CFA Institute Updated Sustainable-Investing Exam Questions and Answers by harris

Exclusion policies in responsible investment typically focus on specific asset classes, such as listed equities and corporate debt, where investors can directly apply ethical and ESG criteria to exclude certain companies or sectors from their portfolios. Indices, however, fall outside of this traditional spectrum as they represent broader market benchmarks.

Exclusion Policies: These policies are applied to directly exclude investments in certain sectors or companies that do not meet the ethical or ESG criteria set by the investor. Common exclusions include tobacco, firearms, and fossil fuels​​​​.

Indices: Indices are used to benchmark the performance of portfolios and are typically not subject to exclusion policies. They represent a broad market or sector and include a range of companies regardless of their ESG performance. While ESG indices do exist, traditional exclusion policies do not typically apply to standard market indices​​​​.

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Formal corporate governance codes are now found in all major world markets. These codes establish guidelines and best practices for corporate governance, aiming to enhance transparency, accountability, and overall governance standards within companies. While the specifics can vary by country, the presence of these codes globally reflects a widespread commitment to improving corporate governance​​​​​​.

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ESG tilting is an investment approach applicable when investing in sovereign debt. It involves adjusting the weightings of sovereign bonds in a portfolio based on ESG scores, thereby favoring countries with better ESG performance. This method aligns investment decisions with ESG criteria while maintaining diversification and managing risk within sovereign bond portfolios​​​​.

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Natural Language Processing (NLP) is a tool used in ESG investing to analyze and quantify large amounts of textual data related to environmental, social, and governance (ESG) factors. The technology involves the automatic manipulation of natural language by software, enabling the extraction of meaningful information from unstructured text such as news articles, reports, and social media posts.

NLP in ESG Investing: NLP helps investors process and analyze large volumes of textual data to identify trends, risks, and opportunities associated with ESG factors. This capability is crucial for assessing the sentiment and context of ESG-related information, which can impact investment decisions​​​​.

Quantifying Online Text: NLP quantifies online text by identifying and categorizing relevant ESG risk areas. This includes monitoring media sources, regulatory filings, and corporate disclosures to capture real-time data on ESG issues. By quantifying these texts, investors can better understand the potential impact of ESG risks on their investments​​​​.

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