Strategic Allocation

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

We have updated the “Trading Calendar” to incorporate data for November 2018.

The home page, “Momentum Strategy” and “Value Strategy” now show preliminary Simple Asset Class ETF Momentum Strategy (SACEMS) and Simple Asset Class ETF Value Strategy (SACEVS) positions for December 2018. For SACEMS, the top three positions are unlikely to change by the close, but their order may change. For SACEVS, allocations are unlikely to change by the close, but the credit premium is getting close to a transition.

Are the “Simple Asset Class ETF Value Strategy” (SACEVS) and the “Simple Asset Class ETF Momentum Strategy” (SACEMS) mutually diversifying. To check, we look at the following three equal-weighted (50-50) combinations of the two strategies, rebalanced monthly:

1. SACEVS Best Value paired with SACEMS Top 1 (aggressive value and aggressive momentum).
2. SACEVS Best Value paired with SACEMS Equally Weighted (EW) Top 3 (aggressive value and diversified momentum).
3. SACEVS Weighted paired with SACEMS EW Top 3 (diversified value and diversified momentum).

We also test sensitivity of results to deviating from equal SACEVS-SACEMS weights. Using monthly gross returns for SACEVS and SACEMS portfolios since January 2003 for the first strategy and since July 2006 for the latter two, all through October 2018, we find that: Keep Reading

Is the U.S. equity turn-of-the-month (TOTM) effect exploitable as a diversifier of other assets? In their October 2018 paper entitled “A Seasonality Factor in Asset Allocation”, Frank McGroarty, Emmanouil Platanakis, Athanasios Sakkas and Andrew Urquhart test U.S. asset allocation strategies that include a TOTM portfolio as an asset. The TOTM portfolio buys each stock at the open on the last trading day of each month and sells at the close on the third trading day of the following month, earning zero return the rest of the time. They consider four asset universes with and without the TOTM portfolio:

1. A conventional stocks-bonds mix.
2. The equity market portfolio.
3. The equity market portfolio, a small size portfolio and a value portfolio.
4. The equity market portfolio, a small size portfolio, a value portfolio and a momentum winners portfolio.

They consider six sophisticated asset allocation methods:

1. Mean-variance optimization.
2. Optimization with higher moments and Constant Relative Risk Aversion.
3. Bayes-Stein shrinkage of estimated returns.
4. Bayesian diffuse-prior.
5. Black-Litterman.
6. A combination of allocation methods.

They consider three risk aversion settings and either a 60-month or a 120-month lookback interval for input parameter measurement. To assess exploitability, they set trading frictions at 0.50% of traded value for equities and 0.17% for bonds. Using monthly data as specified above during July 1961 through December 2015, they find that:

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How does use of actuarial estimates of retiree longevity and empirical mean reversion of stock market returns affect estimated retirement portfolio success rates? In the October 2018 revision of his paper entitled “Joint Effect of Random Years of Longevity and Mean Reversion in Equity Returns on the Safe Withdrawal Rate in Retirement”, Donald Rosenthal presents a model of safe inflation-adjusted retirement portfolio withdrawal rates that addresses: (1) uncertainty about the number of years of retirement (rather than the commonly assumed 30 years); and, (2) mean reversion in annual U.S. stock market returns (rather than a random walk). He estimates retirement longevity as a random input based on the Social Security Administration’s 2015 Actuarial Life Table. He estimates stock market real returns and measures their mean reversion using S&P 500 Index inflation-adjusted total annual returns during 1926 through 2017. He models real bond returns using 10-year U.S. Treasury note (T-note) total annual returns during 1928 through 2017. He applies Monte Carlo simulations (3,000 trials for each scenario) to assess retirement portfolio performance by:

• Assuming an initial retirement portfolio either 100% invested in stocks or 60%/40% in stocks/T-notes (rebalanced at each year-end).
• Debiting the portfolio each year-end by a fixed, inflation-adjusted percentage of the initial amount.
• Calculating percentage of simulation trials for which the portfolio is not exhausted before death (success) and average portfolio terminal balance for successful trials.

