Burak Doğan

This paper studies how artificial-intelligence (AI) disclosure in the Item 1A risk factors of S&P 500 10-K filings evolved between fiscal years 2015 and 2025. It asks three questions: when AI disclosure became common in Item 1A; whether firm characteristics explain which firms disclose and whether that power changes as disclosure spreads; and whether firms that write more AI text write less firm-specific AI language. The data are a panel of 5214 firm-years for the 501 firms in the S&P 500 as of April 2026, so the sample is subject to survivor bias; the coverage gap relative to the historical index is about 38% in 2015 and falls to 2% by 2025. AI mentions come from a hand-validated keyword dictionary, and a lexical distinctiveness score measures how far a firm’s AI wording departs from that of its peers in the same year; the score captures wording, not informational content or quality. Three results follow. First, the share of firms disclosing AI in Item 1A rises from 0.7% to 77.6%, with the largest jump in the first filing cycle after the November 2022 release of ChatGPT. Second, the power of firm characteristics to discriminate disclosers falls as disclosure saturates: the disclosure logit’s pseudo-R² drops from 0.24 to 0.03 and the area under the ROC curve from 0.86 to 0.61. Third, among disclosing firm-years, more AI text is associated with lower lexical distinctiveness. These associations are descriptive; this paper does not test causal mechanisms.

This paper compares the rulebooks of five main Shariah-compliant equity indices—DJIMI, KLSI, FTSE Shariah, MSCI Islamic, and STOXX Europe Islamic 50—inside one fixed S&P 500 stock list from Q1 2019 to Q4 2023. For each index, we build both equally weighted and market-capitalization-weighted portfolios, then check their performances with the Sharpe, Treynor, and Jensen’s alpha ratios. All Islamic portfolios beat the regular S&P 500 after adjusting for risk, with STOXX as the most stable winner. Its market-cap version reaches a level of 253.01 by Q4 2023, far above the S&P 500 level of 210.46. Market-cap portfolios, in general, perform better than equally weighted ones. Furthermore, STOXX offer better protection in rough markets, while DJIMI shows relatively better performance when prices recover. Most rule sets cause small advantages to the Islamic portfolios compared to conventional ones, but STOXX’s 33% limit on leverage and liquidity results in higher Sharpe ratios. These results suggest that screening details shape portfolio behavior and point to the need for one clear, shared Shariah rulebook so investors can compare products with confidence. From a business ethics view, our study also shows that strict and open screening brings a real “moral dividend”, as follows: smaller losses when markets fall and stronger risk-adjusted returns overall, linking faith-based rules to the wider talk on responsible investing and stakeholder welfare.

Boycott movements, initially driven by individual consumer choices in response to Israel's ongoing actions in Gaza, have evolved into potent...

İsrail’in Filistin’de sürdürdüğü işgal politikalarına karşı yükselen boykot hareketleri, bireysel bir tüketim tercihi olmanın ötesinde, ...

This study investigates the financial performance of target companies involved in mergers and acquisitions (M&As), aiming to reveal the dynamics affecting these organizations pre- and post-transaction. Utilizing a comprehensive dataset, we analyze the financial outcomes of M&A deals globally, spanning from 2010 to 2019. Employing various financial ratios, such as liquidity ratios, profitability measures, leverage ratios, asset management ratios, and market valuation metrics, this research provides an understanding of how M&As influence the financial performance of target companies. The key findings suggest that target companies experience significant changes in their financial ratios post-acquisition, with liquidity and profitability ratios showing marked fluctuations. The study shows that the method of payment (cash vs. non-cash) and the size of the deal significantly influence the post-acquisition financial performance of target companies. Cash-based and lower-valued deals are found to have a more positive impact on financial stability and growth metrics. This research contributes to the existing body of knowledge by highlighting the marginal effects of acquisition strategies on target companies’ financial performance. Our findings provide practical insights for potential acquirers, suggesting that the choice of acquisition method and deal size can significantly affect the financial outcomes of M&A activities.

This study examines the interactions among economic growth, technological innovation, renewable energy consumption, and carbon emissions in Africa using advanced econometric methods. Panel data analysis reveals both symmetric and asymmetric impacts on carbon emissions, showing how economic and technological variables contribute to environmental outcomes. The augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators address cross-sectional dependence and heterogeneity, ensuring robust results. Findings indicate that positive economic growth increases emissions, while economic downturns significantly reduce emissions. The study underscores the need for strategic policies that leverage technological innovations and renewable energy to promote sustainable development in African economies, balancing economic growth with environmental protection.