Equity Premium

What are asset class return expectations and associated portfolio allocations of very sophisticated U.S. investors? In their February 2019 paper entitled “The Return Expectations of Institutional Investors”, Aleksandar Andonov and Joshua Rauh analyze disclosures of expected returns across asset classes among U.S. public pension funds, which hold assets of about $4 trillion (see the first chart below), including fixed income, cash, equities, real assets, hedge funds, private equity and other asset classes. Taking into account past fund performance, they investigate how fund managers estimate future returns. Disclosures also reveal target allocations to asset classes (see the second chart below). Together, expected asset class returns and target allocations allow calculation of expected portfolio returns. Using annual disclosures for 228 U.S. state and local government pension plans during 2014 through 2017, they find that:

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What happens if we extend the “Simple Asset Class ETF Value Strategy” (SACEVS) with a real estate risk premium, derived from the yield on equity Real Estate Investment Trusts (REIT), represented by the FTSE NAREIT Equity REITs Index? To investigate, we apply the SACEVS methodology to the following asset class exchange-traded funds (ETF), plus cash:

3-month Treasury bills (Cash)
iShares 20+ Year Treasury Bond (TLT)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
SPDR Dow Jones REIT (RWR) through September 2004 dovetailed with Vanguard REIT ETF (VNQ) thereafter
SPDR S&P 500 (SPY)

This set of ETFs relates to four risk premiums, as specified below: (1) term; (2) credit (default); (3) real estate; and, (4) equity. We focus on the effects of adding the real estate risk premium on Compound annual growth rates (CAGR) and Maximum drawdowns (MaxDD) of the Best Value (picking the most undervalued premium) and Weighted (weighting all undervalued premiums according to degree of undervaluation) versions of SACEVS. Using lagged quarterly S&P 500 earnings, monthly S&P 500 Index levels and monthly yields for 3-month U.S. Treasury bill (T-bill), the 10-year Constant Maturity U.S. Treasury note (T-note), Moody’s Seasoned Baa Corporate Bonds and FTSE NAREIT Equity REITs Index during March 1989 through August 2018 (limited by availability of earnings data), and monthly dividend-adjusted closing prices for the above asset class ETFs during July 2002 through September 2019, we find that: Keep Reading

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 essentially 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 about 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 September 2019, we find that: Keep Reading

Do quarterly allocation updates for the Best Value and Weighted versions of the “Simple Asset Class ETF Value Strategy” (SACEVS) work as well as monthly updates? These strategies allocate funds to the following asset class exchange-traded funds (ETF) according to valuations of term, credit and equity risk premiums, or to cash if no premiums are undervalued:

3-month Treasury bills (Cash)
iShares 20+ Year Treasury Bond (TLT)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
SPDR S&P 500 (SPY)

Changing from monthly to quarterly allocation updates does not sacrifice information about lagged quarterly S&P 500 Index earnings, but it does sacrifice currency of term and credit premiums. To assess alternatives, we compare cumulative performances and the following key metrics for quarterly and monthly allocation updates: gross compound annual growth rate (CAGR), gross maximum drawdown (MaxDD), annual gross returns and volatilities and annual gross Sharpe ratios. Using monthly dividend-adjusted closes for the above ETFs during September 2002 (earliest alignment of months and quarters) through September 2019, we find that:

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How different are stock market performance metrics for:

• Capital gains only, capital gains plus dividends accrued as cash (spent or saved), and capital gains plus dividends reinvested in the stock market?
• Nominal versus real returns?
• Simple return-to-risk calculations versus Sharpe ratio?

Using quarterly S&P 500 Index levels and dividends, quarterly U.S. Consumer Price Index (CPI) data (all items) and monthly 3-month U.S. Treasury bill (T-bill) yield as the risk-free rate/return on cash during the first quarter of 1988 through the second quarter of 2019, we find that: Keep Reading

Is the conventional wisdom that exchange-traded funds (ETF) are efficient, low-cost alternatives to mutual funds correct? In their September 2019 paper entitled “The Performance of Exchange-Traded Funds”, David Blitz and Milan Vidojevic evaluate the performance of a comprehensive, survivorship bias-free sample of U.S. equity ETFs. They first divide the sample into three groups: (1) broad market index trackers; (2) inverse and leveraged funds; and, (3) others. They then subdivide group 3 into equity factor subgroups (small, value, dividend, momentum, quality or low-risk) based on either their names or their empirical exposures to widely accepted factor premiums. Finally, they compare performances of value-weighted ETF groups to those of the broad U.S. stock market and specified factors, focusing on data starting January 2004 when there are at least 100 ETFs of some variety. Using trading data and descriptions for 918 U.S. equity ETFs (642 live and 276 dead by the end of the sample period) and equity factor returns during January 1993 through December  2017, they find that: Keep Reading

