Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for April 2024 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for April 2024 (Final)
1st ETF 2nd ETF 3rd ETF

Bonds

Bonds have two price components, yield and response of price to prevailing interest rates. How much of a return premium should investors in bonds expect? How can investors enhance this premium? These blog entries examine investing in bonds.

Recent Interactions of Asset Classes with Economic Policy Uncertainty

How do returns of different asset classes recently interact with uncertainty in government economic policy as quantified by the Economic Policy Uncertainty (EPU) Index? This index at the beginning of each month incorporates from the prior month:

  1. Coverage of policy-related economic uncertainty by prominent newspapers (50% weight).
  2. Number of temporary federal tax code provisions set to expire in future years (one sixth weight).
  3. Level of disagreement in one-year forecasts among participants in the Federal Reserve Bank of Philadelphia’s Survey of Professional Forecasters for both (a) the consumer price index (one sixth weight) and (b) purchasing of goods and services by federal, state and local governments (one sixth weight).

Because the historical EPU Index series includes substantial revisions to prior months, we focus on monthly percentage changes in EPU Index and look at lead-lag relationships between change in EPU Index and returns for each of the following 10 exchange-traded fund (ETF) asset class proxies:

  • Equities:
    • SPDR S&P 500 (SPY)
    • iShares Russell 2000 Index (IWM)
    • iShares MSCI EAFE Index (EFA)
    • iShares MSCI Emerging Markets Index (EEM)
  • Bonds:
    • iShares Barclays 20+ Year Treasury Bond (TLT)
    • iShares iBoxx $ Investment Grade Corporate Bond (LQD)
    • iShares JPMorgan Emerging Markets Bond Fund (EMB)
  • Real assets:
    • Vanguard REIT ETF (VNQ)
    • SPDR Gold Shares (GLD)
    • Invesco DB Commodity Index Tracking (DBC)

Using monthly levels of the EPU Index and monthly dividend-adjusted prices for the 10 specified ETFs during December 2007 (limited by EMB) through December 2021, we find that: Keep Reading

Recent Interactions of Asset Classes with Inflation (PPI)

How do returns of different asset classes recently interact with inflation as measured by monthly change in the not seasonally adjusted, all-commodities producer price index (PPI) from the U.S. Bureau of Labor Statistics? To investigate, we look at lead-lag relationships between change in PPI and returns for each of the following 10 exchange-traded fund (ETF) asset class proxies:

  • Equities:
    • SPDR S&P 500 (SPY)
    • iShares Russell 2000 Index (IWM)
    • iShares MSCI EAFE Index (EFA)
    • iShares MSCI Emerging Markets Index (EEM)
  • Bonds:
    • iShares Barclays 20+ Year Treasury Bond (TLT)
    • iShares iBoxx $ Investment Grade Corporate Bond (LQD)
    • iShares JPMorgan Emerging Markets Bond Fund (EMB)
  • Real assets:
    • Vanguard REIT ETF (VNQ)
    • SPDR Gold Shares (GLD)
    • Invesco DB Commodity Index Tracking (DBC)

Using monthly total PPI values and monthly dividend-adjusted prices for the 10 specified ETFs during December 2007 (limited by EMB) through December 2021, we find that: Keep Reading

SACEVS with Quarterly Allocation Updates

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 2021, we find that:

Keep Reading

Quit Rate and Future Asset Returns

Does the U.S. employment quit rate, a measurement from the Job Openings and Labor Turnover Survey run monthly by the U.S. Bureau of Labor Statistics, have implications for future U.S. stock market or U.S. Treasury bond return? A high (low) quit rate may indicate a strong (weak) economy and/or may signal high (low) wage inflation. To investigate, we relate quit rate to future performance of SPDR S&P 500 (SPY) as a proxy for the stock market and of iShares 20+ Year Treasury Bond (TLT) as a proxy for government bonds. Using monthly quit rate (which has a release delay of about six weeks) during December 2000 through August 2021 and monthly dividend-adjusted returns for SPY and TLT as available during December 2000 through September 2021, we find that: Keep Reading

Testing a Countercyclical Asset Allocation Strategy

“Countercyclical Asset Allocation Strategy” summarizes research on a simple countercyclical asset allocation strategy that systematically raises (lowers) the allocation to an asset class when its current aggregate allocation is relatively low (high). The underlying research is not specific on calculating portfolio allocations and returns. To corroborate findings, we use annual mutual fund and exchange-traded fund (ETF) allocations to stocks and bonds worldwide from the 2021 Investment Company Fact Book, Data Tables 3 and 11 to determine annual countercyclical allocations for stocks and bonds (ignoring allocations to money market funds). Specifically:

  • If actual aggregate mutual fund/ETF allocation to stocks in a given year is above (below) 60%, we set next-year portfolio allocation below (above) 60% by the same percentage.
  • If actual aggregate mutual fund/ETF allocation to bonds in a given year is above (below) 40%, we set next-year portfolio allocation below (above) 40% by the same percentage.

