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Individual Gurus

These blog entries consist of reviews of the performance of individual gurus based on information freely available on the web.

Test of Some Motley Fool Public Stock Picks

A reader asked: “I am wondering how come you have not rated Motley Fool guys. Any insight?” To augment the test of Motley Fool public stock picks in “‘Buy These Stocks for 2019’ Forward Test”, we look at two more lists of stock picks: “10 Top Stocks That Will Make You Richer in 2021” with publication date 1/5/2021; and, “7 Stocks That Could Make You Richer in 2022” with publication date 1/5/2022. We calculate total (dividend-reinvested) returns for stocks in the first list during 1/5/2021 through 12/31/2021 and for stocks in the second list during 1/5/2022 through 11/11/2022. We compare average returns for these lists to returns for SPDR S&P 500 ETF Trust (SPY) over matched sample periods. Using dividend-adjusted closing prices for SPY and each of the stocks in the two lists on the specified beginning and end dates, we find that: Keep Reading

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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Testing the Buffett Indicator Outside the U.S.

Is the Buffett Indicator, the ratio of total stock market capitalization to Gross Domestic Product (GDP), a useful indicator of future stock market performance internationally? In their March 2022 paper entitled “The Buffett Indicator: International Evidence”, Laurens Swinkels and Thomas Umlauft extend Buffett Indicator research from the U.S. to 14 international equity markets. Because the value of the indicator varies so much across countries at a given time (for example, 1.48 for the U.S. and 0.55 for Germany at the end of 2019), they first look at time-series predictability of returns by the Buffett Indicator within each country. They then compare predictive power of the Buffett Indicator to those of Shiller’s cyclically-adjusted price-to-earnings ratio (CAPE or P/E10) and mean-reversion in stock returns. Finally, they test a trading strategy that invests in the stock markets of those countries having low values of the Buffett Indicator relative to their respective (expanding window) histories. Using stock market valuation and earnings data and GDP series for 14 countries as available during 1973 through 2019, they find that:

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Warren Buffett on Investing

Does Warren Buffett consistently keep Berkshire Hathaway in market-beating form? If so, how does he do it? In his annual letters to stockholders, he includes company performance and benchmark data and describes in general terms how he goes about investing. He sometimes shares his thoughts on the current state of and prospects for the U.S. markets. Using annual performance data from his 2021 letter for 1965 through 2021 (57 years) and the investing approach/outlooks described in his letters of 1977 through 2021, we find that: Keep Reading

Skillful Advice from Seeking Alpha?

Do non-professional analysts who publish on Seeking Alpha offer valuable stock-picking advice? In their August 2020 paper entitled “The Cross-Section of Non-Professional Analyst Skill”, Michael Farrell, Russell Jame and Tian Qiu measure skill among such analysts as the hypothetical abnormal return an investor would earn by following reports/recommendations that focus on one common stock over 5-day or 63-day post-publication holding intervals. They classify recommendations as buy or sell using either: (1) disclosed author positions, or (2) sentiment of associated reports inferred from word usage. They measure abnormal return for each recommendation as its 6-factor alpha, adjusting for market, size, book-to-market, profitability, investment and momentum factors calculated from daily returns from 13 months to one month before the recommendation. They further test an implementable trading strategy that buys (sells) at the ask (bid) and subsequently sells (buys) at the bid (ask) price at the end of the holding period, with and without delays of 24 to 72 hours after publication. Using 123,120 Seeking Alpha research reports prepared by 1,879 non-professional analysts (each with at least 10 qualifying reports) and focused on single common stocks, along with contemporaneous stock and factor returns, during 2005 through 2017, they find that:

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Wisdom from the Essays of Warren Buffett

What advice does Warren Buffett offer investors? In his December 2019 paper entitled “Introduction to the Essays of Warren Buffett: Lessons for Corporate America”, Lawrence Cunningham summarizes main themes of the 5th edition of the essay collection (letters to shareholders), including those related to investing. Based on the advice in these letters, he concludes that: Keep Reading

