Animal Spirits

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 2023, we find that:

Keep Reading

In their 2023 book, The Missing Billionaires: A Guide to Better Financial Decisions, authors Victor Haghani and James White seek “to give you a practical framework, consistent with the consensus of university finance textbooks, for making good financial decisions that are right for you. Good decisions will take account of your personal circumstances, financial preferences, and your considered views on the risks and expected returns of available investments. …You will likely get the most out of this book if you have already accumulated a decent amount of financial capital or if you are young with a healthy measure of human capital. …The book is written from the perspective of a US individual or family…” Based on their many years of wealth management experience and portfolio systems development, they conclude that:

Keep Reading

What trading experience makes individual day traders quit trading? In their November 2023 paper entitled “Why Do Individuals Keep Trading and Losing?”. Fernando Chague, Bruno Giovannetti, Bernardo Guimaraes and Bernardo Maciel study the life cycle of individual traders who repeatedly open and close stock or futures positions on the same trading day. They focus on gross daily profit for individuals who begin day-trading during the sample period, day-trade for at least 30 trading days and then quit day-trading during the sample period. They ignore trading costs, costs of any trading courses taken and taxes. Using anonymized daily trade data for all Brazilian day traders during 2012 through 2018, they find that: Keep Reading

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:

• • iShares Global Clean Energy (ICLN)
  • Invesco Solar (TAN)
  • First Trust NASDAQ Clean Edge Green Energy Index (QCLN)
  • Invesco WilderHill Clean Energy (PBW)
  • ALPS Clean Energy (ACES)
  • Invesco Global Clean Energy (PBD)
  • SPDR S&P Kensho Clean Power (CNRG)
  • First Trust Global Wind Energy (FAN)
  • Global X Renewable Energy Producers (RNRG)

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 2023, we find that: Keep Reading

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 2022 (56 events), we find that: Keep Reading

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:

Keep Reading

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:

Keep Reading

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:

Keep Reading

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

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