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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Strategic Allocation

Is there a best way to select and weight asset classes for long-term diversification benefits? These blog entries address this strategic allocation question.

Allocations and Returns of Endowments

How do U.S. non-profit endowment funds allocate and perform? In their November 2019 paper entitled “The Risk, Reward, and Asset Allocation of Nonprofit Endowment Funds”, Andrew Lo, Egor Matveyev and Stefan Zeume examine recent asset allocations and investment returns of U.S. public non-profit endowment funds. Due to the unstructured nature of asset reporting, they manually assign each asset in each fund to one of nine categories: (1) public equity; (2) fixed income; (3) private equity; (4) cash instruments; (5) hedge funds; (6) real estate; (7) real assets and real return; (8) trusts; and, (9) cooperative investments. Using tax return data encompassing 34,170 endowment funds during 2009 through 2018, they find that: Keep Reading

Effectiveness of Various Risk Controls during the COVID-19 Crash

How well did previously identified portfolio risk management strategies work during the COVID-19 market crash? In their July 2020 paper entitled “Strategic Risk Management: Out-of-Sample Evidence from the COVID-19 Equity Selloff”, Campbell Harvey, Edward Hoyle, Sandy Rattray and Otto Van Hemert extended analyses of risk management strategies they identified in a 2016-2019 series of papers with an out-of-sample test of the February-March 2020 stock market sell-off. These strategies include:

  • Long put options, short credit risk, long bonds or long gold.
  • Trend following based on time series/intrinsic momentum (past return divided by volatility of returns over a specified lookback interval) or on moving average crossovers.
  • Holding defensive stocks (based on profitability, payout, growth, safety or quality).
  • Volatility targeting (increasing/decreasing exposure when past volatility is relative low/high).
  • Rebalancing a stocks-bonds portfolio only half way and only when recent (1, 3 or 12 months) portfolio return is above its historical average.

Extending analyses from their prior papers through March 2020 to capture the COVID-19 crash, they find that:

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SACEVS Best Value + SACEMS EW Top 2?

A subscriber asked for a comparison of two 50%-50% monthly rebalanced combinations of Simple Asset Class ETF Value Strategy (SACEVS) and Simple Asset Class ETF Momentum Strategy (SACEMS) portfolios, as follows:

  1. 50-50 Best Value + EW Top 2: SACEVS Best Value plus SACEMS EW Top 2, employing a somewhat more aggressive momentum portfolio.
  2. 50-50 Best Value + EW Top 3: Best Value plus SACEMS equal-weighted (EW) Top 3, as tracked at “Combined Value-Momentum Strategy (SACEVS-SACEMS)”.

To investigate, we run the two combinations and compare cumulative performances and annual performance statistics. Using monthly SACEVS Best Value and SACEMS EW Top 2 and EW Top 3 portfolio returns commencing July 2006 (limited by SACEMS), we find that: Keep Reading

SACEVS Input Risk Premiums and EFFR

The “Simple Asset Class ETF Value Strategy” (SACEVS) seeks diversification across a small set of asset class exchanged-traded funds (ETF), plus a monthly tactical edge from potential undervaluation of three risk premiums:

  1. Term – monthly difference between the 10-year Constant Maturity U.S. Treasury note (T-note) yield and the 3-month Constant Maturity U.S. Treasury bill (T-bill) yield.
  2. Credit – monthly difference between the Moody’s Seasoned Baa Corporate Bonds yield and the T-note yield.
  3. Equity – monthly difference between S&P 500 operating earnings yield and the T-note yield.

Premium valuations are relative to historical averages. How might this strategy react to changes in the Effective Federal Funds Rate (EFFR)? Using end-of-month values of the three risk premiums, EFFRtotal 12-month U.S. inflation and core 12-month U.S. inflation during March 1989 (limited by availability of operating earnings data) through July 2020, we find that: Keep Reading

Forcing SACEMS to Agree with SACEVS

A subscriber asked whether forcing the Simple Asset Class ETF Momentum Strategy (SACEMS) to agree with the Simple Asset Class ETF Value Strategy (SACEVS) when the latter assigns zero weight to stocks or government bonds improves the performance of the former. Specifically, the suggested change would force to Cash in SACEMS any allocation to SPDR S&P 500 ETF Trust (SPY) or iShares 20+ Year Treasury Bond ETF (TLT) occurring when SACEVS allocates 0% to SPY or TLT, respectively. To investigate, we impose this additional condition on SACEMS and compare detailed monthly and annual performance statistics for this new version of SACEMS (New) to the original version (Base). Using monthly SACEVS allocations and monthly dividend-adjusted prices of the SACEMS universe ETFs during February 2006 through July 2020, 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 2020 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 2019 and FFIDX and FBNDX May through April total returns and April 1-year U.S. Treasury note (T-note) yields for 1985 through 2020, we find that: Keep Reading