Are equity multifactor strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider seven ETFs, all currently available (in order of decreasing assets):

• Goldman Sachs ActiveBeta U.S. Large Cap Equity (GSLC) – holds large U.S. stocks based on good value, strong momentum, high quality and low volatility.
• iShares Edge MSCI Multifactor International (INTF) – holds global developed market ex U.S. large and mid-cap stocks based on quality, value, size and momentum, while maintaining a level of risk similar to that of the market.
• John Hancock Multifactor Mid Cap (JHMM) – holds mid-cap U.S. stocks based on smaller capitalization, lower relative price and higher profitability, which academic research links to higher expected returns.
• iShares Edge MSCI Multifactor USA (LRGF) – holds large and mid-cap U.S. stocks with focus on quality, value, size and momentum, while maintaining a level of risk similar to that of the market.
• John Hancock Multifactor Large Cap (JHML) – holds large U.S. stocks based on smaller capitalization, lower relative price and higher profitability, which academic research links to higher expected returns.
• JPMorgan Diversified Return U.S. Equity (JPUS) – holds U.S. stocks based on value, quality and momentum via a risk-weighting process that lowers exposure to historically volatile sectors and stocks.
• Xtrackers Russell 1000 Comprehensive Factor (DEUS) – seeks to track, before fees and expenses, the Russell 1000 Comprehensive Factor Index, which seeks exposure to quality, value, momentum, low volatility and size factors.

Because available sample periods are very short, we focus on daily return statistics, along with cumulative returns. We use four benchmarks according to fund descriptions: SPDR S&P 500 (SPY), iShares MSCI ACWI ex US (ACWX), SPDR S&P MidCap 400 (MDY) and iShares Russell 1000 (IWB). Using daily returns for the seven equity multifactor ETFs and benchmarks as available through September 2019, we find that: Keep Reading

Do bonds have a bad rap based on an unfavorable subsample? In the September 2019 revisions of his papers entitled “The US Bond Market Before 1926: Investor Total Return from 1793, Comparing Federal, Municipal, and Corporate Bonds Part I: 1793 to 1857” and “Part II: 1857 to 1926”, Edward McQuarrie revisits analysis of returns to bonds in the U.S. prior to 1926. He focuses on investor holding period returns rather than yields, considering U.S. Treasury, state, city and corporate debt. Specifically, he estimates returns to a 19th century diversified bond portfolio comprised of all long-term investment grade bonds trading in any year (free of contaminating factors such as circulation privileges and tax exemptions). Returns assume:

1. Weights are proportional to amounts outstanding.
2. Bonds are far from before maturity.
3. Calculations use actual bond prices.

In other words, he calculates performance of a diversified index fund tracking actual long-term, investment-grade 19th century U.S. bonds. He also calculates returns to sub-indexes as feasible. He further constructs a new stock index for the period January 1793 to January 1871 and revisits conclusions in Stocks for the Long Run about relative performances of stocks and bonds. Using newly and previously compiled U.S. bond and stock prices extending back to January 1793, he finds that:

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How should global investors assess country sovereign bond and equity risks? In his July 2019 paper entitled “Country Risk: Determinants, Measures and Implications – The 2019 Edition”, Aswath Damodaran examines country risk from multiple perspectives. He provides an overview of sources and measures of country risk, addressing both sovereign bond default risk and equity risk premiums. Based on a variety of sources and methods, he concludes that: Keep Reading

A subscriber wondered whether U.S. stock market movements predict Federal Funds Rate (FFR) actions taken by the Federal Reserve open market operations committee. To investigate and evaluate usefulness of findings, we relate three series:

1. FFR actions per the above source, along with recent and historical committee meeting dates.
2. S&P 500 Index returns.
3. Changes in yield for the 10-Year U.S. Constant Maturity Treasury note (T-note).

In constructing the first series, for Federal Reserve open market operations committee meeting dates which do not produce FFR changes, we quantify committee actions as 0%. We ignore committee conference calls that result in no changes in FFR. We calculate the second and third series between committee meeting dates because that irregular interval represents new information to the committee and potential exploitation points for investors. Using data for the three series during January 1990 through early August 2019, we find that:

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