Jim Cramer Using the S&P Oscillator

A reader asked about the usefulness of the S&P Short-range Oscillator as sometimes used by Jim Cramer to forecast U.S. stock market returns. The self-reported “Performance” of the oscillator, relying on in-sample visual inspection with snooped thresholds, is of small use. Since continuous historical values of the indicator are not publicly available, we conduct an out-of-sample test by:

  1. Searching CNBC.com for “Oscillator” “Mad Money” and just “Oscillator” on October 3, 2019 and identifying articles with U.S. stock market forecasts from Jim Cramer based on the S&P Short-range Oscillator.
  2. Extracting the date for each forecast and determining whether it is call to be “In” or “Out” of the market.
  3. Calculating for each call a cumulative S&P 500 Index return starting at the next open after the article date (generally timestamped after the market close) for 21 trading days.
  4. Computing average cumulative performances of “In” and “Out” calls.
  5. Comparing these averages to that for all days spanning the search results.

Using the 15 qualifying articles and daily opening levels of the S&P 500 Index during June 16, 2008 through October 31, 2019, we find that: Keep Reading

Sunspot Cycle and Stock Market Returns

A reader asked whether Charles Nenner, self-described as “the talk of Wall Street since accurately predicting some of the biggest moves in the Markets over the past few years,” accurately forecasts equity and commodity markets. We consider the following:

  • In his July 2007 discussion of the “Nenner Methodology at the Bloomberg Studio”, Charles Nenner cites sunspot activity as a specific key indicator for equity returns. Per this source, he believes that the sunspot cycle correlates strongly with equity markets via the predictable effects of magnetic field disturbances on investors.
  • In “Sunspots Predict ‘Major Crisis’ After 2013: Chartist”, he states: “If there is a high intensity of sunspots, markets rise, if their intensity lowers, markets go down because sunspots affect people’s mood.”

Is there a reliable relationship between sunspot activity and stock market returns? Using monthly averages of daily sunspot counts and monthly levels of Shiller’s S&P Composite Index (also monthly averages of daily levels) during January 1871 (limited by the Shiller data) through October 2018, we find that: Keep Reading

Explaining Warren Buffett’s Performance

Is Warren Buffett’s track record explicable and replicable? In the June 2018 update of their paper entitled “Buffett’s Alpha”, Andrea Frazzini, David Kabiller and Lasse Pedersen model Warren Buffett’s exceptional investing performance based on replicating exposures of Berkshire Hathaway overall and of its publicly traded holdings to six factors. Four of the factors are those conventionally used to explain stock returns: market return, size, book-to-market ratio and momentum. The other two factors are betting-against-beta (buy low beta and avoid high beta) and quality (profitable, growing, dividend-paying). They further create portfolios that track Berkshire Hathaway’s factor exposures, leveraged to the same active risk as Berkshire Hathaway. Using monthly stock returns and accounting data for a broad sample of U.S. stocks, quarterly Berkshire Hathaway SEC Form 13F holdings and monthly returns for six factors specified above during October 1976 through March 2017, along with contemporaneous open-end active mutual fund performance data, they find that:

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Guru Re-grades

What happens to the rankings of Guru Grades after weighting each forecast by forecast horizon and specificity? In their March 2017 paper entitled “Evaluation and Ranking of Market Forecasters”, David Bailey, Jonathan Borwein, Amir Salehipour and Marcos Lopez de Prado re-evaluate and re-rank market forecasters covered in Guru Grades after weighting each forecast by these two parameters. They employ original Guru Grades forecast data as the sample of forecasts, including assessments of the accuracy of each forecast. However, rather than weighting each forecast equally, they:

  • Apply to each forecast a weight of 0.25, 0.50, 0.75 or 1.00 according to whether the forecast horizon is less than a month/indeterminate, 1-3 months, 3-9 months or greater than 9 months, respectively.
  • Apply to each forecast a weight of either 0.5 for less specificity or 1.0 for more specificity.

Using a sample of 6,627 U.S. stock market forecasts by 68 forecasters from CXO Advisory Group LLC, they find that: Keep Reading

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