SDG rating confusion illustration with picture from GoranH from pixabay

SDG rating confusion: Researchpost #152

SDG rating confusion: 13x new research on emissions, life expectancy, green bonds, physical risks and transition, environmental information, private equity ESG, SDG ratings, bond and equity factors, fraud, health-wealth relations, LLM financial analysts (# shows the number of full paper SSRN downloads as of Nov. 16th, 2023)

Ecological and social research (SDG rating confusion)

Too hot: The State of Climate Action: Major Course Correction Needed from +1.5% to −7% Annual Emissions by the World Economic Forum and The Boston Consulting Group as of November 2023: “As 1.5°C is slipping out of reach, achieving it now calls for a 7% annual emissions reduction, more than the climate reduction impact from COVID-19 and against the current trend of a 1.5% annual increase. … Only 35% of emissions are covered by a national net-zero commitment by 2050, and only 7% by countries that complement bold targets with ambitious policies. Fewer than 20% of the world’s top 1,000 companies have set 1.5°C science-based targets, and, based on the Net Zero Tracker, fewer than 10% also have comprehensive public transition plans. Technologies that are economically attractive now or will be in the near future can only achieve just over half of the emissions reductions needed to reach 1.5°C. … More than half of climate funding needs are still unmet, with critical gaps in early technologies and infrastructure particularly acute, and the climate funding gap twice as large in developing economies as in developed ones” (p. 4).

Longer lifes: The Long-run Effect of Air Pollution on Survival by Tatyana Deryugina and Julian Reif as of Nov. 13th, 2023 (#8): “We show that the short-run mortality effects of acute SO2 exposure can be decomposed into two distinct phenomena: mortality displacement, where exposure kills frail individuals with short counterfactual life expectancies, and accelerated aging, where mortality continues to increase after exposure has ceased. … we calculate that a permanent, ten percent decrease in air pollution exposure would improve life expectancy by 1.2–1.3 years … our estimates imply that value of reducing pollution exposure may be substantially larger than has previously been recognized“ (p. 37).

Responsible investing research (SDG rating confusion)

Green bond limits: Decoding Corporate Green Bonds: What Issuers Do With the Money and Their Real Impact by Yufeng Mao as of Nov. 8th, 2023 (#157): “This paper reveals a distinct motivation for issuing green bonds compared to conventional bonds. Proceeds from green bonds remain as cash for longer periods, largely owing to the time required to identify eligible projects. Contrary to the notion of fungibility, my results indicate that they neither lead to more new investments than conventional bonds nor are used in apparent green-washing. … firms issuing green bonds show improved environmental performance, particularly in the reduction of GHG intensity. However, this improvement appears not to stem from incremental green investments facilitated by green bonds but rather from issuers that would have pursued green initiatives regardless” (p. 44).

Physical risk costs: The cost of maladapted capital: Stock returns, physical climate risk and adaptation by Chiara Colesanti Senni and Skand Goel as of July 23rd, 2023 (#48): “Using S&P Global Sustainable data on Physical Risk and measures of adaptability to physical risk from S&P Global Corporate Sustainability Assessment, we find evidence that higher physical risk is associated with higher expected returns. However, this risk premium diminishes with increased adaptability, signifying that risk management through adaptation reduces a company’s cost of capital. Notably, this adaptability-driven risk discount is more pronounced for high levels of physical risk, reflecting market incentives for efficient adaptation” (abstract).

Carbon-free distance: Carbon-Transition Risk and Net-Zero Portfolios by Gino Cenedese, Shangqi Han, and Marcin Kacperczyk as of Oct. 5th, 2023 (#493): “…. using a novel measure of distance-to-exit (DT E) … we show that companies that are more exposed to exit from net-zero portfolios have lower values and require higher returns from investors holding them. This result is economically large and is consistent with the view that DT E are useful measures of transition risk. Notably, we show that DT E capture distinct variation to that captured by previously used measures based on corporate carbon emissions. Distinct from these, they capture information that is forward-looking and is grounded in climate science“ (p. 29)

Attention, outsiders: Do Insiders Profit from Public Environmental Information? Evidence from Insider Trading by Sadok El Ghoul, Zhengwei Fu, Omrane Guedhami, and Yongwon Kim as of Oct. 19th, 2023 (#26): “We provide evidence that insiders sell their stocks profitably based on publicly available information on environmental costs. Further analysis indicates that these results become more pronounced when the search frequency for environmental information in Google is low, in countries governed by left-leaning governments, and in countries where investor protection is weak. These results … suggest that investor inattention and investor protection are key drivers of insider trading performance“ (abstract).

PE ESG boost: ESG Footprints in Private Equity Portfolios: Unpacking Management Instruments and Financial Performance by Noah Bani-Harounia, Ulrich Hommel, and Falko Paetzold as of Nr. 8th, 2023 (#13): “Based on data covering 206 buyout funds for the time period 2010-2022, … Improving fund-level ESG footprints by 50% explains a statistically and economically significant net IRR increase of up to 12.4% over a fund’s life cycle. The outcome is linked to specific ESG-management instruments of private equity investors, such as centralised ESG management and ESG value enhancement plans, while no significant effect is recorded for other measures, such as ESG reporting frequencies and ESG impact controlling” (abstract).

