Aesthetic Investments

Do exchange-traded funds selecting stocks based on environmental, social, and governance characteristics (ESG ETF) typically offer attractive performance? To investigate, we compare performance statistics of eight ESG ETFs, all currently available, to those of simple and liquid benchmark ETFs, as follows:

1. iShares MSCI USA ESG Select ETF (SUSA), with SPDR S&P 500 ETF Trust (SPY) as a benchmark.
2. iShares MSCI KLD 400 Social ETF (DSI), with SPY as a benchmark.
3. iShares ESG MSCI EM ETF (ESGE), with iShares MSCI Emerging Markets ETF (EEM) as a benchmark.
4. iShares ESG Aware MSCI EAFE ETF (ESGD), with iShares MSCI EAFE ETF (EFA) as a benchmark
5. iShares ESG MSCI USA ETF (ESGU), with SPY as a benchmark.
6. Nuveen ESG Small-Cap ETF (NUSC), with iShares Russell 2000 ETF (IWM) as a benchmark.
7. Vanguard ESG U.S. Stock ETF (ESGV), with SPY as a benchmark.
8. Vanguard ESG International Stock ETF (VSGX), with Vanguard FTSE All-World ex-US Index Fund ETF (VEU) as a benchmark.

We focus on average return, standard deviation of returns, reward/risk (average return divided by standard deviation of returns), compound annual growth rate (CAGR) and maximum drawdown (MaxDD), all based on monthly data. Using monthly dividend-adjusted returns for all specified ETFs since inceptions and for all benchmarks over matched sample periods through June 2024, we find that: Keep Reading

How much do investors gain or sacrifice by focusing their portfolios on “sustainable” (green) stocks? In their March 2024 paper entitled “In Search of the True Greenium”, Marc Eskildsen, Markus Ibert, Theis Jensen and Lasse Pedersen broadly examine the green-minus-brown premium (the greenium). Specifically, they:

• Replicate and extend past studies to estimate the U.S. equity greenium in 230 ways based on realized returns, encompassing: 23 firm greenness metrics; estimates with or without industry-neutrality; and, five ways of adjusting for risk.
• Generate estimates of the greenium in each of 48 countries also using realized returns, each firm greenness metric and each way to adjust for risk.
• Construct a robust firm greenness score by averaging key greenness metrics from leading data providers and estimate the greenium using expected (instead of realized) returns based on each firm’s implied cost of capital. For robustness, they consider other ways to model expected returns.

They also estimate the greenium for U.S. corporate bonds. Using the specified data as available during August 2009 through December 2022, they find that: Keep Reading

Prior research indicates that stocks of firms with high direct and indirect carbon dioxide emissions tend to beat the market (offer a carbon premium). Does high-emissions stock outperformance derive from surprisingly high earnings? In their September 2023 paper entitled “Does the Carbon Premium Reflect Risk or Mispricing?”, Yigit Atilgan, Ozgur Demirtas, Alex Edmans and Doruk Gunaydin examine relationships between firm carbon dioxide emissions and future earnings surprises. They consider three levels of emissions from S&P Global Trucost: Scope 1 directly from firm operations; Scope 2 from firm consumption of purchased heat/electricity/steam; and, Scope 3 from upstream supply chain operations. They consider level of emissions (natural logarithm of emissions measured in tons) and annual change in level of emissions, with the latter winsorized at the 2.5% level. They consider several measures of earnings surprises, all comparing analyst forecasts to actual earnings. They calculate market reactions to earnings announcements as 3-day cumulative abnormal returns (CAR) relative to a 3-factor (market, size, book-to-market) model the day before through the day after earnings announcements. Using carbon dioxide emissions data, stock returns, market valuations, book values and analyst earnings forecasts for a broad sample of U.S. stocks during 2002 through 2021, they find that: Keep Reading

Do companies that make the strongest commitments to diversity, equity and inclusion (DEI) generate attractive stock returns? In their April 2023 paper entitled “Diversity, Equity, and Inclusion”, Alex Edmans, Caroline Flammer and Simon Glossner relate DEI to future firm performance and stock returns. They measure firm DEI based on 250 confidential employee responses to 13 of 58 questions on a Trust Index survey that comprises two thirds of the score for each firm applying to be one of the Best Companies to Work For in America. Using the specified annual survey responses, associated firm accounting data and monthly stock returns for all companies applying to be a best company during 2006 through 2021, they find that: Keep Reading

Do good firm environmental, social and governance (ESG) ratings signal attractive stock returns? If so, what is the best way to exploit the signals? In their February 2023 paper entitled “Quantifying the Returns of ESG Investing: An Empirical Analysis with Six ESG Metrics”, Florian Berg, Andrew Lo, Roberto Rigobon, Manish Singh and Ruixun Zhang test performance of long-short ESG portfolios of U.S., European and Japanese stocks based on proprietary ESG scores from six major rating sources. They consider ESG scores from individual sources and apply several statistical and voting-based methods to aggregate ESG ratings across sources, including: simple average, Mahalanobis distance, principal component analysis, average voting and singular transferable voting. They consider equal-weighted and ESG score-weighted portfolios. They consider different percentile thresholds for long and short holdings. They assess ESG portfolio alpha with respect to widely used 1-factor (market), 3-factor (plus size and value) and 5-factor (plus investment and profitability) models of stock returns. They further test long-short portfolios from aggregations of E, S and G scores separately across sources. Using proprietary ESG ratings, monthly returns of associated stocks and monthly factor model returns during 2014 through 2020, they find that:

