Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for March 2023 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for March 2023 (Final)
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Fundamental Valuation

What fundamental measures of business success best indicate the value of individual stocks and the aggregate stock market? How can investors apply these measures to estimate valuations and identify misvaluations? These blog entries address valuation based on accounting fundamentals, including the conventional value premium.

Usefulness of P/E10 as Stock Market Return Predictor

Does P/E10 (or Cyclically Adjusted Price-Earnings ratio, CAPE) usefully predict U.S. stock market returns? Per Robert Shiller’s data, P/E10 is inflation-adjusted S&P Composite Index level divided by average monthly inflation-adjusted 12-month trailing earnings of index companies over the last ten years. To investigate its usefulness, we consider in-sample regression/ranking tests and out-of-sample cumulative performance tests. Using monthly values of P/E10, S&P Composite Index levels (calculated as average of daily closes during the month), associated dividends (smoothed), 12-month trailing real earnings (smoothed) and interest rates as available during January 1871 through September 2022, we find that: Keep Reading

Stock Index Earnings-Returns Lead-lag

A subscriber asked about the lead-lag relationship between S&P 500 earnings and S&P 500 Index returns. To investigate, we relate actual aggregate S&P 500 operating and as-reported earnings to S&P 500 Index returns at both quarterly and annual frequencies. Earnings forecasts are available well in advance of returns. Actual earnings releases for a quarter occur throughout the next quarter. Using quarterly S&P 500 earnings and index levels during March 1988 through June 2022 and September 2022, respectively, we find that: Keep Reading

Do High-dividend Stock ETFs Beat the Market?

A subscriber asked about current evidence that high-dividend stocks outperform the market. To investigate, we compare performances of 10  exchange-traded funds (ETFs) holding high-dividend stocks to that of SPDR S&P 500 (SPY) as a proxy for the U.S. stock market. The  high-dividend stock ETFs, from oldest to newest, are:

For each of these ETFs, we compare average monthly total (dividend-reinvested) return, standard deviation of monthly returns, monthly return-risk ratio (average monthly return divided by standard deviation), compound annual growth rate (CAGR) and maximum drawdown (MaxDD) to those for SPY over matched sample periods. Using monthly total returns for the 10 high-dividend stock ETFs and SPY over available sample periods through September 2022, we find that:

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The Most Important Firm Fundamental?

What kind of firm growth should long-term investors value most? In his August 2022 paper entitled “The Role of Net Income Growth in Explaining Long-Horizon Stock Returns”, Hendrik Bessembinder relates decade compound stock returns to same-decade growth in firm net income, sales and assets and same-decade average profitability (income-to-assets ratio). His universe consists of U.S. common stocks/decades with available data and inflation-adjusted (to end-of-sample) market capitalization at least $500 million at the beginning of a decade. He further excludes firm/decades with net income-to-total assets ratio at the beginning of the decade less than 0.15% (the bottom percentile of profitable firms). He calculates both decade excess returns (relative to U.S. Treasury bill return) and decade returns relative to that of the value-weighted U.S. stock market, both expressed on an annualized basis. For growth variables, he measures growth based on differences between the last and first years of a decade, and ultimately excludes the top and bottom 1% to mitigate effects of extreme outliers. For each decade and each variable, he then ranks stocks into fifths (quintiles) and calculates the difference in average returns between the highest and lowest quintiles. He looks at the full sample of five decades and subsamples of the early decades (1970s and 1980s) and recent decades (1990s, 2000s, 2010s). Using the specified accounting data and associated stock returns during January 1970 through December 2019, he finds that:

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Best Model of Future Stock Market Returns?

Which variables deserve greatest focus when predicting stock market returns? In their July 2022 paper entitled “Searching for the Best Conditional Equity Premium Model”, Hui Guo, Saidat Sanni and Yan Yu exhaustively explore combinations of 18 previously identified potential stock market return predictors to isolate the most powerful subset. They focus on a best subset selection method with a penalty on complexity, thereby suppressing data snooping bias and selecting a manageable subset. For robustness, they consider four alternative variable selection methods. Using quarterly U.S. data for these 18 variables and S&P 500 Index levels/returns during 1947 through 2020, they find that: Keep Reading

