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Equity Premium

Governments are largely insulated from market forces. Companies are not. Investments in stocks therefore carry substantial risk in comparison with holdings of government bonds, notes or bills. The marketplace presumably rewards risk with extra return. How much of a return premium should investors in equities expect? These blog entries examine the equity risk premium as a return benchmark for equity investors.

Reversions from Stock Market Valuation Extremes Drive the Value Premium?

Do extreme equity market valuations represent opportunities in value stocks? In their October 2020 paper entitled “Extrapolators at the Gate: Market-wide Misvaluation and the Value Premium”, Stefano Cassella, Zhaojing Chen, Huseyin Gulen and Ralitsa Petkova test the hypothesis that extrapolating (momentum) investors bid up growth stocks in good times and bid down value stocks in bad times, such that the value premium concentrates during reversion from these conditions. Their principal measure of market valuation is average book value-to-market capitalization ratio (B/M) of all firms, excluding financial stocks, utility stocks and stocks priced ice less than $1. When monthly B/M is in the top (bottom) 10% of monthly values for the past 10 years, they deem the market overvalued (undervalued). For robustness, they consider other percentage cutoffs and an alternative metric that quantifies the distance between the current-month distribution of firm B/Ms and the distributions of over the past 10 years based on the Mann-Whitney U test. They further tie findings to investor expectations based on a long times series constructed from Gallup, American Association of Individual Investors and Investor Intelligence surveys of investors. Using monthly returns and accounting data for U.S. common stocks and the specified survey data during January 1962 through December 2018, they find that:

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Are Currency Carry Trade ETFs Working?

Is the currency carry trade, as implemented by exchange-traded funds/notes (ETF/ETN), attractive? To investigate, we consider two currency carry trade ETF/ETNs, one live (with low trading volume) and one dead:

  • PowerShares DB G10 Currency Harvest Fund (DBV) – tracks changes in the Deutsche Bank G10 Currency Future Harvest Index. This index consists of futures contracts on certain G10 currencies with up to 2:1 leverage to exploit the tendency that currencies with relatively high interest rates tend to appreciate relative to currencies with relatively low interest rates, reconstituted annually in November.
  • iPath Optimized Currency Carry (ICITF) – provides exposure to the Barclays Optimized Currency Carry Index, which reflects the total return of a strategy that holds high-yielding G10 currencies financed by borrowing low-yielding G10 currencies. This fund stopped trading July 2018, but an indicative value is still available.

We focus on monthly return statistics, plus compound annual growth rates (CAGR) and maximum drawdowns (MaxDD). For reference (not benchmarking), we compare results to those for SPDR S&P 500 (SPY) and iShares Barclays 20+ Year Treasury Bond (TLT). Using monthly total returns for the two currency carry trade products, SPY and TLT as available through October 2020, we find that: Keep Reading

U.S. Economy and Equity Market Linkage Weakening?

How connected are principal measures of U.S. economic activity and U.S. stock market performance? In their October 2020 paper entitled “Has the Stock Market Become Less Representative of the Economy?”, Frederik Schlingemann and René Stulz model and measure relationships between market capitalizations of U.S. publicly listed firms and their contributions to U.S. employment and Gross Domestic Product (GDP). They estimate employment contribution directly based on firm reports, with modeled adjustments. They measure contribution to GDP based on firm value-add, approximated as operating income before depreciation plus labor costs (with labor costs often modeled). They also try other ways of measuring value-add. Using annual non-farm employment and GDP data for the U.S., annual employment and value-add data for U.S. publicly listed firms and annual stock prices for those firms during 1973 (limited by firm employment data) through 2019, they find that:

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Testing for Trends in Trending for U.S. Stocks and Bonds

“Market Impacts of Growth in Target Date Funds” summarizes research on potential market-wide effects of periodic rebalancing actions of Target Date Funds (TDF), which trade against momentum. One piece of evidence is that monthly autocorrelation of S&P 500 Index returns is significantly negative during 2010-2019 but not during 1986-1995 or 1996-2005. Another is that TDFs accomplish most of quarterly rebalancing within the next quarter. To assess how convincing autocorrelation findings are, we calculate rolling 5-year monthly (60-month) and quarterly (20-calendar quarter) autocorrelations of returns for:

Using monthly total (dividend-reinvested) returns for these three assets through October 2020, we find that: Keep Reading

Market Impacts of Growth in Target Date Funds

Are aggregate periodic stocks-bonds rebalancing actions of Target Date Funds (TDF), which trade against momentum, increasingly affecting U.S. stock market dynamics? In their October 2020 paper entitled “Retail Financial Innovation and Stock Market Dynamics: The Case of Target Date Funds”, flagged by a subscriber, Jonathan Parker, Antoinette Schoar and Yang Sun examine market impacts of Target Date Funds (TDFs), assets of which have grown from less than $8 billion in 2000 to more than $2.3 trillion (of roughly $21 trillion in U.S. mutual funds) in 2019. Using quarterly data on TDF holdings, monthly U.S. stock market and Vanguard Total Bond Market Index Fund (bond market) returns and monthly data for stocks held by and similar to those held by TDFs during the third quarter of 2008 through the fourth quarter of 2018 (excluding three quarters with suspect data), they find that:

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Three High-attention Earnings Announcement Clusters Drive Market?

