Strategic Allocation

A subscriber requested evaluation of versions of the Simple Asset Class ETF Value Strategy (SACEVS), the Simple Asset Class ETF Momentum Strategy (SACEMS) and a combination of the two, as follows:

1. For SACEVS Best Value, which chooses the asset proxy for the term, credit or equity premium that is most undervalued (if any), use only every third signal rather than every monthly signal. We start these quarterly signals with the first available signal in July 2002.
2. For SACEMS Equal-Weighted (EW) Top 2, use only every third signal rather than every monthly signal, rebalancing to equal weights only with these quarterly signals. We align quarterly signals with those for SACEVS.
3. For the SACEVS-SACEMS combination, use 30%-70% weights (per “SACEVS-SACEMS for Value-Momentum Diversification”) and rebalance only quarterly. We align quarterly rebalancings with those for SACEVS.

The overall approach is to suppress trading by limiting portfolio reformations/rebalancings to quarterly, while retaining the informativeness of monthly inputs. We apply these changes and compare results to those for the tracked (baseline) versions of SACEVS Best Value, SACEMS EW Top 2 and their 50%-50% combination. Using monthly SACEMS and SACEVS data during July 2006 (limited by availability of a commodities proxy in SACEMS) through June 2024, we find that: Keep Reading

The four iShares Core Asset Allocation exchange-traded funds (ETF) offer exposures to U.S. stocks, global stocks and bonds semiannually rebalanced to fixed weights, as follows.

1. iShares Core Conservative Allocation (AOK) – 30% stocks and 70% bonds (30-70).
2. iShares Core Moderate Allocation (AOM) – 40% stocks and 60% bonds (40-60).
3. iShares Core Growth Allocation (AOR) – 60% stocks and 40% bonds (60-40).
4. iShares Core Aggressive Allocation (AOA) – 80% stocks and 20% bonds (80-20).

Each fund holds a portfolio of seven iShares Core stocks and bonds ETFs, thereby compounding management costs and fees. Do these funds of funds offer attractive performance? To investigate, we compare performance statistics for these funds with those for comparably weighted and rebalanced combinations of SPDR S&P 500 Trust (SPY) and iShares 20+ Year Treasury Bond (TLT), or SPY and iShares iBoxx $ Investment Grade Corporate Bond (LQD). We start tests at the end of December 2008 (about a month after inception of the asset allocation ETFs). We ignore semiannual rebalancing frictions for the SPY-TLT and SPY-LQD comparison strategies. Using semiannual dividend-adjusted prices for all specified funds during December 2008 through June 2024, we find that: Keep Reading

Does adding an exchange-traded fund (ETF) or note (ETN) to the Simple Asset Class ETF Momentum Strategy (SACEMS) boost performance via consideration of more trending/diversifying options? To investigate, we add the following 25 ETF/ETN asset class proxies one at a time to the base set and measure effects on the Top 1, equally weighted (EW) Top 2 and EW Top 3 SACEMS portfolios:

Alerian MLP ETF (AMLP)
VanEck Vectors BDC Income (BIZD)
Vanguard Total Bond Market (BND)
SPDR Barclays International Treasury Bond (BWX)
Invesco DB Agriculture Fund (DBA)
iShares MSCI Emerging Markets (EEM)
iShares MSCI Frontier 100 (FM)
First Trust US IPO Index (FPX)
iShares iBoxx High-Yield Corporate Bond (HYG)
iShares 7-10 Year Treasury Bond (IEF)
iShares Latin America 40 (ILF)
iShares National Muni Bond ETF (MUB)
Invesco Closed-End Fund Income Composite (PCEF)
Invesco Global Listed Private Equity (PSP)
IQ Hedge Multi-Strategy Tracker (QAI)
Invesco QQQ Trust (QQQ)
SPDR Dow Jones International Real Estate (RWX)
ProShares UltraShort S&P 500 (SDS)
iShares Short Treasury Bond (SHV)
ProShares Short 20+ Year Treasury (TBF)
iShares TIPS Bond (TIP)
United States Oil (USO)
Invesco DB US Dollar Index Bullish Fund (UUP)
ProShares VIX Short-Term Futures (VIXY)
ProShares VIX Mid-Term Futures (VIXM)

We focus on gross compound annual growth rate (CAGR) and gross maximum drawdown (MaxDD) as key performance statistics, ignoring monthly reformation costs. Using end-of-month, dividend-adjusted returns for all assets as available during February 2006 through June 2024, we find that: Keep Reading

