Biodiversity risks illustration by Pixabay by Sergei Belozerov
10x new research regarding ESG disclosure effects, green innovation, food waste reduction, biodiversity models and investments, climate equity risks, AI investment opportunities, listed equity impact, sustainability questionnaires, hedge funds, open-source investment AI (#shows SSRN full paper downloads as of Sept. 5th, 2024)
Social and ecological research
Competitive disclosure effects: Do ESG disclosure mandates affect the competitive position of public and private firms? by Peter Fiechter, Jörg-Markus Hitz, and Nico Lehmann as of May 23rd, 2024 (#202): “… we explore economic effects of mandatory ESG disclosure, specifically the impact of these regulations on the competitive position of public and private suppliers in domestic markets. Using granular data on customer-supplier contracts, we find that the staggered adoption of ESG disclosure mandates in different economies around the globe has an economically meaningful impact on competition in these domestic markets, as private suppliers gain contracts at the expense of public suppliers. Our cross-sectional results provide evidence for two non-mutually exclusive mechanisms that help explain this finding: (i) ESG regulated corporate customers shift contracts from public to private suppliers, consistent with a preference for ESG opaque over ESG transparent supply chains, and (ii) adverse price competition effects for treated suppliers due to incremental direct and indirect costs associated with the ESG disclosure mandate. We also show that treatment effects are concentrated in contractual relations with suppliers of low importance to their corporate customers“ (p. 27/28).
Disclosure innovation push: Mandatory Disclosure and Corporate Green Innovation by Brian Bratten, Sung-Yuan (Mark) Cheng, and Tyler Kleppe as of May 29th, 2024 (#69): “Adopting a difference-in-differences research design surrounding the adoption of state-level greenhouse gas (GHG) emissions disclosure mandates, we find that disclosure mandates are associated with an increase in the quantity of patents related to climate change mitigation/adaptation technologies (i.e., “green innovations”). This increase is stronger among firms with more social investors …. We also document a positive association between GHG emissions disclosure mandates and future environmental performance ratings … However, we find that these mandates are associated with a reduction in future financial performance for some firms, suggesting a potential negative effect on shareholder welfare“ (abstract).
Good food AI: Using Artificial Intelligence To Reduce Food Waste by Yu Nu, Elena Belavina, and Karan Girotra as of June 3rd, 2024 (#219): “Technology companies … have launched (AI-powered) granular food waste information gathering systems that can easily measure and stratify food waste in an automated manner … The quasi-experimental … implementation at almost 900 commercial kitchens … reduces food waste, on average, by 29% three months post-adoption. … In addition, we estimate that upgrading to the computer-vision-based automatic recognition system induces a further 30% average reduction in food waste level one year post-upgrade“ (p. 38).
Biodiversity risks of models: Assessing Integrated Assessment Models for Building Global Nature-Economy Scenarios by Mathilde Salin, Katie Kedward, and Nepomuk Dunz as of August 22nd, 2024: “… we review how different ecosystem services, drivers of nature loss, and mitigation policies are represented in global integrated assessment models (Sö: IAM) that incorporate aspects of nature loss. … First, we find that applied global IAMs represent economic dependencies on only a subset of ecosystem services (mostly provisioning services, in particular food and water) and capture selected drivers of biodiversity loss (mainly climate and land use–related). Only a few models represent regulating and maintenance ecosystem services (focusing mainly on pollination and climate) albeit with only partial connections to the economy. … Second, we find that the representation of nature/policy dimensions in applied models is linked to macroeconomic variables by limited and in some cases indirect mechanisms. Important nature-to-economy transmission mechanisms are missing, such as those involving the role of critical ecosystem services to production … and human health and nutrition. … As a result, applied global models are likely to underestimate the economic impacts stemming from nature-related shocks“ (p. 17).
ESG investment research (in: Biodiversity risks)
Biodiversity risks of investments: Biodiversity Risk and Dividend Policy by Md Noman Hossain, Md Rajib Kamal, and Monika K. Rabarison as of Aug. 6th, 2024 (#33): “… we examine whether the increased corporate awareness of the potential loss of biodiversity affects dividend policy in relation to biodiversity risk. Using ,,, a sample of 26,811 firm-year observations in the United States, we found strong evidence that firms that are exposed to high-biodiversity risk pay lower dividends than those that are less exposed to biodiversity risk. … Additionally, we observe that financially constrained firms experience significantly lower dividend payouts when exposed to biodiversity risk. … The aforementioned negative association is more pronounced for firms with higher … biodiversity scores, and firms that get more public attention about their biodiversity risk“ (p. 32).