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Are non-fungible tokens (NFT) viable and attractive as an investment class? In their December 2022 paper entitled “Non-Fungible Tokens (NFTs) as an Investment Class”, Mieszko Mazur and Efstathios Polyzos provide an overview of NFT investing. First, they summarize NFT primary and secondary markets, exchanges, aggregators, borrowing and lending,  and staking. Then, they analyze returns for leading NFT collections overall and separately during bull and bear markets. Using data as available from OpenSea excluding those in the bottom 1% of prices on nearly two million NFT transactions across leading NFT collections and ether/U.S. dollar exchange rates through June 2022, they find that:

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Is growing interest in environmental, social, and governance (ESG) issues among investors and asset managers materially affecting stock selection decisions and associated returns? In the September 2022 version of their paper entitled “The Economic Impact of ESG Ratings”, Florian Berg, Florian Heeb and Julian Kölbel measure impacts of ESG rating changes on associated mutual fund holdings and stock returns. They focus on average abnormal holdings changes and average cumulative abnormal returns from: (1) 12 months before rating change up to the change, and (2) from the ratings change through 24 months after the change. Abnormal returns control for firm leverage, size, book-to-market ratio and profitability, and for stock return beta and momentum. Using quarterly fundamentals and monthly stock returns and ESG-dedicated mutual fund holdings for 3,665 firms with a total of 2,545  MSCI ESG rating upgrades and 2,133 downgrades during February 2013 through September 2020, they find that:

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Do environmental, social, and corporate governance (ESG) ratings aggregated across individual firms predict overall stock market returns? In the July 2022 version of their paper entitled “ESG and the Market Return”, Ran Chang, Liya Chu, Bohui Zhang, Guofu Zhou and Jun Tu investigate whether ESG ratings in aggregate predict overall stock market returns. Specifically, they each month:

• Combine 38 firm-level ESG subcategory ratings via equal weighting to calculate 38 market-level ESG measures.
• Apply machine learning tools to these market-level measures to suppress noise and redundancies and generate 14 market-level predictors.
• Aggregate the 14 predictors into a market-level composite ESG index, and similarly develop market-level environmental, social and governance ESG subindexes.
• Use full-sample (in-sample) regression to relate ESG index/subindexes to next-month and next-year stock market excess return (value-weighted stock market return minus U.S. Treasury bill yield).
• Use the first seven years of the sample as the initial training period and the rest of the data as an out-of-sample forecast evaluation period.

Using monthly firm ESG data from Morningstar Sustainalytics and stock market excess returns during August 2009 (ESG measurement inception) through September 2019, they find that: Keep Reading

Are there conflicts inherent in an investment strategy seeking to impose social preferences on a value style? In their May 2022 paper entitled “No Good Deed Goes Unpunished? Social vs. Investment”, Tzee-man Chow and Feifei Li investigate how a carbon reduction requirement affects construction and performance of a global developed market value stock strategy. They measure firm carbon emissions using end-of-year data from Institutional Shareholder Services (ISS), which supplements publicly available self-reported emissions with analyst reviews/estimates. They lag ISS data by three months and merge it with information for large and medium-sized stocks (top 86% of market value) in each country. Their benchmark value portfolio each year holds the market capitalization-weighted cheapest 10% of stocks based on composite valuation (average standardized book-to-price, cash flow-to-price and sales-to-price ratios and dividend yield). They then lower the carbon intensity of this portfolio via an iterative process of shifting weights from firms with relatively high carbon intensity to those with relatively low carbon intensity to achieve portfolio carbon intensities in the range 100% to 50% of that for the full universe. Using carbon emissions, valuation and price data for the specified stock universe during April 2016 through March 2021, they find that:

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What are the return behaviors of non-fungible tokens (NFT), which employ blockchain technology to convey ownership of unique digital or physical items? In their March 2022 paper entitled “The Economics of Non-Fungible Tokens”, Nicola Borri, Yukun Liu and Aleh Tsyvinski assemble a comprehensive dataset of NFT transactions (including digital art/media and objects related to virtual worlds) and create NFT overall market and sector indexes based on a repeat sales method. They then test:

• NFT market exposure to cryptocurrency market, size, value, momentum and attention factors.
• NFT market exposure to traditional equity, commodity and currency market factors.
• NFT market return predictability based on NFT market volatility, index-to-transaction valuation ratio, volume, momentum and attention factors.
• Individual NFT return predictability based on size and momentum/reversal.

Using blockchain-validated weekly data from major NFT exchanges during January 2018 through December 2021, encompassing about 1.3 million repeat sales, they find that: Keep Reading