ESG Ratings

Quantum computing approach to realistic ESG-friendly stock portfolios ArXiv ID: 2404.02582 “View on arXiv” Authors: Unknown Abstract Finding an optimal balance between risk and returns in investment portfolios is a central challenge in quantitative finance, often addressed through Markowitz portfolio theory (MPT). While traditional portfolio optimization is carried out in a continuous fashion, as if stocks could be bought in fractional increments, practical implementations often resort to approximations, as fractional stocks are typically not tradeable. While these approximations are effective for large investment budgets, they deteriorate as budgets decrease. To alleviate this issue, a discrete Markowitz portfolio theory (DMPT) with finite budgets and integer stock weights can be formulated, but results in a non-polynomial (NP)-hard problem. Recent progress in quantum processing units (QPUs), including quantum annealers, makes solving DMPT problems feasible. Our study explores portfolio optimization on quantum annealers, establishing a mapping between continuous and discrete Markowitz portfolio theories. We find that correctly normalized discrete portfolios converge to continuous solutions as budgets increase. Our DMPT implementation provides efficient frontier solutions, outperforming traditional rounding methods, even for moderate budgets. Responding to the demand for environmentally and socially responsible investments, we enhance our discrete portfolio optimization with ESG (environmental, social, governance) ratings for EURO STOXX 50 index stocks. We introduce a utility function incorporating ESG ratings to balance risk, return, and ESG-friendliness, and discuss implications for ESG-aware investors. ...

Green portfolio optimization: A scenario analysis and stress testing based novel approach for sustainable investing in the paradigm Indian markets ArXiv ID: 2305.16712 “View on arXiv” Authors: Unknown Abstract In this article, we present a novel approach for the construction of an environment-friendly green portfolio using the ESG ratings, and application of the modern portfolio theory to present what we call as the ``green efficient frontier’’ (wherein the environmental score is included as a third dimension to the traditional mean-variance framework). Based on the prevailing action levels and policies, as well as additional market information, scenario analyses and stress testing are conducted to anticipate the future performance of the green portfolio in varying circumstances. The performance of the green portfolio is evaluated against the market returns in order to highlight the importance of sustainable investing and recognizing climate risk as a significant risk factor in financial analysis. ...

ESG Rating Disagreement and Stock Returns ArXiv ID: ssrn-3433728 “View on arXiv” Authors: Unknown Abstract Using ESG ratings from seven different data providers for a sample of S&P 500 firms between 2010 and 2017, we study the relation between ESG rating disagree Keywords: ESG Ratings, Corporate Governance, Sustainability Disclosure, Firm Performance, S&P 500 Complexity vs Empirical Score Math Complexity: 3.0/10 Empirical Rigor: 7.5/10 Quadrant: Street Traders Why: The paper relies heavily on empirical data analysis (correlations, panel regressions, firm characteristics) with a focus on backtest-ready financial metrics like stock returns and equity cost of capital, but the mathematical modeling is limited to standard econometric techniques without advanced theory or derivations. flowchart TD A["Research Goal: Impact of ESG Rating Disagreement<br>on Stock Returns for S&P 500 Firms"] --> B["Data Inputs<br>2010-2017, S&P 500, 7 ESG Providers"] B --> C["Methodology: Calculate ESG Disagreement<br>across providers"] C --> D["Methodology: Regression Analysis<br>ESG Disagreement vs. Stock Returns"] D --> E{"Key Findings"} E --> F["Higher ESG Disagreement<br>associated with Lower Stock Returns"] E --> G["Disagreement mediates<br>the ESG-Performance relationship"]