Are all of the potentially trending/diversifying asset class proxies used in the Simple Asset Class ETF Momentum Strategy (SACEMS) necessary? Might one or more of them actually be harmful to performance? To investigate, we each month rank the nine SACEMS assets based on past return with one excluded (nine separate test series) and reform the Top 1, equally weighted (EW) Top 2 and EW Top 3 SACEMS portfolios. We focus on gross compound annual growth rate (CAGR) and gross maximum drawdown (MaxDD) as key performance statistics, ignoring monthly portfolio reformation costs. Using end-of-month, dividend-adjusted returns for SACEMS assets during February 2006 through June 2024, we find that: Keep Reading

What happens if we extend the “Simple Asset Class ETF Value Strategy” (SACEVS) with a utilities risk premium, derived from the yield on Utilities Select Sector SPDR Fund (XLU)? 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 ETF (TLT)
iShares iBoxx $ Investment Grade Corporate Bond ETF (LQD)
XLU
SPDR S&P 500 ETF Trust (SPY)

This set of ETFs relates to four risk premiums, as specified below: (1) term; (2) credit (default); (3) utilities; and, (4) equity. We focus on effects of adding the utilities risk premium on gross compound annual growth rates (CAGR), maximum drawdowns (MaxDD) and annual Sharpe ratios 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 since March 1989 (limited by availability of earnings data), XLU prices and dividends since December 1998 (inception) and monthly dividend-adjusted closing prices for the above asset class ETFs since July 2002, all through May 2024, we find that: Keep Reading

“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 2024 Investment Company Fact Book data tables 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 2023 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 2024, we find that: Keep Reading

Is industry trend-following an attractive strategy over the long run? In their June 2024 paper entitled “A Century of Profitable Industry Trends”, Carlo Zarattini and Gary Antonacci evaluate the long-term performance of a long-only industry trend-following (Timing Industry) strategy, modeled as follows:

• Entry – buy an industry when its daily closing price crosses above the upper band of either its 20-day Keltner Channel (with a multiplier of 2 for the high-low price range component) or its 20-day Donchian Channel.
• Sizing – each day for each open position, calculate 14-day past return volatility as an estimate of its future volatility and resize all open positions so that they contribute equally to overall portfolio volatility, limiting overall portfolio leverage to 200%.
• Exit – each day for each open position, close the position if it crosses below a stop loss represented by the lower band of either its 40-day Keltner Channel (again with a multiplier of 2 for the high-low price range component) or its 40-day Donchian Channel. However, do not ever lower the stop loss. When a position closes, reinvest proceeds into 1-month U.S. Treasury bills.

For a long-term test, they apply these rules to nearly 98 years of daily returns for 48 hypothetical annually rebalanced, capitalization-weighted industry portfolios constructed by assigning a Standard Industrial Classification (SIC) Code to each stock traded on NYSE, AMEX and NASDAQ. For a recent and more realistic test, they apply these rules to 31 sector exchange-traded funds (ETF) offered by State Street Global Advisors. Utilizing daily returns for the 48 industry portfolios since July 1926 and for the 31 sector ETFs as available (inceptions January 2005 to June 2018), all through March 2024, they find that:

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We have updated monthly allocations and performance data for the Simple Asset Class ETF Momentum Strategy (SACEMS) and the Simple Asset Class ETF Value Strategy (SACEVS). We have also updated performance data for the Combined Value-Momentum Strategy.

We have updated the Trading Calendar to incorporate data for June 2024.

The home page, Simple Asset Class ETF Momentum Strategy (SACEMS) and Simple Asset Class ETF Value Strategy (SACEVS) now show preliminary positions for July 2024. SACEMS rankings are unlikely to change by the close. SACEVS allocations are unlikely to change by the close.

A subscriber asked about the stability of the momentum measurement (lookback) interval used for strategies like the Simple Asset Class ETF Momentum Strategy (SACEMS). To investigate, we run two tests on each of top one (Top 1),  equal-weighted top two (EW Top 2) and equal-weighted top three (EW Top 3) versions of SACEMS:

1. Identify the SACEMS lookback interval with the highest gross compound annual growth rate (CAGR) for a sample starting February 2006 when Invesco DB Commodity Index Tracking Fund (DBC) becomes available and ending each of May 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 and 2024. We consider lookback intervals of one to 12 months, meaning that earliest allocations are for February 2007 to accommodate the longest interval. The shortest sample period is therefore 5.3 years. This test takes the perspective of an investor who devises SACEMS in May 2012 and each year adds 12 months of data and checks whether the optimal lookback interval has changed.
2. Identify the SACEMS lookback interval with the highest gross CAGR for a sample ending May 2021 and starting each of February 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018 and 2019. The shortest sample period is again 5.3 years. This test takes perspectives of different investors who devise SACEMS at the end of February in different years.

Using monthly SACEMS inputs and the SACEMS model as currently specified for February 2006 through May 2024, we find that: Keep Reading