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Animal Spirits

Are investors and traders cats, rationally and independently sniffing out returns? Or are they cows, flowing with a herd that must know something? These blog entries relate to behavioral finance, the study of the animal spirits of investing and trading.

Mad Money Still Mad?

Does coverage of stocks on Mad Money attract attention to them and affect their returns? In their August 2022 paper entitled “Does the Mad Money Show Cause Investors to Go Madly Attentive?”, Lawrence Kryzanowski and Ali Rouhghalandari examine reactions of investors to stocks related to Mad Money guest interviews and buy/sell recommendations. They measure impacts on investor attention to the stocks via associated SEC EDGAR activity (segmented into retail and institutional users based on IP address) and via number of relevant posts on Stocktwits. They measure abnormal returns based on cumulative 5-factor alphas (adjusting for market, size, book-to-market, profitability and investment effects) from 10 trading days before through 20 trading days after coverage relative to the interval from 230 trading days to 30 trading days before coverage. Using attention and return data for all stocks covered on Mad Money during June 2006 through December 2020, they find that:

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Machines Smarter than Expert Investors?

Do presumably expert early-stage startup investors, whether individuals (Angels) or institutions (Venture Capitalists) invest efficiently? In his June 2022 paper entitled “Predictably Bad Investments: Evidence from Venture Capitalists”, Diag Davenport applies machine learning methods based on information known at the time of investment to evaluate decisions of early-stage investors. He defines early-stage investments as equity deals within two years of incubator completion categorized in Pitchbook as deal types Series A, Series B, Seed Round or Angel (Individual). He define late-stage exit as initial public offering, merger/acquisition or funding categorized in Pitchbook as Series C or later. He uses his first five years of quantitative data and numerical transformations of the qualitative data (text) in training a model with XGBoost to predict future venture success. He then applies the model to the next three years of data to build a portfolio that substitutes conventional investments (such as the S&P 500 Index) for predictably bad ventures. Using venture financials and qualitative information about the CEO from Pitchbook for 16,054 startups accepted into top accelerator programs during 2009 through 2016 (2009-2013 for model training and 2014-2016 for testing), he finds that:

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Anti-ESG Portfolio Performance?

Should investors expect materially different returns for stocks accepted or excluded by institutional investors based on firm environmental, social and corporate governance (ESG) policies and practices? In their April 2022 paper entitled “The Expected Returns of ESG Excluded Stocks. The Case of Exclusions from Norway’s Oil Fund”, Erika Berle, Wangwei He and Bernt Ødegaard analyze aggregate performance of stocks excluded by the Norwegian Government Pension Fund Global portfolio based on ESG-related conduct or products, used as a model by many institutional investors. They construct various equal-weighted (EW) and value-weighted (VW) portfolios of excluded stocks and measure returns and Fama-French 5-factor (market, size, book-to-market, profitability and investment) alphas of these portfolios. Using monthly returns in U.S. dollars and firm data for a sample of 186 excluded stocks, with some exclusions revoked, during 2005 through early 2022, they find that:

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Underwear Leads the Stock Market?

A subscriber hypothesized that keeping old underwear is an early indicator of personal income at risk. Trends in underwear, as proxied by Hanesbrands Inc. (HBI), may therefore be a leading indicator of trends in the overall stock market. To test this hypothesis, we relate HBI returns to SPDR S&P 500 ETF Trust (SPY) returns at a monthly frequency. Using monthly dividend-adjusted prices for HBI and SPY during September 2006 (limited by HBI) through March 2022, we find that: Keep Reading

A Slinky (Short-term Reversion) Effect?

Do often frenzied investors/traders tend to overdo buying and selling, coming to their senses shortly thereafter? In other words, does the broad U.S. stock market tend to revert after short-term moves up or down? To check, we relate sequential past and future return intervals of 1, 2, 3, 5, 10, 15 and 21 trading days. Using daily closes of the S&P 500 Index over the period January 1928 through mid-March 2022, we find that: Keep Reading

Climate Solutions Stocks

Are firms offering products and services purported to mitigate climate change compelling investments? In the February 2022 revision of their paper entitled “Climate Solutions Investments”, Alexander Cheema-Fox, George Serafeim and Hui Wang analyze international reports, regional net zero frameworks, research papers and news to develop a list of 164 key words/phrases associated with climate change solution business areas. They apply these key words/phrases to firm descriptions to identify 632 actively traded pure plays in climate solutions. They then characterize geographies, accounting fundamentals and valuation ratios for this sample and construct monthly rebalanced value-weighted and equal-weighted climate solutions portfolios (CSP). Using monthly firm fundamentals and stock trading data for these 632 firms from the end of 2010 through October 2021, they find that: Keep Reading

Doom and the Stock Market

Is proximity to doom good or bad for the U.S. stock market? To measure proximity to doom, we use the Doomsday Clock “Minutes-to-Midnight” metric, revised intermittently in late January via the Bulletin of the Atomic Scientists, which “warns the public about how close we are to destroying our world with dangerous technologies of our own making. It is a metaphor, a reminder of the perils we must address if we are to survive on the planet.” Using the timeline for the Doomsday Clock since inception in 1947 and contemporaneous end-of-year levels of the S&P 500 Index through 2021, we find that:

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Stock Market and the Super Bowl

Investor mood may affect financial markets. Sports may affect investor mood. The biggest mood-mover among sporting events in the U.S. is likely the National Football League’s Super Bowl. Is the week before the Super Bowl especially distracting and anxiety-producing? Is the week after the Super Bowl focusing and anxiety-relieving? Presumably, post-game elation and depression cancel between respective fan bases. Using past Super Bowl dates since inception and daily/weekly S&P 500 Index levels for 1967 through 2021 (55 events), we find that: Keep Reading

How Are Renewable Energy ETFs Doing?

How do exchange-traded-funds (ETF) focused on supplying renewable energy perform? To investigate, we consider nine of the largest renewable energy ETFs, all currently available, as follows:

We use SPDR S&P 500 (SPY) as a benchmark, assuming investors look at renewable energy stocks to beat the market and not to beat the energy sector. We focus on monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). Using monthly returns for the nine renewable energy ETFs and SPY as available through September 2021, we find that: Keep Reading

Variation in COVID-19 Cases and Future Asset Returns

Does variation in the number of reported cases of COVID-19 predict near-term asset returns? To investigate, we look for a test acknowledging that the available sample is short and very noisy. Specifically:

  • To suppress noise, we use the 7-day moving average of U.S. COVID-19 cases.
  • To avoid measurement overlap, we calculate weekly changes in this average and compare these changes to next-week returns for SPDR S&P 500 Trust (SPY) and iShares Barclays 20+ Year Treasury Bond (TLT).
  • To assess reliability of any relationship, we look at rolling 13-week correlations between weekly changes in COVID-19 data and next-week asset returns. While 13 weeks is a short measurement interval for noisy data, consistency in outputs would offer some confidence that there is a reliable relationship.

Using weekly (Friday) COVID-19 case data from the Centers for Disease Control (CDC) and weekly (Friday close) dividend-adjusted SPY and TLT levels during late January 2020 (limited by COVID-19 data) through mid-September 2021, we find that: Keep Reading

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