm collaboration in an emerging field paints an erroneous picture of how high innovation performance is actually achieved.

This study aims to examine the relationship between corporate governance mechanisms and the capital structure of Latin American firms.

The sample included companies from Argentina, Brazil, Chile, Colombia, Mexico and Peru. The authors collected data from 201 non-financial companies between 2009 and 2018, totalizing 1,716 firm-year observations. The data were analyzed using descriptive statistics and linear regression models with panel data.

The main results indicated that chief executive officer duality, legal protection system and corporate social responsibility voluntary disclosure impact the firm's total debt ratio, corresponding to a positive effect for the first two variables and a negative for the last.

This study advances in two main ways. Firstly, due to the broad approach in which the authors addressed corporate governance, involving board composition, ownership structure, minority shareholders legal protection system and information disclosure. Secondly, by presenting empirical evidence about the effects of corporate governance on capital structure from an extensive sample of Latin American firms, the authors expect to contribute to the international debate on the capital structure due to the unique characteristics of Latin America in this regard.

The purpose of this paper is to test an implication of the pecking order theory to explain capital structure decisions among Chinese listed companies during the 2005-2007 NTS Reform transition period.

The authors utilize direct proxies for information asymmetry based on microstructure models including Probability of the arrival of informed trades (PIN), Adverse selection component of the bid-ask spread (λ), Illiquidity ratio (ILLIQ) and liquidity ratio, and Information asymmetry index (InfoAsy) to examine their relation with firms’ debt financing.

Consistent with the prediction of Pecking Order Theory, the authors find that companies for which stock investors are challenged with more severe informational disadvantages are associated with higher degree of leverage use.

The study provides a more direct test on the positive relation between information asymmetry and financial leverage of Chinese firms. In contrast to previous findings by Chen (2004), the results suggest that capital structure choices among Chinese firms progressively conform to conventional finance theories (e.g. Pecking Order Theory) with the decline of non-tradable shares.

The aim of the paper is to investigate the associations between hedge fund activism and corporate internal control weaknesses.

In this paper, the authors identify hedge fund activism events using 13D filings and news search. After matching with internal control related information from Audit Analytics, the authors utilize ordinary least square (OLS) and propensity score matching (PSM) to analyze the data.

The authors find that after hedge fund activism, target firms report additional internal control weaknesses, and these identified internal control weaknesses are remediated in subsequent years, leading to better financial-reporting quality.

The findings indicate that both managers and activists have incentives to develop a stronger internal control environment after targeting.