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Extreme climate events (ECEs) like heavy rainfall and heatwaves significantly impact society, and climate change is altering their magnitude and frequency. Generalized Extreme Value (GEV) distributions help quantify these ECEs and guide human system design. We train a machine learning (ML) model using a set of arbitrary GEV distributions to estimate the sample size required to determine a return value with specific uncertainty. For ECEs like heatwaves with a negative GEV shape parameter the maximum extreme temperatures of heatwaves are bounded and fewer samples are needed to estimate the return value to given uncertainty than rainfall extremes which have positive shape parameter with unbounded extreme values. For example, if a 1‐in‐20‐year heatwave event requires 400 samples to estimate return value to ±$\\pm $ 1% uncertainty, one would need 20 different 20‐year simulations. Achieving such quantities will require extensive climate downscaling simulations, potentially aided by ML‐based downscaling methods to increase the ensemble size. Plain Language Summary Generalized Extreme Value (GEV) distribution is a common way to characterize extreme climate events from climate data sets. We develop a machine learning model to estimate the sample size required to determine a return value to a prescribed uncertainty for an arbitrary set of GEV parameters. For the expected GEV parameters relevant to climate variables, the number of years needed to quantify the annual return value of low probability events (e.g., a 1 in 100‐year event) can easily exceed 1000s of years of simulations to get sufficiently accurate estimates of the return value to differentiate it from a more likely event (e.g., 1 in 50‐year event). By knowing the sample size, one can start to design climate change simulation experiments with sufficient simulated years to detect how annual return values are changing with climate change. Key Points Generalized extreme value (GEV) distributions are a common way to characterize extreme climate events in climate data sets We develop a machine learning model to quantify the sample size needed to estimate return value of GEV distribution to specific uncertainty Knowing how return values are influenced by sample size will help to design experiments to attribute climate change impacts on extreme events

Purpose The purpose of this paper is to analyze the relationship between firms’ intellectual capital (IC), financial performance (FP) and market value (MV) as well as the relationship between ownership concentrations on IC performance. Design/methodology/approach A large sample of non-financial listed firms belonging to 14 countries in Western Europe, for the period between 2004 and 2015, was investigated using the GMM system (1998) dynamic estimator and the effect of lagged explanatory variables on firm’s FP and MV. Findings The results reveal that IC is an important resource for firms’ value creation. Human capital is found to be a key factor of firms’ wealth. Results show that capital employed efficiency positively impacts on firms’ FP in the short run. The impact of IC components on firms’ MV may not be immediate. The structural capital positively affects firms’ FP in the long run. Also, the results reveal that ownership concentration and owners’ management involvement constrain firms’ IC performance. Originality/value The current study contributes to IC research by exploring a large sample of firms across countries in Western Europe using econometric modeling. Considering that the effect of IC on firms’ FP needs time to be realized, thus to be measured, the effect of lagged explanatory variables on performance was tested, using dynamic panel estimators, specifically the GMM system (1998) dynamic estimator.

Standard-setters worldwide have passed new audit reporting requirements aimed at making audit reports more informative to investors. In the UK, the new standard expands the audit reporting model by requiring auditors to disclose the risks of material misstatement (RMMs) that had the greatest effect on the financial statement audit. Using short window tests, prior research indicates that these disclosures are not incrementally informative to investors (Gutierrez et al. in Review of Accounting Studies 23:1543–1587, 2018). In this study, we investigate three potential explanations for why investors do not find the additional auditor risk disclosures to be informative. First, using long-window tests, we find no evidence that the insignificant short-window market reactions are due to a delayed investor reaction to RMMs. Second, using value relevance tests, we show that the insignificant market reactions are not due to auditors disclosing irrelevant information. Finally, we provide evidence suggesting that RMMs lack information content because investors were already informed about the financial reporting risks before auditors began disclosing them in expanded audit reports.

The past performance and the capital structure of the companies that are involved in mergers and acquisition (M&As) are considered into the analysis of the circular causality relationship between financial performance and market value. Considering two models, one for value relevance and one for accounting conservatism, this paper aims to analyze if the capital market influences the accounting practices of a target company or that the accounting figures influence the capital market. The analyzed sample used in the study is represented by the target companies involved in M&As which took place in the European Union Enlarged in 2017–2018. Financial and market data were considered for eight years (2011–2018). Using the conservatism model, the results show that targets’ earnings are significantly influenced by their financial leverage as an indicator for financial structure. Using the value relevance model, the capital market reaction is influenced by prices and return on equity that indicates the capital market influence on accounting figures.

Purpose - The purpose of this study is to investigate empirically the relationship between intellectual capital and financial performance of 65 Indian banks for a period of ten years from 1999 to 2008.Design methodology approach - Reserve Bank of India's database and Annual reports, especially the profit and loss accounts and balance sheets of the banks for the relevant years have been used to obtain the data. Value added intellectual coefficient (VAIC™) method is applied for measuring the value based performance of banks. Return on assets (ROA) and return on equity (ROE) are used to measure the profitability and productivity of Indian banks, measured by assets turnover ratio (ATO). The intellectual capital (human capital and structural capital) and physical capital of selected banks have been analyzed and their impact on corporate performance has been measured using multiple regression technique.Findings - The analysis indicates that the relationships between the performance of a bank's intellectual capital, and financial performance indicators, namely profitability and productivity, are varied. The study results suggest that banks' intellectual capital is vital for their competitive advantage.Research limitations implications - The study uses only 65 leading Indian banks, including foreign banks operating in India. The value added intellectual coefficient (VAIC™), introduced by Pulic, is used in this study as a basic methodology to measure the IC performance of banks.Practical implications - The VAIC™ method can be used as an important tool by the decision makers in the knowledge economy to integrate the intellectual capital in the decision making process.Originality value - This is one of the first empirical researches in India that examines the impact of IC on financial performance of the Indian banking sector in the long term.