SDG rating confusion: “In partnership for the goals”? The (dis)agreement of SDG ratings by Tobias Bauckloh, Juris Dobrick, André Höck, Sebastian Utz, and Marcus Wagner as of May 31st, 2023 (#59): „This paper analyzes the (dis)agreement of Sustainable Development Goals (SDGs) ratings across different rating providers and implications for portfolio management. It documents a considerable level of disagreement that is particularly high for large companies and for companies from the Healthcare and the Basic Materials sector. In general, the sector in which the companies are mainly active explains a large part of the variation in disagreement measures of the SDG ratings. Moreover, we document different return characteristics and risk factor exposures of portfolios sorted according to SDG ratings of different rating providers” (abstract). My comment: I expect SDG-Risk-Ratings to have little additional value to ESG-Ratings. I prefer to use SDG-related revenues or Capex in addition to ESG-Ratings to avoid SDG rating confusion (see e.g. Divestments: 49 bei 30 Aktien meines Artikel 9 Fonds – Responsible Investment Research Blog (

Other investment research

Equity factors: Factor Zoo (.zip) by Alexander Swade, Matthias X. Hanauer, Harald Lohre and David Blitz from Robeco as of Nov. 15th, 2023 (#2546): “Using a comprehensive set of 153 U.S. equity factors, we find that a set of 10 to 20 factors spans the entire factor zoo, depending on the selected statistical significance level. This implies that most candidate factors are redundant but also that academic factor models, which typically contain just three to six factors, are too narrowly defined. When repeating the factor selection to factors as they become available over an expanding window, we find that newly published factors sometimes supersede older factor definitions, emphasizing the relevance of continuous factor innovation based on new insights or newly available data. However, the identified factor style clusters are quite persistent, emphasizing the relevance of diversification across factor styles” (p. 20/21). My comment: Without good (almost impossible) forecasts which factors will outperform, outperforming factor investing is difficult.

Bond factors: Corporate Bond Factors: Replication Failures and a New Framework by Jens Dick-Nielsen, Peter Feldhütter, Lasse Heje Pedersen, and Christian Stolborg as of Oct. 26th, 2023 (#1257): “Many corporate bond factors cannot be reproduced even when attempting to use the methodology of the corresponding paper. More broadly, even factors that can be reproduced should be questioned, since the corporate bond literature is based on data full of errors. … we show that the majority of corporate bond factors from the literature fail to replicate, but a minority of factors remain significant. Further, analyzing corporate bond factors based on equity signals, we find a number of significant new factors“ (p. 27/28). My comment: Same as above: Without good (almost impossible) forecasts which factors will outperform, outperforming factor investing is difficult.

Big fraud? How pervasive is corporate fraud? by Alexander Dyck, Adair Morse, and Luigi Zingales as of Oct. 2nd, 2023 (#120): “… we use the natural experiment provided by the sudden demise of a major auditing firm, Arthur Andersen, to infer the fraction of corporate fraud that goes undetected. This detection likelihood is essential to quantify the pervasiveness of corporate fraud in the United States and to assess the costs that this fraud imposes on investors. We find that two out of three corporate frauds go undetected, implying that, pre Sox, 41% of large public firms were misreporting their financial accounts in a material way and 10% of the firms were committing securities fraud, imposing an annual cost of $254 billion on investors“ (p. 31). My comment: It would be interesting to see the relationship between governance-ratings and fraud.

Health-Wealth-Gap: Health Heterogeneity, Portfolio Choice and Wealth Inequality by Juergen Jung and Chung Tran as of Oct. 18th, 2023 (#28): “… the early exposure to health shocks has strong and long-lasting impacts on the portfolio choice of households and the observed wealth gap among households at retirement age. … as sicker individuals often forgo investing in risky assets that pay higher returns in the long-run. This health-wealth portfolio channel amplifies wealth concentration across groups and over the lifecycle. … In the absence of the health-wealth portfolio channel, the observed wealth gap at retirement is 40–50 percent smaller. In addition, we provide new insights into the social benefit of health insurance. The expansion of public or private health insurance in the US can reduce wealth inequality via mitigating exposure to health expenditure shocks and thereby allow households to make riskier investment choices with higher long-term returns” (p. 27/28).

LLM financial analysts: Large Language Models and Financial Market Sentiment by Shaun A. Bond, Hayden Klok, and Min Zhu as of Oct. 23rd, 2023 (#257): “… we use ChatGPT and BARD to recall daily news summaries related to the S&P 500 Index, classify sentiments from these texts, and use these sentiments to forecast future index returns. … we demonstrate ChatGPT and BARD can recall and classify summary market-level financial text from the perspective of a financial analyst. … we show these sentiments proxy for aggregate investor sentiment and forecast future return reversals of the S&P 500 Index … we provide evidence that incorporating ChatGPT-derived sentiments leads to superior economic performance compared to portfolios that incorporate sentiments from BARD, simpler transformer models, and traditional dictionary approaches. LLMs have superior potential to process contextual information around specific topics or themes beyond that of simpler transformer models and context-indifferent word frequency methods. This greater context awareness leads to better identification of aggregate market sentiment, and superior short-term economic performance when taken into account. Further, results suggest LLMs can identify different aspects of sentiment from text, such as information on different frequencies, and the presence of persistent effects“ (p. 45). My comment see AI: Wie können nachhaltige AnlegerInnen profitieren? – Responsible Investment Research Blog ( or How can sustainable investors benefit from artificial intelligence? – GITEX Impact – Leading ESG Event 2023


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