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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.

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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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. equity market. Using annual performance data from his 2019 letter for 1965 through 2019 (55 years) and the investing approach/outlooks described in his letters of 1977 through 2019, we find that: Keep Reading

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

Twisting Buffett’s Preferred Stocks-bonds Allocation Internationally

As summarized in “Twisting Buffett’s Preferred Stocks-bonds Allocation”: (1) Warren Buffett’s preferred fixed asset allocation of 90% stocks and 10% short‐term government bonds (90-10), rebalanced annually, is sensible for U.S. markets; and, (2) investors may be able to beat this allocation modestly by adding simple annual dynamics. Are findings similar internationally? In his July 2016 paper entitled “Global Asset Allocation in Retirement: Buffett’s Advice and a Simple Twist”, Javier Estrada extends his analysis of U.S. markets to 20 other countries. He assumes a 1,000 (local currency unit) nest egg to start a 30‐year retirement. Annual withdrawals (either 4% or 3% of the initial amount, adjusted annually for inflation) and rebalancing to the target allocation occur at the beginning of each year. The first 30‐year retirement interval is 1900‐1929 and the last 1985‐2014, for a total of 86 rolling intervals. He first compares performances of eight fixed stocks-bonds allocations, rebalanced annually, ranging from 100-0 to 30-70. He then compares a fixed 90-10 allocation to one with a dynamic twist that, at the end of each year, compares the stock market’s annualized total return over the last five years to its annualized total return since the beginning of the sample. If 5-year performance exceeds long-term performance, the annual withdrawal comes from stocks with rebalancing to 90-10. If long-term performance exceeds 5-year performance, the annual withdrawal comes from bonds with no portfolio rebalancing (giving stocks time to recover). He focuses on average portfolio failure rate (running out of money within 30 years) and average terminal wealth across countries as key performance metrics. Using annual stock and short-term government bond real total returns (adjusted by local inflation rate) in local currencies for 21 countries as compiled by Dimson‐Marsh‐Staunton for 1900 through 2014, he finds that: Keep Reading

Forbes Evaluates Ken Fisher’s Stock Picking

Each year, Forbes calculates the performance of columnist recommendations assuming: (1) equal initial investments in each stock pick when published; (2) 1% trading friction for each purchase; and, (3) matching benchmark investments in the S&P 500 Index for each pick with no trading friction. Because matching benchmark investments are spread across the year, the benchmark performance is not the same as the annual performance of the S&P 500 Index. In his February 10, 2016 column for Forbes, Ken Fisher reports the performance of the recommendations he made in his column during 2014, as follows: “Calculated by Forbes, taking a hypothetical 1% brokerage commission haircut, my basket lagged the S&P 500 (without any brokerage haircut) by 5% equal dollars invested. This is the seventh year out of 20 that my picks have lagged and the third year in a row.” Using data from the 18 annual performance summary columns covering 1998 through 2015, we find that: Keep Reading

Twisting Buffett’s Preferred Stocks-bonds Allocation

What is Warren Buffett’s preferred fixed asset allocation, and how does it perform? In his October 2015 paper entitled “Buffett’s Asset Allocation Advice: Take It … With a Twist”, Javier Estrada examines Warren Buffett’s 2013 implied endorsement of a fixed allocation of 90% stocks and 10% short‐term bonds (90/10). Specifically, he tests the performance of eight fixed asset allocations ranging from 100/0 to 30/70. Testing assumes a $1,000 nest egg at retirement, a withdrawal rate of 4% of the initial amount adjusted annually for inflation and a 30‐year retirement. At the beginning of each year, the retiree makes the annual withdrawal and rebalances to the target allocation. The first 30‐year retirement interval is 1900‐1929 and the last 1985‐2014, for a total of 86 rolling intervals. He further explores two adjustments (twists) to the 90/10 allocation:

  1. T1 – If stocks are up the past year, take the annual withdrawal from stocks and rebalance to 90/10. If stocks are down, take the annual withdrawal from bonds and do not rebalance.
  2. T2 – If stocks outperform bonds the past year, take the annual withdrawal from stocks and rebalance to 90/10. If stocks underperform, take the annual withdrawal from bonds and do not rebalance.

Using U.S. stock market and U.S. Treasury bill (T-bill) annual real total returns as compiled by Dimson‐Marsh‐Staunton for 1900 through 2014, he finds that: Keep Reading

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