Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for July 2024 (Final)

Momentum Investing Strategy (Strategy Overview)

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

Simple Asset Class ETF Value Strategy (SACEVS)

Government securities, corporate bonds and equities arguably compete for investments at increasing levels of inherent risk based on: (1) valuations relative to each other, measured by risk premiums; and, (2) attractiveness of these risk premiums relative to their respective historical norms.

The Simple Asset Class ETF Value Strategy (SACEVS) seeks diversification across a small set of U.S. Treasury note, corporate bond and stock ETFs [iShares 20+ Year Treasury Bond (TLT), iShares iBoxx $ Investment Grade Corporate Bond (LQD) and SPDR S&P 500 (SPY)], plus a monthly tactical edge from timing the following three risk premiums associated with these asset classes:

  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.

There are two versions of SACEVS: (1) Best Value, which at the end of each month picks the most undervalued premium (if any); and, (2) Weighted, which at the end of each month weights all undervalued premiums (if any) according to degree of undervaluation. Based on the assets considered, the principal benchmark is a monthly rebalanced portfolio of 60% SPY-40% TLT (60-40).

Supporting research includes (items may at times be unavailable for a few days during updates):

We started tracking SACEVS in 2015, with only slight adjustments since as documented in the above list.

Some investors may want to follow one of the two strategy alternatives tracked here. Others may want to adapt them with modifications suited to their individual goals and constraints. Still others may want to apply the analysis approaches to test other strategies. Something to keep in mind is that adding complexity to the strategy with refining variables/parameters increases the number of ways to optimize and thereby elevates potential for data snooping bias.

The next section summarizes historical (backtest) performance data.

Historical Performance

The following chart shows the gross cumulative values of $100,000 initial investments in the Best Value and Weighted portfolios since the end of July 2002 (when all ETFs considered are first available). The chart includes the 60-40 portfolio as a benchmark and buying and holding SPY for reference.

The following table summarizes some monthly statistics for these same strategies and their ETF components over the available sample period. Return/Risk is average return divided by standard deviation. Maximum (peak-to-trough) drawdowns are based on monthly measurements over the available sample period. 

The next table summarizes annual/annualized returns for these strategies over different intervals commonly used to describe performance of funds. The annualized returns are compound annual growth rates (CAGR). For Sharpe ratio, to calculate excess annual return, we use average monthly yield on 3-month Treasury bills during a year as the risk-free rate for that year.

The next section offers a discussion of this performance.

ETF Value Allocations for July 2024 (Final)





The asset with the highest allocation is the holding of the Best Value strategy.

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