This paper investigates whether improvements in the firm's internal corporate governance create value for shareholders. We analyze the market reaction to governance proposals that pass or fail by a small margin of votes in annual meetings. This provides a clean causal estimate that deals with the endogeneity of internal governance rules. We find that passing a proposal leads to significant positive abnormal returns. Adopting one governance proposal increases shareholder value by 2.8%. The market reaction is larger in firms with more antitakeover provisions, higher institutional ownership, and stronger investor activism for proposals sponsored by institutions. In addition, we find that acquisitions and capital expenditures decline and long-term performance improves.

We analyze the relationship between corporate social responsibility and the stock market performance in the post-global financial crisis period. A new measure of social responsibility by Thomson Reuters, called the ESG Combined Score, is used. As a novel feature of our analysis, socially responsible engagement is divided into the strategic activities closely related to the examined companies’ core business and the remaining secondary activities. The results of the fixed effects regression show a positive and statistically, as well as economically, significant impact of the strategic activities on the corporate stock market performance of companies. This impact is up to 103% higher compared to the secondary activities. The empirical results suggest that if companies aim to increase their share prices via the corporate social responsibility channel, they should strategically select their socially responsible initiatives.

We examine the association between changes in companies’ textual risk disclosures in 10-K filings and changes in stock market and analyst activity around the filings. We find that annual increases in risk disclosures are associated with increased stock return volatility and trading volume around and after the filings. Increases in risk disclosures are also associated with more dispersed forecast revisions around the filings. In contrast to prior literature documenting resolved uncertainties in response to various types of company disclosures, our findings suggest that textual risk disclosures increase investors’ risk perceptions. However, the results are less pronounced for firm-level disclosures that deviate from those of other companies in the same industry and year. These results lend support for critics’ arguments that firm-level risk disclosures are more likely to be boilerplate.

Purpose>This paper aims to investigate if and to what extent environmental, social and governance (ESG) practices are influenced by innovation, measured by investment in research and development (R&D) and the number of patents developed by companies.Design/methodology/approach>To test this hypothesis, the authors estimated a regression model for the panel data considering a time horizon of eight years. The analysis was conducted on a sample of listed firms operating in the industrial sector in France, Germany, Italy, Spain, the UK and the USA.Findings>The empirical analysis shows that there is a positive and significant relationship between ESG practices and innovation. Companies investing more in R&D and patents have better ESG performance.Originality/value>This study contributes to the existing literature by improving the understanding of the importance of innovation in improving ESG practices for firms in the industrial sector. Furthermore, it provides empirical evidence of the ability of innovation to be a valuable tool for sustainable industry development through R&D investment and patent development.

Purpose The purpose of this paper is to examine the factors affecting profitability in Malaysian-listed companies. It has been argued that profitability is the main pillar for any company to survive in the long run. Although profitability is the primary goal of all business ventures, scant attention has been paid to the factors that affect profitability in developing countries. This study investigates the factors affecting profitability in Malaysian-listed companies. Design/methodology/approach This research is based on five independent variables that were empirically examined for their relationship with profitability. These variables are: firm size (as measured by total sales), working capital (WC), company efficiency (assets turnover ratio), liquidity (current ratio) and leverage (debt equity ratio and leverage ratio). Data of 120 companies listed on Bursa Malaysia covering the period from 2012 to 2014 were extracted from companies’ annual reports. Pooled ordinary least squares regression and fixed-effects were used to analyze the data. Findings The findings show a strong positive relationship between firm size (total sales), WC, company efficiency (assets turnover ratio) and profitability. The results also show a negative relationship between both debt equity ratio and leverage ratio and profitability. Liquidity (current ratio) has no significant relationship with profitability. Research limitations/implications Due to the time limitation, the data includes only 120 companies listed in bursa Malaysia and covers the period from 2012 to 2014. Practical implications These results benefit internal users (such as mangers, shareholders and employees). They can realize the determinants of enhancing the profitability of their company after the depreciation of the Malaysian currency and therefore concentrate more on the factors that enhance their companies’ profitability. On the other side, other external users (such as investors, creditors, new established companies, tax authority) also may get advantages of these results. It is clear that those users concern about the profitability of companies and the determinants of their profitability after the currency’s depreciation. Originality/value This study differs than previous studies in many ways: first, it focuses on non-financial listed companies in Malaysia. Previous studies have concentrated on companies in the financial sector, such as banking and financial institutions or on industrial organizations. Second, this study analyzes the data in companies’ annual reports for a three-year period from 2012 to 2014. During this period, the economy in Malaysia was fluctuating due to currency depreciation. Third, the study used both return on equity and earnings per share as indicators of profitability. Fourth, the results of the study provide empirical evidence that large size firms with efficiently managed assets can improve operating income and ultimately enhance profitability. Last but not least, this study applies the resource-based theory and the trade-off theory.