Climate equity risks: How Does Climate Risk Affect Global Equity Valuations? A Novel Approach by Ricardo Rebonato, Dherminder Kainth, and Lionel Melin from EDHEC as of July 10th, 2024: “1. A robust abatement policy, i.e., roughly speaking, a policy consistent with the 2°C Paris-Agreement target, can limit downward equity revaluation to 5-to-10%. 2. Conversely, the correction to global equity valuation can be as large as 40% if abatement remains at historic rates, even in the absence of tipping points. … 3. Tipping points exacerbate equity valuation shocks but are not required for substantial equity losses to be incurred. … 4. When state-dependent discounting is used for valuation, physical damages, even if ‘back-loaded’, are not fully ‘discounted away’, and contribute significantly to the equity valuation“ (p. 6).
Wrong sustainability questions? Explaining the Attitude-Behavior Gap for Sustainable Investors: Open vs. Closed-Ended Questions by Tobias Wekhof as of May 23rd, 2024 (#39): “We analyzed the attitude-behavior gap in sustainable investing … with open- and closed-ended questions. Our results indicate that open-ended responses have several advantages that can help to narrow the “gap.” Respondents tend to focus on fewer topics, making ranking topics across the entire sample more distinct. The written answers also allowed the expression of topics not included in the closed-ended options. However, respondents would often select a topic among the closed-ended options but not write about it. … the open-ended responses showed a higher predictive power“ (p. 18).
Other investment research
Listed equity impact? Who Clears the Market When Passive Investors Trade? by Marco Sammon and John J. Shim as of April 15th, 2024 (#832): “Over the past 20 years across all stocks, firms are the largest providers of shares to passive investors on average and on the margin: For every 1 percentage point (pp) change in ownership by index funds, firms take the other side at a rate of 0.64 pp. When restricting to stock-quarters where index funds are net buyers, firms issue at a rate of 0.95 pp. … firms, through adjustments in the supply of shares, are the single-most responsive group to inelastic demand. More than half of the adjustment comes through stock compensation, stock options, and restricted stock units …“ (abstract). My comment: Investing in “responsible” ETFs may therefore have more impact by providing additional capital (like private equity investments) than previously thought.
Hedge fund AI benefits: Generative AI and Asset Management by Jinfei Sheng, Zheng Sun, Baozhong Yang, and Alan Zhang as of April 8th, 2024 (#236): “… we develop a novel measure of the usage or reliance on generative AI (RAI) of investment companies based on their portfolio holdings and AI-predicted information. We study the adoption and implications of generative AI in hedge funds and 28 other asset management companies. … Hedge fund companies with higher RAI produce superior returns, both unadjusted and risk-adjusted. … we find hedge fund companies generate more returns from using AI-predicted firm-specific information related to firm policies and performance than from macroeconomic and sectorwise information. … Non-hedge fund companies do not produce significant returns. Furthermore, large and more active hedge fund companies adopt the technology early and perform better than others” (p. 28/29). My comment see AI: Wie können nachhaltige AnlegerInnen profitieren? or How can sustainable investors benefit from artificial intelligence?
Free Investment-AI: FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models by Hongyang (Bruce) Yang et al. as of May 29th, 2024 (#54): “… we introduce FinRobot, a novel open-source AI agent platform supporting multiple financially specialized AI agents, each powered by LLM. Specifically, the platform consists of four major layers: 1) the Financial AI Agents layer that formulates Financial Chain-of-Thought (CoT) by breaking sophisticated financial problems down into logical sequences; 2) the Financial LLM Algorithms layer dynamically configures appropriate model application strategies for specific tasks; 3) the LLMOps and DataOps layer produces accurate models by applying training/finetuning techniques and using task-relevant data; 4) the Multi-source LLM Foundation Models layer that integrates various LLMs and enables the above layers to access them directly. Finally, FinRobot provides hands-on for both professional-grade analysts and laypersons to utilize powerful AI techniques for advanced financial analysis. We open-source FinRobot at https://github. com/AI4Finance-Foundation/FinRobot“ (abstract).
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Werbehinweis (in: Biodiversity risks)
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