Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for July 2024 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for July 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.

Best Safe Haven ETF?

A subscriber asked which exchange-traded fund (ETF) asset class proxies make the best safe havens for the U.S. stock market as proxied by the S&P 500 Index. To investigate, we test 15 ETFs/funds as potential safe havens:

Utilities Select Sector SPDR Fund (XLU)
iShares 20+ Year Treasury Bond (TLT)
iShares 7-10 Year Treasury Bond (IEF)
iShares 1-3 Year Treasury Bond (SHY)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
iShares Core US Aggregate Bond (AGG)
iShares TIPS Bond (TIP)
Vanguard Real Estate Index Fund (VNQ)
SPDR Gold Shares (GLD)
Invesco DB Commodity Index Tracking Fund (DBC)
United States Oil Fund, LP (USO)
iShares Silver Trust (SLV)
Invesco DB G10 Currency Harvest Fund (DBV)
SPDR Bloomberg Barclays 1-3 Month T-Bill (BIL)
Grayscale Bitcoin Trust (GBTC)

We consider three ways to find safe havens for the U.S. stock market based on daily or monthly returns:

  1. Contemporaneous return correlation with the S&P 500 Index during all market conditions at daily and monthly frequencies.
  2. Performance during S&P 500 Index bear markets as defined by the index being below its 10-month simple moving average (SMA10) at the end of the prior month.
  3. Performance during S&P 500 Index bear markets as defined by the index being -20%, -15% or -10% below its most recent peak at the end of the prior month.

Using daily and monthly dividend-adjusted closing prices for the above 15 funds since their respective inceptions, and contemporaneous daily and monthly levels of the S&P 500 Index since 10 months before the earliest inception, all through April 2022, we find that: Keep Reading

Economic Surprise Momentum

How should investors think about surprises in economic data? In their March 2022 paper entitled “Caught by Surprise: How Markets Respond to Macroeconomic News”, Guido Baltussen and Amar Soebhag devise and investigate a real-time aggregate measure of surprises in economic (not financial) variables around the world. Each measurement for each variable consists of release date/time, initial as-released value, associated consensus (median) forecast, number and standard deviation of individual forecasts and any revision to the previous as-released value across U.S., UK, the Eurozone and Japan markets from the Bloomberg Economic Calendar. They classify variables as either growth-related or inflation-related. They apply recursive principal component analysis to aggregate individual variable surprises separately into daily nowcasts of initial growth-related and inflation-related announcement surprises and associated revision surprises. They investigate the time series behaviors of these nowcasts and then examine their interactions with returns for four asset classes:

  1. Stocks via prices of front-month futures contracts rolled the day before expiration for S&P 500, FTSE 100, Nikkei 225 and Eurostoxx 50 indexes.
  2. Government bonds via prices of front-month futures contracts rolled the day before first notice on U.S., UK, Europe and Japan 10-year bonds.
  3. Credit via returns on 5-year credit default swaps for U.S. and Europe investment grade and high yield corporate bond indexes.
  4. Commodities via excess returns for the Bloomberg Commodity Index.

Specifically, they test an investment strategy that takes a position equal to the 1-day lagged value of the growth surprise nowcast or the inflation surprise nowcast on the last trading day of each month. They pool regions within an asset class by equally weighting regional markets. Using daily as-released data for 191 economic variables across global regions and the specified monthly asset class price inputs during March 1997 through December 2019, they find that: Keep Reading

Overnight Effect Across Asset Classes?

Does the overnight return effect found pervasively among equity markets, as summarized in “Persistence of Overnight/Intraday Equity Market Return Patterns”, also hold for other asset classes? To investigate, we compare open-to-close (O-C) and close-to-open (C-O) average returns, standard deviations of returns and cumulative performances for the exchange-traded funds (ETF) used as asset class proxies in the Simple Asset Class ETF Momentum Strategy (SACEMS). Using daily dividend-adjusted opening and closing prices of these ETFs during mid-December 2007 (inception of the youngest ETF) through early March 2022, we find that: Keep Reading

Best Bear Market Asset Class?

A subscriber asked which asset (short stocks, cash, bonds by subclass) is best to hold during equity bear markets. To investigate, we consider two ways to define a bear market: (1) months when SPDR S&P 500 (SPY) is below its 10-month simple moving average (SMA10) at the end of the prior month; and, (2) months when SPY is in drawdown by at least 20% from a high-water mark at the end of the prior month. We consider nine alternative assets:

  1. Short SPY
  2. Cash, estimated using the yield on 3-month U.S. Treasury bills (T-bill)
  3. Vanguard GNMA Securities (VFIIX)
  4. T. Rowe Price International Bonds (RPIBX)
  5. Vanguard Long-Term Treasury Bonds (VUSTX)
  6. Fidelity Convertible Securities (FCVSX)
  7. T. Rowe Price High-Yield Bonds (PRHYX)
  8. Fidelity Select Gold Portfolio (FSAGX)
  9. Spot Gold

Specifically, we compare monthly return statistics, compound annual growth rates (CAGR) and maximum (peak-to-trough) drawdowns (MaxDD) of these nine alternatives during bear market months. Using monthly T-bill yield and monthly dividend-adjusted closing prices for the above assets during January 1993 (as limited by SPY) through February 2022, we find that: Keep Reading

Alternative Yield Discount (Inflation) Rates

Investors arguably expect that investments generate returns in excess of the inflation rate. Do different measures of the inflation rate indicate materially different yield discounts? To investigate, we relate 12-month trailing S&P 500 annual operating earnings yield (E/P), S&P 500 12-month trailing annual dividend yield, 10-year U.S. Treasury note (T-note) yield and 3-month U.S. Treasury bill (T-bill) yield to four measures of annual U.S. inflation rate:

  1. Non-seasonally adjusted inflation rate based on the total Consumer Price Index (CPI) from the Bureau of Labor Statistics (retroactive revisions of seasonal adjustments interfere with historical analysis).
  2. Non-seasonally adjusted inflation rate based on core CPI from the Bureau of Labor Statistics.
  3. Inflation rate based on the Personal Consumption Expenditures: Chain-type Price Index (PCE) from the Federal Reserve Bank of St. Louis.
  4. Trimmed mean PCE from the Federal Reserve Bank of Dallas.

The CPI measurements have a delay of about two weeks, and the PCE measurements have a delay of about a month. Using monthly data for all variables during March 1989 (limited by earnings data) through January 2022, we find that… Keep Reading

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:

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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

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:

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