Below is a weekly summary of our research findings for 2/11/19 through 2/15/19. These summaries give you a quick snapshot of our content the past week so that you can quickly decide what’s relevant to your investing needs.

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Subscribers asked whether risk parity might work better than equal weighting of winners within the Simple Asset Class ETF Momentum Strategy (SACEMS), which each month  selects the best performers over a specified lookback interval from among the following eight asset class exchange-traded funds (ETF), plus cash:

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)
3-month Treasury bills (Cash)

To investigate, we focus on the SACEMS Top 3 portfolio and compare equal weighting to risk parity weights. We calculate risk parity weights at the end of each month by:

• Calculating daily asset return volatilities over the last 63 trading days (about three months, as suggested). This step includes Cash, which has very low volatility.
• Picking the volatilities of the Top 3 momentum winners.
• Weighting each winner by the inverse of its volatility.
• Scaling winner weights such that the total of the three allocations is 100%.  This step essentially puts the entire portfolio into Cash when any of the Top 3 is Cash.

We use gross compound annual growth rates (CAGR) and maximum drawdowns (MaxDD) to compare strategies. We check robustness by trying lookback intervals of one to 12 months for both momentum ranking and volatility estimation (increments of 21 trading days for the latter). Using monthly dividend-adjusted closing prices for asset class proxies and the yield for Cash during February 2006 (when all ETFs are first available) through December 2018, we find that: Keep Reading

Each month, the Institute for Supply Management (ISM) compiles results of a survey “sent to more than 375 purchasing executives working in the non-manufacturing industries across the country.” Based on this survey, ISM computes the Non-Manufacturing Index (NMI), “a composite index based on the diffusion indexes for four…indicators with equal weights: Business Activity (seasonally adjusted), New Orders (seasonally adjusted), Employment (seasonally adjusted) and Supplier Deliveries.” ISM releases NMI for a month on the third business day of the following month. Does the monthly level of NMI or the monthly change in NMI predict U.S. stock market returns? Using monthly seasonally adjusted NMI data during January 2008 through January 2016 from the Federal Reserve Bank of St. Louis and from press releases thereafter through December 2018, and contemporaneous monthly S&P 500 Index closes (132 months), we find that: Keep Reading

The Inflation Forecast now incorporates actual total and core Consumer Price Index (CPI) data for January 2019. The actual total (core) inflation rate for January is lower than (slightly higher than) forecasted.

According to the Institute for Supply Management (ISM) ISM, their Manufacturing Report On Business, published since 1931, “is considered by many economists to be the most reliable near-term economic barometer available.” The manufacturing summary component of this report is the Purchasing Managers’ Index (PMI), aggregating monthly inputs from purchasing and supply executives across the U.S. regarding new orders, production, employment, deliveries and inventories. ISM releases PMI for a month at the beginning of the following month. Does PMI predict stock market returns? Using monthly seasonally adjusted PMI data during January 1950 through January 2016 from the Federal Reserve Bank of St. Louis (discontinued and removed) and from press releases thereafter through December 2018, and contemporaneous monthly S&P 500 Index closes (828 months), we find that:

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How well do mutual funds exploit theoretical (academic) equity factor premiums, and how well do investors exploit such exploitation? In their January 2019 paper entitled “Factor Investing from Concept to Implementation”, Eduard Van Gelderen, Joop Huij and Georgi Kyosev examine: (1) how performances of mutual funds that target equity factor premiums (low beta, size, value, momentum, profitability, investment) compare to that of funds that do not; and, (2) flow-adjusted performances, indicating how much of any outperformance accrues to fund investors. They classify funds empirically based on factor exposures. Using monthly returns and total assets and quarterly turnover and expense ratios for 3,109 actively managed long-only U.S. equity mutual funds with assets over $5 million (1,334 dead and 1,775 live) since January 1990 and for 4,859 (2,000 dead and 2,859 live) similarly specified global mutual funds since January 1991, all through December 2015, along with contemporaneous monthly equity factor returns, they find that: Keep Reading

Personal residences represent the largest asset class allocation for many U.S. investors. What return do they generate, how do their returns relate to stock market returns and how do they vary across Metropolitan Statistical Areas (MSA)? In their January 2019 paper entitled “The Cross-Section of Expected Housing Returns”, Esther Eiling, Erasmo Giambona, Ricardo Lopez Aliouchkin and Patrick Tuijp examine how U.S. residential real estate returns vary across MSAs. They also examine relationships between MSA residential real estate returns and both U.S. stock market returns and overall U.S. residential real estate returns. Using monthly Zillow Home Value Index levels for 571 MSAs, zip code population data from the U.S. Census Bureau and U.S. stock market returns during April 1996 through December 2016, they find that:

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Below is a weekly summary of our research findings for 2/4/19 through 2/8/19. These summaries give you a quick snapshot of our content the past week so that you can quickly decide what’s relevant to your investing needs.

Subscribers: To receive these weekly digests via email, click here to sign up for our mailing list. Keep Reading

In response to “Robustness of SACEMS Based on Sharpe Ratio”, a subscriber asked whether Martin ratio might work better than raw returns and Sharpe ratio for ranking assets within the Simple Asset Class ETF Momentum Strategy (SACEMS), which each month  selects the best performers over a specified lookback interval from among the following eight asset class exchange-traded funds (ETF), plus cash:

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)
3-month Treasury bills (Cash)

To investigate, we focus on the SACEMS equally weighted (EW) Top 3 portfolio and compare outcomes across lookback intervals ranging from one to 12 months for the following three asset ranking metrics:

1. Raw return – cumulative total return over the lookback interval.
2. Sharpe ratio (SR) – average daily excess return (asset return minus T-bill return) divided by standard deviation of daily excess returns over the lookback interval, with months approximated as 21 trading days. We set SR for Cash at zero (though it is actually zero divided by zero).
3. Martin ratio (MR) – average daily excess return divided by the Ulcer Index calculated from daily returns over the lookback interval, with months again approximated as 21 trading days.

We employ gross compound annual growth rates (CAGR) and maximum drawdowns (MaxDD) to compare ranking metrics. Using monthly dividend-adjusted closing prices for asset class proxies and the yield for Cash during February 2006 (when all ETFs are first available) through December 2018, we find that: Keep Reading

Larry Swedroe and Kevin Grogan introduce their 2019 book, Your Complete Guide to a Successful and Secure Retirement, as follows: “…failure to plan is to plan to fail. While so many of us have carefully planned our education, career choices, and family responsibilities, we tend to fail to prepare a written retirement life plan that considers, among other things, our passions, financial security, charitable endeavors, relationships, intellectual stimulation, and having fun. …Having a well-thought-out plan is important. However, planning is not a one-and-done event. To be effective, plans must be living things that must be revisited whenever any of the assumptions upon which the plan was based have changed.” Based on their experience in wealth management, mortgage lending and investment banking, they conclude that: Keep Reading