He considers two benchmarks: (1) no stock market mean reversion (random walk) and fixed 30-year retirement; and, (2) no stock market mean reversion and actuarial estimate of retirement duration. He also runs sensitivity tests to see how changes in assumptions affect success rate. Using the specified data, he finds that:

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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 increases in the Effective Federal Funds Rate (EFFR)? Using end-of-month values of the three risk premiums, EFFR, total 12-month U.S. inflation and core 12-month U.S. inflation during March 1989 (limited by availability of operating earnings data) through September 2018, we find that: Keep Reading

What happens if we extend the “Simple Asset Class ETF Value Strategy” (SACEVS) with a real estate risk premium, derived from the yield on equity Real Estate Investment Trusts (REIT), represented by the FTSE NAREIT Equity REITs Index? 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 (TLT)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
SPDR Dow Jones REIT (RWR) through September 2004 dovetailed with Vanguard REIT ETF (VNQ) thereafter
SPDR S&P 500 (SPY)

This set of ETFs relates to four risk premiums, as specified below: (1) term; (2) credit (default); (3) real estate; and, (4) equity. We focus on the effects of adding the real estate risk premium on Compound annual growth rates (CAGR) and Maximum drawdowns (MaxDD) 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 and FTSE NAREIT Equity REITs Index during March 1989 through August 2018 (limited by availability of earnings data), and monthly dividend-adjusted closing prices for the above asset class ETFs during July 2002 through August 2018 (194 months, limited by availability of TLT and LQD), we find that: Keep Reading

Brian Livingston introduces his 2018 book, Muscular Portfolios: The Investing Revolution for Superior Returns with Lower Risk, as follows: “What we laughingly call the financial ‘services’ industry is a cesspool filled with sharks intent on siphoning your money away and making it their own. The good news is that it is absolutely possible to grow your savings with no fear of financial sharks or stock market crashes. In the past few years, we’ve seen an explosion of low-cost index funds, along with serious mathematical breakthroughs in how to combine these funds into low-risk portfolios. …This book shows you how.  …You can start with just a little money and make it grow.” Based on research from multiple sources and extensions of that research, he concludes that: Keep Reading

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)

In other words, we add one of the five risk-free assets to the following base set of eight ETFs:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 2000 Index (IWM)
SPDR S&P 500 (SPY)
iShares Barclays 20+ Year Treasury Bond (TLT)
Vanguard REIT ETF (VNQ)

We focus on the equally weighted (EW) EW Top 3 SACEMS portfolio and consider all performance metrics used for base SACEMS. Using end-of-month total (dividend-adjusted) returns for the specified assets during February 2006 (except May 2007 for BIL) through July 2018, we find that:

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A subscriber inquired whether a longer test of the “Simple Asset Class ETF Momentum Strategy” (SACEMS) is feasible using mutual funds rather than exchange-traded funds (ETF) as asset class proxies. To investigate, we consider the following set of mutual funds (partly adapted from the paper summarized in “Asset Allocation Combining Momentum, Volatility, Correlation and Crash Protection”):

Oppenheimer Commodity Strategy Total Return A (QRAAX) until its discontinuation in mid-2016, and PIMCO CommoditiesPLUS Strategy (PCPSX) thereafter.
Vanguard Emerging Markets Stock Index Investor Shares (VEIEX)
Fidelity Diversified International (FDIVX)
First Eagle Gold A (SGGDX)
Vanguard Total Stock Market Index Investor Shares (VTSMX)
Vanguard Small Capitalization Index Investor Shares  (NAESX)
Vanguard REIT Index Investor Shares (VGSIX)
Vanguard Long-Term Treasury Investor Shares (VUSTX)
3-month Treasury bills (Cash)

We rank mutual funds based on total (dividend-adjusted) returns over past (lookback) intervals of one to 12 months. We consider portfolios of past mutual fund winners based on Top 1 and on equally weighted (EW) Top 2 through Top 5. We consider as benchmarks: an equally weighted portfolio of all mutual funds, rebalanced monthly (EW All); buying and holding VTSMX; and, holding VTSMX when the S&P 500 Index is above its 10-month simple moving average (SMA10) and Cash when the index is below its SMA10 (VTSMX:SMA10). Using monthly dividend-adjusted closing prices for the above mutual funds and the yield for Cash during March 1997 through July 2018 (269 months), we find that: Keep Reading