In today’s dynamic financial landscape, the integration of environmental, social, and governance (ESG) principles into investment strategies has gained great significance. Investors and financial advisors are increasingly confronted with the crucial question of whether their dedication to ESG values enhances or hampers their pursuit of financial performance. Addressing this crucial issue, our research delves into the impact of ESG ratings on financial performance, exploring a cutting-edge machine learning approach powered by the Extreme Gradient algorithm. Our study centers on US-registered equity funds with a global investment scope, and performs a cross-sectional data analysis for annualized fund returns for a five-year period (2017–2021). To fortify our analysis, we synergistically amalgamate data from three prominent mutual fund databases, thereby bolstering data completeness, accuracy, and consistency. Through thorough examination, our findings substantiate the positive correlation between ESG ratings and fund performance. In fact, our investigation identifies ESG score as one of the dominant variables, ranking among the top five with the highest predictive capacity for mutual fund performance. As sustainable investing continues to ascend as a central force within financial markets, our study underscores the pivotal role that ESG factors play in shaping investment outcomes. Our research provides socially responsible investors and financial advisors with valuable insights, empowering them to make informed decisions that align their financial objectives with their commitment to ESG values.

The recent financial crisis shows that failure of some financial institutions can cause other banks to fail and ultimately cause damage to the financial system worldwide. Eurozone banks that experienced either liquidity or solvency problems during the financial markets turmoil were bailed out by their national governments with the financial support and supervision of the European Union. This paper applies the boosted classification tree methodology to predict failure in the banking sector and identifies four key scorecard variables that are worth tracking closely in order to anticipate and prevent bank financial distress. The data used in this study comprises 2006–2012 annual series of 25 financial ratios of 155 banks in the Eurozone. The findings indicate that the greater the size and the higher the income from non-operating items and net loans to deposits, the more likely is bank failure; conversely, the higher the Interbank ratio the lower the chances of bank financial distress. For the sake of their own financial soundness, banks should fund lending activities through clients’ deposits and should avoid relying excessively on non-recurring sources of income.

Purpose: – The purpose of this paper is to explore whether the provision of non-audit services (NAS) by public accounting firms undermines audit quality. The study addresses this question by testing for an association between the provision of consulting services and auditor independence in listed companies. Design/methodology/approach: – The authors study if the magnitude of non-audit fees explains variations in earnings management by looking at the joint determination of non-audit fees, audit fees, and abnormal accruals using the SURE-regression estimation method. Findings: – Evidence from tested models suggests that audit services quality is uncompromised by the provision of NAS. In other words, high non-audit fees do not necessarily result in poor quality financial reporting. Research limitations/implications: – A different research methodology and a different sample (e.g. non-listed companies) may lead to differing results. As the paper analyses only one country, generalizability of the results might be a limitation. There is no need to increase legal restrictions on the provision of consulting services by public accounting firms in order to better safeguard audit quality. Practical implications: – Consulting clients may be more confident to hire both audit and NAS with the same firm and can make a case before the general Shareholders’ meeting. By providing both audit and NAS, consulting firms obtain knowledge spillovers and synergies while appealing highly qualified professionals. Originality/value: – The use of simultaneous equations (SURE-regression) to establish the auditor-client relation allows us to better model theoretical relations between audit fees, non-audit fees, and abnormal accruals. Likewise, joint modeling takes account of correlations between the error terms of the individual models, yielding more efficient estimates than ordinary least squares. Performing this analysis in a non-Anglo-American country with low litigation risk is also a valuable contribution to extant literature.

Innovation is an important driver of economic growth for it leads to new products and services, enhanced quality, and lower prices. In an increasingly competitive global market, innovation turns out to be essential to secure a viable competitive position. Although there is no perfect correspondence between accounting intangible assets and innovation activities, the association between these two concepts is close enough to take investment in intangible assets as a proxy for entrepreneurship and innovation. To identify differences between innovative and non‐innovative small and medium enterprises in the service industry, both descriptive and statistical analyses are performed on financial data for the period 2007–2009. The results obtained show that, although with some exceptions, innovative firms generally have better economic and financial performance than non‐innovative companies.

Past financial crises have illustrated the importance of recognising the combinations of factors that can cause financial distress in the banking industry. Accordingly, this study uses fuzzy-set qualitative comparative analysis (fsQCA) to identify the combinations of factors that lead to bank failure. The data consist of 30 annual financial ratio series for 156 U.S. banks over a 15-year period (2001–2015). Identifying combinations of conditions that can produce bank failure is crucial to help regulators and bank managers. The fsQCA presented in this paper sheds light on the relationships between combinations of conditions and bank failure, providing a solution comprising two sufficient and disjunctive sets of conditions that lead to bank failure. This solution includes financial indicators of performance, asset quality, efficiency and capitalisation. The robustness of the two sets of conditions is assessed using several tests.