Does the U.S. stock market respond predictably to simultaneous earnings announcements of attention-grabbing companies? In their September 2020 paper entitled “Famous Firms, Earnings Clusters, and the Stock Market”, Yixin Chen, Randolph Cohen and Zixuan Wang examine U.S. stock market (E-mini S&P 500 futures) responses to earnings announcement clusters (EAC) comprised of high-attention firms. They focus on the three most prominent pre-open (AM) and three most prominent post-close (PM) EACs in each of January, April, July and October, with each announcement weighted for prominence by associated total number of Dow Jones earnings news articles during the prior calendar year. Using earnings announcements and daily prices for S&P 500 components and minute-by-minute E-mini S&P 500 futures returns during 1999-2018, and associated earnings news articles during 1998-2018, they find that: Keep Reading

Stocks for the Long Run Internationally

Are buy-and-hold stock market returns attractive over the long run globally? In their May 2020 paper entitled “Stocks for the Long Run? Evidence from a Broad Sample of Developed Markets”, Aizhan Anarkulova, Scott Cederburg and Michael O’Doherty apply a stationary block bootstrap procedure (retaining some time series features) to generate distributions of 1,000,000 each 1-month to 30-year real returns across global equity markets. They mitigate survivorship and easy data biases via broad coverage of developed countries and inclusion of market interruptions. They focus on a long-term (30-year) investment horizon, with returns accumulated in local currencies. Using monthly total (dividend-reinvested) equity index returns and consumer price indexes for 39 developed countries as available according to certain criteria during January 1841 through December 2019, they find that: Keep Reading

Behaviors and Characteristics of Top Stocks

What are typical return behaviors and firm characteristics of the best-performing and worst-performing U.S. stocks at a 10-year horizon? In his July 2020 series of papers entitled “Extreme Stock Market Performers”, Part I: Expect Some Drawdowns, Part II: Do Technology Stocks Dominate?, Part III: What are their Observable Characteristics? and Part IV: Can Observable Characteristics Forecast Outcomes?, Hendrik Bessembinder investigates returns and firm characteristics of stocks that generate the most and least total shareholder wealth (are the “best” and “worst” stocks) in each decade since 1950. Total shareholder wealth generation incorporates both cumulative return and market capitalization. Using monthly returns, market capitalizations and firm characteristics for U.S. stocks for each decade during 1950 through 2019, he finds that: Keep Reading

Best Stock Return Anomaly Double Sorts?

Are portfolios of U.S. stocks that are double-sorted to capture benefits of two complementary return anomalies attractive? In their July 2020 paper entitled “Interacting Anomalies”, Karsten Müller and Simon Schmickler test all possible double-sorted portfolios across 102 stock return anomalies (10,302 double-sorts). They employ 5×5 double-sorts, first ranking stocks into fifths (quintiles) for one anomaly and then re-sorting each of these quintiles into fifths for the second anomaly. They focus on the four “corner” portfolios involving the extreme high and low quintiles for both anomalies. They evaluate average returns, Sharpe ratios and factor model alphas of both equal-weighted (EW) and value-weighted (VW) versions of these portfolios, emphasizing performance gains from anomaly interactions. They correct for multiple hypothesis testing (data snooping bias) using the Bonferroni correction. Using trading and accounting data for a broad sample of U.S. common stocks with annual (quarterly) accounting data lagged by six (four) months during 1970 through 2017, they find that:

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Ending with the Beginning in Mind

How should investors think about the interactions between working years (retirement account contributions) and retirement years (retirement account withdrawals)? In his June 2020 paper entitled “Retirement Planning: From Z to A”, Javier Estrada integrates working and retirement periods to estimate how much an individual should save and how they should invest to achieve a desired retirement income and ultimate bequest to heirs. He illustrates his analytical solution empirically for U.S. stocks and bonds, first using a base case plus sensitivity analysis and then using Monte Carlo simulations. His base case assumes:

  • Work will last 40 years with a 60%/40% stocks/bonds retirement portfolio.
  • Retirement will last 30 years with beginning-of-year real (inflation-adjusted) withdrawals of $60,000 from a 40%/60% stocks/bonds retirement portfolio and ultimate bequest $300,000.

Using annual data for U.S. stocks (the S&P 500 Index total return), bonds (10-year U.S. Treasury notes) and U.S. inflation during 1928 through 2019, he finds that: Keep Reading

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