This paper aims to test the hypothesis that higher ESG scores lead to a lower cost of capital for publicly traded companies in Eastern Europe. In recent years, ESG factors have become increasingly important in the investment industry, influencing the cost of capital for publicly traded companies from banking industry. As companies seeking capital are increasingly scrutinized based on ESG factors, most publicly traded companies publish ESG disclosures and strive to be ESG compliant. Although there is no definitive governing body for ESG, capital providers benchmark companies based on ESG scores—either internally created or from external providers—and integrate these scores into their investment decisions. With cost of capital on the rise during previous period, the authors want to test the hypothesis that ESG score have positive influence on the cost of capital for public companies in banking industry, with lower cost of capital compared to their peers. Using the Weighted Average Cost of Capital (WACC), this paper breaks down the cost of capital to test the effect of ESG scores on both the cost of debt and the cost of equity for publicly traded banking corporations from Eastern Europe.

The growth in electricity demand driven by artificial intelligence and digital infrastructure is directing attention toward nuclear energy as a stable source. The sector has been transformed by the emergence of SMRs and the growing number of publicly listed developers. The aim of this paper is to investigate whether the stock returns of publicly listed SMR companies are more closely associated with the AI-related equity benchmark or with the energy commodity benchmark. Due to the absence of a unified SMRs index, a market-capitalization-weighted synthetic NUC index was constructed from Oklo Inc., NuScale Power Corporation, and NANO Nuclear Energy Inc. for the period from 1 July 2024 to 1 July 2026. The Global X Artificial Intelligence & Technology ETF (AIQ) and The S&P GSCI Energy Spot Index represented the AI-related equity and energy commodity benchmarks, respectively. The relationships were examined using correlation and regression analyses with Newey–West HAC standard errors, based on 501 daily logarithmic returns. NUC increased by 166.80%, versus 77.79% for AIQ and −7.68% for the energy benchmark. Correlations were 0.510 (p < 0.001) with AIQ and −0.059 (p = 0.186) with the energy benchmark; standardized coefficients were 0.509 and −0.046, respectively, differing significantly (one-sided p < 0.001).