Xinxin Wang leads MSCI’s research on ESG and climate solutions for the Americas, focusing on applied research and thought leadership on ESG and climate investing. She has served on the MSCI Executive Diversity Council, cofounded the firm’s Asian Support Network and headed the Boston office. Xinxin’s prior experiences include Credit Suisse, the Federal Home Loan Bank of Chicago and Fannie Mae. Xinxin holds an MBA from the University of Chicago and graduated from Harvard Business School’s General Management Program. She is a CFA® charterholder and GARP-certified FRM®.
Research and Insights
Articles by Xinxin Wang
ESG Factor Returns: 2022 in Review5 mins read Blog | Mar 7, 2023 |
Our analysis of ESG factor performance in 2022 suggests that time horizons, as well as specific sectors and regions, may be significant in assessing the return characteristics of ESG portfolios.
Did Low-Carbon-Transition Strategies Differentiate Energy Companies?2 mins read Quick Take | Feb 2, 2023 |
While the energy crisis has boosted the energy sector overall, individual company performance has varied markedly. Our analysis shows that businesses with above-average strategies to manage a low-carbon transition outperformed.
Keeping Energy Exposure While Lowering Emissions4 mins read Blog | Oct 25, 2022 |
Could equity managers have maintained their energy exposure during the sector’s recent outperformance while also reducing carbon emissions? We find that they could have lowered emissions but with some trade-offs during our study period.
Despite Energy Outperformance, Climate Indexes Were Resilient6 mins read Blog | Oct 6, 2022 |
There have been several dynamics that have influenced climate-index performance in the third quarter and first nine months of 2022. We examine the impact of macroeconomic and financial conditions on risk, return and sectors.
An Artificial Intelligence-Based Industry Peer Grouping SystemResearch Report | Jul 15, 2022 |
In this article published in the Journal of Financial Data Science, coauthors from MSCI and MIT develop and describe a data-driven system using AI tools to capture market perception and, in turn, group companies into peer clusters.