We then apply next-year allocations to stock (Fidelity Fund, FFIDX) and bond (Fidelity Investment Grade Bond Fund, FBNDX) mutual funds that have long histories. Based on Fact Book annual publication dates, we rebalance at the end of April each year. Using the specified actual fund allocations for 1984 through 2020 and FFIDX and FBNDX May through April total returns and end-of-April 1-year U.S. Treasury note (T-note) yields for 1985 through 2021, we find that: Keep Reading

Update of Credit as a Tactical Asset Allocation Signal

Do credit portfolio managers adjust their portfolios more expeditiously than equity managers, thereby offering a means to time the equity market? In his August 2021 paper entitled “Credit-Informed Tactical Asset Allocation – 10 Years On”, David Klein updates and enhances the strategy presented in his paper of June 2011 (see “Credit as a Tactical Asset Allocation Signal”). The strategy holds stocks (short-term Treasuries) when stocks appear undervalued (overvalued) relative to corporate bonds based on data from a rolling 6-month historical interval. His proxy for corporate bonds is the ICE BofA Single-B US High Yield Index Option-Adjusted Spread (converted to a default probability) and for stocks is the Russell 2000 Index (with dividends). He hypothesizes that stock prices tend to fall when credit spread widens, and small capitalization stocks are more sensitive to credit conditions than large capitalization stocks. Two enhancements to the original strategy are: (1) shorten the lookback from six to three months; and (2) increase the equity allocation by adding a premium to equity values. A third enhancement is taking a 120% long position in stocks when they are undervalued and a 20% short position in stocks when they are overvalued (with 2% estimated annual costs for implementation). Updating and enhancing this strategy with 10 years of new daily data through June 2021, he finds that:

Keep Reading

Credit Spread as an Asset Return Predictor

A reader commented and asked: “A wide credit spread (the difference in yields between Treasury notes or Treasury bonds and investment grade or junk corporate bonds) indicates fear of bankruptcies or other bad events. A narrow credit spread indicates high expectations for the economy and corporate world. Does the credit spread anticipate stock market behavior?” To investigate, we define the U.S. credit spread as the difference in yields between Moody’s seasoned Baa corporate bonds and 10-year Treasury notes (T-note), which are average daily yields for these instruments by calendar month (a smoothed measurement). We use the S&P 500 Index (SP500) as a proxy for the U.S. stock market. We extend the investigation to bond market behavior via:

Using monthly Baa bond yields, T-note yields and SP500 closes starting April 1953 and monthly dividend-adjusted closes of VUSTX, VWESX and VWEHX starting May 1986, January 1980 and January 1980, respectively, all through June 2021, we find that: Keep Reading

Real Interest Rates and Asset Returns

How sensitive are returns of stocks, bonds and gold to levels real interest rates (nominal rates minus inflation)? To investigate, we consider three nominal interest rates and two measures of inflation, as follows:

These choices offer six alternative real interest rates. We use end-of-month interest rates and inflation measures lagged by one month to account for release delay. We use the S&P 500 Index (SP500) capital gain only, the 10-year yield (with bond prices moving inversely) and spot gold price, all measured end-of-month, to represent returns for stocks, bonds and gold. We then relate monthly changes in real interest rates to asset class monthly returns in two ways: (1) calculate correlations of monthly real interest rates to asset class returns for each of the next 12 months to get a sense of how real rates lead asset returns; and, (2) calculate average asset class monthly returns by ranked tenths (deciles) of prior-month real interest rates to discover any non-linear relationships. Using monthly PCEPI and Core PCEPI since January 1961, interest rates since January 1962, SP500 level since December 1961 and spot gold price since December 1974 (when controls are removed), all through May 2021, we find that:

Keep Reading

Real Bond Returns and Inflation

A subscriber asked (years ago): “Everyone says I should not invest in bonds today because the interest rate is so low (and inflation is daunting). But real bond returns over the last 30 years are great, even while interest rates are low. Could you analyze why bonds do well after, but not before, 1981?” To investigate, we consider the U.S. long-run interest rate and the U.S. Consumer Price Index (CPI) series from Robert Shiller. The long-run interest rate is the yield on U.S. government bonds, specifically the constant maturity 10-year U.S. Treasury note after 1953. We use the term “T-note” loosely to name the entire series. We apply the formula used by Aswath Damodaran to the yield series to estimate nominal T-note total returns. We use 12-month change in CPI. We subtract inflation from T-note nominal total return to get T-note real total return. Using annual Shiller interest rate and CPI data for 1871 through 2020, we find that: Keep Reading

Seasonal Timing of Monthly Investment Increments

A subscriber requested evaluation of three retirement investment alternatives, assuming a constant increment invested at the end of each month, as follows:

  1. 50-50: allocate each increment via fixed percentages to stocks and bonds (for comparability, we use 50% to each).
  2. Seasonal 1: during April through September (October through March), allocate 100% of each increment to stocks (bonds).
  3. Seasonal 2: during April through September (October through March), allocate 100% of each increment to bonds (stocks).

The hypothesis is that seasonal variation in asset class allocations could improve overall long-term investment performance. We conduct a short-term test using SPDR S&P 500 ETF Trust (SPY) as a proxy for stocks and iShares iBoxx $ Investment Grade Corporate Bond ETF (LQD) as a proxy for bonds. We then conduct a long-term test using Vanguard 500 Index Fund Investor Shares (VFINX) as a proxy for stocks and Vanguard Long-Term Investment-Grade Fund Investor Shares (VWESX) as a proxy for bonds. Based on the setup, we focus on terminal value as the essential performance metric. Using total (dividend-adjusted) returns for SPY and LQD since July 2002 and for VFINX and VWESX since January 1980, all through December 2020, we find that: Keep Reading

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