Best Brands Investment Performance

Do the Best Brands, as published annually by Interbrand based on net present value of predicted incremental earnings due to brand, offer superior investment performance due to pricing power and superior operating practices? In their June 2022 paper entitled “Is Buffett Right? Brand Values and Long-run Stock Returns”, Hamid Boustanifar and Young Dae Kang examine the investment performance of Best Brands. Best Brands companies must be global, have publicly available financial data, be visible and have the expectation of positive long-term profitability above the cost of capital). Up to 2007 (subsequently), Interbrand published Best Brand lists in July or August (late September or October). The authors each year reform a Best Brands portfolio limited to U.S. firms the first day of the month after publication, thereby excluding immediate announcement effects on stock prices. For stocks encompassing multiple brands (e.g., Google and YouTube for Alphabet), they map brands to stocks by summing brand values. Using firm characteristics, accounting data and stock prices for a broad sample of U.S. stocks during 2000 (the first Best Brands list) through 2020, they find that:

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S&P 500 Price-to-Sales Ratio and Stock Market Returns

A subscriber suggested looking at the S&P 500 price-to-sales ratio (P/S) as an indicator for timing the U.S. stock market. To investigate, we relate P/S and change in P/S to S&P 500 Index (SP500) returns, as follows:

  1. Conduct lead-lag analyses for quarterly P/S versus quarterly SP500 returns, and for quarterly change in P/S versus SP500 returns.
  2. Calculate average next-quarter SP500 returns by range of quarterly values of P/S and quarterly changes in P/S.

Using quarterly S&P 500 P/S data since the end of December 2000 and quarterly closing SP500 levels since December 1999, both through June 2022, we find that: Keep Reading

Are Stock Quality ETFs Working?

Are stock quality strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider five ETFs, all currently available (from oldest to youngest):

We calculate monthly return statistics, along with compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). Using monthly returns for the stock quality ETFs and benchmarks as available through June 2022, we find that:

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SACEVS-SACEMS Leverage Sensitivity Tests

“SACEMS with Margin” investigates the use of target 2X leverage via margin to boost the performance of the “Simple Asset Class ETF Momentum Strategy” (SACEMS). “SACEVS with Margin” investigates the use of target 2X leverage via margin to boost the performance of the “Simple Asset Class ETF Value Strategy” (SACEVS). In response, a subscriber requested a sensitivity test of 1.25X, 1.50X and 1.75X leverage targets. To investigate effects of these leverage targets, we separately augment SACEVS Best Value, SACEMS EW Top 2 and the equally weighted combination of these two strategies by: (1) initially applying target leverage via margin; (2) for each month with a positive portfolio return, adding margin at the end of the month to restore target leverage; and, (3) for each month with a negative portfolio return, liquidating shares at the end of the month to pay down margin and restore target leverage. Margin rebalancings are concurrent with portfolio reformations. We focus on gross monthly Sharpe ratiocompound annual growth rate (CAGR) and maximum drawdown (MaxDD) for committed capital as key performance statistics. We use the 3-month Treasury bill (T-bill) yield as the risk-free rate. Using monthly total (dividend-adjusted) returns for the specified assets since July 2002 for SACEVS and since July 2006 for SACEMS, both through May 2022, we find that:

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SACEVS with Margin

Is leveraging with margin a good way to boost the performance of the “Simple Asset Class ETF Value Strategy” (SACEVS)? To investigate effects of margin, we augment SACEVS by: (1) initially applying 2X leverage via margin (limited by Federal Reserve Regulation T); (2) for each month with a positive portfolio return, adding margin at the end of the month to restore 2X leverage; and, (3) for each month with a negative portfolio return, liquidating shares at the end of the month to pay down margin and restore 2X leverage. Margin rebalancings are concurrent with portfolio reformations. We focus on gross monthly Sharpe ratiocompound annual growth rate (CAGR) and maximum drawdown (MaxDD) for committed capital as key performance statistics for Best Value (which picks the most undervalued premium) and Weighted (which weights all undervalued premiums according to degree of undervaluation) variations of SACEVS. We use the 3-month Treasury bill (T-bill) yield as the risk-free rate and consider a range of margin interest rates as increments to this yield. Using monthly total returns for SACEVS and monthly T-bill yields during July 2002 through May 2022, we find that:

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