Safe Haven Benchmark Index

How should investors evaluate the effectiveness of a safe haven asset? In their July 2020 paper entitled “A Safe Haven Index”, Dirk Baur and Thomas Dimpfl devise and apply a safe haven index (SHI) to evaluate over 20 individual potential safe haven assets. SHI consists of seven equal-weighted assets: gold, Swiss franc, Japanese yen, 2-year, 10-year and 30-year U.S. Treasuries and 10-year German government bonds. For evaluations, they focus on four safe haven events: the October 1987 stock market crash, the September 2001 terrorist attacks, the September 2008 Lehman collapse and the March 2020 COVID-19 pandemic. Using daily data for index components and other potential safe haven assets as available during January 1985 through May 2020, they find that:

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SACEMS with Different Alternatives for “Cash”

Do alternative “Cash” (deemed risk-free) instruments materially affect performance of the “Simple Asset Class ETF Momentum Strategy” (SACEMS)? Changing the proxy for Cash can affect how often the model selects Cash, as well as the return on Cash when selected. To investigate, we test separately each of the following yield and exchange-traded funds (ETF) as the risk-free asset:

3-month Treasury bills (Cash), a proxy for the money market as in base SACEMS
SPDR Bloomberg Barclays 1-3 Month T-Bill (BIL)
iShares 1-3 Year Treasury Bond (SHY)
iShares 7-10 Year Treasury Bond (IEF)
iShares TIPS Bond (TIP)

We focus on compound annual growth rate (CAGR) and maximum drawdown (MaxDD) as key performance metrics and consider Top 1, equally weighted (EW) EW Top 2 and EW Top 3 SACEMS portfolios. Using end-of-month total (dividend-adjusted) returns for the specified assets during February 2006 (except May 2007 for BIL) through June 2020, we find that:

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Optimal SACEMS Lookback Interval Update

How sensitive is performance of the “Simple Asset Class ETF Momentum Strategy” (SACEMS) to choice of momentum calculation lookback interval, and what interval works best? To investigate, we generate gross compound annual growth rates (CAGR) and maximum drawdowns (MaxDD) for SACEMS Top 1, equally weighted (EW) EW Top 2 and EW Top 3 portfolios over lookback intervals ranging from one to 12 months. All calculations start at the end of February 2007 based on inception of the commodities exchange-traded fund and the longest lookback interval. Using end-of-month total (dividend-adjusted) returns for the SACEMS asset universe during February 2006 through June 2020, we find that: Keep Reading

Classic Stocks-Bonds Portfolios with Leveraged ETFs

Can investors use leveraged exchange-traded funds (ETF) to construct attractive versions of simple 60%/40% (60/40) and 40%/60% (40/60) stocks-bonds portfolios? In their March 2020 presentation package entitled “Robust Leveraged ETF Portfolios Extending Classic 40/60 Portfolios and Portfolio Insurance”, flagged by a subscriber, Mikhail Smirnov and Alexander Smirnov consider several variations of classic stocks/bonds portfolio as implemented with leveraged ETFs. They ultimately focus on a monthly rebalanced partially 3X-leveraged portfolio consisting of:

  • 40% ProShares UltraPro QQQ (TQQQ)
  • 20% Direxion Daily 20+ Year Treasury Bull 3X Shares (TMF)
  • 40% iShares 20+ Year Treasury Bond ETF (TLT)

To verify findings, we consider this portfolio and several 60/40 and 40/60 stocks/bonds portfolios. We look at net monthly performance statistics, along with compound annual growth rate (CAGR), maximum drawdown (MaxDD) based on monthly data and annual Sharpe ratio. To estimate monthly rebalancing frictions, we use 0.5% of amount traded each month. We use average monthly 3-month U.S. Treasury bill yield during a year as the risk-free rate in Sharpe ratio calculations for that year. Using monthly adjusted prices for TQQQ, TMF, TLT and for SPDR S&P 500 ETF Trust (SPY) and Invesco QQQ Trust (QQQ) to construct benchmarks during February 2010 (limited by TQQQ inception) through June 2020, we find that: Keep Reading

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