Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for April 2021 (Final)

Momentum Investing Strategy (Strategy Overview)

Allocations for April 2021 (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.

Stock Market Valuation Ratio Trends

To determine whether the stock market is expensive or cheap, some experts use aggregate valuation ratios, either trailing or forward-looking, such as earnings-price ratio (E/P) and dividend yield. Under belief that such ratios are mean-reverting, most imminently due to movement of stock prices, these experts expect high (low) future stock market returns when these ratios are high (low). Where are the ratios now and how are they changing during recent months? Using recent actual and forecasted earnings and dividend data from Standard & Poor’s and associated S&P 500 Index levels, we find that: Keep Reading

Stock Market Earnings Yield and Inflation Over the Long Run

How does the U.S. stock market earnings yield (inverse of price-to-earnings ratio, or E/P) interact with the U.S. inflation rate over the long run? Is any such interaction exploitable? To investigate, we employ the long run dataset of Robert Shiller. Using monthly data for the S&P Composite Stock Index, estimated aggregate trailing 12-month earnings and dividends for the stocks in this index, and estimated U.S. Consumer Price Index (CPI) during January 1871 through February 2021 (over 150 years), and estimated monthly yield on 1-year U.S. Treasury bills (T-bills) since January 1951, 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 February 2021, we find that:

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Effects of Capitalizing Intangibles on Factor Models of Stock Returns

Under current U.S. accounting rules, many investments in innovation, human resources and brand that are crucial to long-term competitiveness immediately reduce operating profits and earnings (are expensed rather than capitalized). Does failure to incorporate such intangible investments in firm investment and valuation ratios (book-to-market, profitability and return on equity) harm equity investment decisions? In their January 2021 paper entitled “Intangible Capital in Factor Models”, Huseyin Gulen, Dongmei Li, Ryan Peters and Morad Zekhnini study impacts of capitalizing intangible investments on three widely used factor models of stock returns: 3-factor (market, size, book-to-market)5-factor (adding profitability and investment); and, q-factor (market, size, investment, profitability). They focus on effects of intangibles on book-to-market ratio, investment and profitability. Using accounting data and stock returns for a broad sample of U.S. firms during July 1977 through December 2018, they find that: Keep Reading

Poor Firm Management and Stock Returns

Do negative environmental, social and governance (ESG) incidents (environmental pollution,
poor employment conditions or anti-competitive practices) indicate poor firm management and therefore underperforming stocks? In his February 2021 paper entitled “ESG Incidents and Shareholder Value”, Simon Glossner analyzes ESG incident data to determine whether: (1) history is predictive of future ESG incidents; (2) high incident rates impact firm performance: and, (3) the stock market prices incidents. Using over 80,000 incident news items, firm information and stock returns for 2,848 unique U.S. public firms starting January 2007 and a smaller sample for European firms starting January 2009, all through December 2017, he finds that: Keep Reading

Remaking Value Investing

Value investing performance over the past two decades is poor. Is this underperformance a temporary consequence of an unusual macro environment, or a reflection of permanent economic/equity market changes. In their February 2021 paper entitled “Value Investing: Requiem, Rebirth or Reincarnation?”, Bradford Cornell and Aswath Damodaran survey the history and alternative approaches to value investing, with focus on its failure in recent decades. They then discuss how value investing must adapt to recover. Based on the body of value investing research through 2020, they conclude that: Keep Reading

Valuation-based Stock Market Return Expectations

What performance should investors expect from the S&P 500 Index based on price-to-earnings (P/E) and Cyclically-Adjusted Price-to-Earnings (CAPE, or P/E10)? In their November 2020 paper entitled “Extreme Valuations and Future Returns of the S&P 500”, Shaun Rowles and Andrew Mitchell take a layered “regression upon a regression” approach to predict S&P 500 Index returns and level. First, to estimate future returns, they run a linear regression on P/E, P/E10, S&P 500 dividend yield, inflation, 10-year U.S. Treasury note yield, historical 1-year, 3-year, 5-year and 10-year S&P 500 Index returns and percentiles of many of these variables within their respective historical distributions. Then, they run separate linear regressions to predict 1-year, 3-year, 5-year and 10-year future annualized returns. Finally, they run a linear regression to model current S&P 500 Index level for comparison to actual current level. Using Robert Shiller’s U.S. stock market and economic data spanning January 1871 through June 2020, they find that: Keep Reading

SACEVS with SMA Filter

The “Simple Asset Class ETF Value Strategy” (SACEVS) allocates across 3-month Treasury bills (Cash, or T-bill), iShares 20+ Year Treasury Bond (TLT), iShares iBoxx $ Investment Grade Corporate Bond (LQD) and SPDR S&P 500 (SPY) according to the relative valuations of term, credit and equity risk premiums. Does applying a simple moving average (SMA) filter to SACEVS allocations improve its performance? Since many technical traders use a 10-month SMA (SMA10), we apply SMA10 filters to dividend-adjusted prices of TLT, LQD and SPY allocations. If an allocated asset is above (below) its SMA10, we allocate as specified (to Cash). This rule does not apply to any Cash allocation. We focus on gross compound annual growth rates (CAGR), maximum drawdowns (MaxDD) and annual Sharpe ratios (using average monthly T-bill yield during a year as the risk-free rate for that year) of SACEVS Best Value and SACEVS Weighted portfolios. We compare to baseline SACEVS as currently tracked and to the SMA rule applied to a 60%-40% monthly rebalanced SPY-TLT benchmark portfolio (60-40). Finally, we test sensitivity of main findings to varying the SMA lookback interval. Using SACEVS historical data, monthly dividend-adjusted closing prices for the asset class proxies and yield for Cash during July 2002 (the earliest all funds are available) through December 2020, we find that:

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Intangible Value Factor

Intangible assets derive largely from investments in employees, brand and knowledge that are expensed rather than booked. Despite large and growing importance of intangible assets, traditional measures of firm value ignore them. Are firm value assessments therefore defective? In their October 2020 paper entitled “Intangible Value”, Andrea Eisfeldt, Edward Kim and Dimitris Papanikolaou evaluate a value factor that includes intangible assets in book equity for each firm (HMLINT) following exactly the methodology used to construct the widely accepted Fama-French value factor (HMLFF). They measure intangible assets based on flows of Selling, General, and Administrative (SG&A) expenses. Using firm accounting data and associated monthly stock returns and Fama-French 5-factor model data for a broad sample of U.S. stocks during January 1975 through December 2018, they find that:

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Timing GBTC Based on Its Inferred Premium

“Evolution of Bitcoin as an Investment” suggests a shift toward acceptance of Bitcoin (BTC) as an investment asset, as do recent actions by some large investors. Grayscale Bitcoin Trust (GBTC) offers a way for investors to access BTC via a fund that manages BTC holdings. GBTC price generally carries a premium over its BTC holdings in consideration for this convenience (17% as of the end of 2020). Does variation in this premium indicate good times to buy and sell GBTC? To investigate, we use the ratio GBTC/BTC (with BTC divided by 1,000 because the prices greatly differ in scale) as an easy way to infer the premium. We then look at ways to exploit variation in the ratio to buy and sell GBTC. Because of the rapid evolution of Bitcoin, we limit analysis to recent data. Using daily closing prices of GBTC and BTC during 2019 through 2020, we find that: Keep Reading

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