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Returns on U.S. Residential Real Estate

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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Weekly Summary of Research Findings: 2/4/19 – 2/8/19

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

SACEMS Based on Martin Ratio?

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

A Few Notes on Your Complete Guide to a Successful and Secure Retirement

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

SMA Signal Effectiveness Across Stock ETFs

Simple moving averages (SMA) are perhaps the most widely used and simplest market regime indicators. For example, many investors estimate that a stock index, exchange-traded fund (ETF) or individual stock priced above (below) its 200-day SMA is in a good (bad) regime. Do SMA signals/signal combinations usefully and consistently distinguish good and bad regimes across different kinds of U.S. stock ETFs? To investigate, we test regime signals of 50-day, 100-day and 200-day SMAs and combinations of them across broad equity market (DIASPYIWBIWM and QQQ), equity style (IWDIWFIWN and IWO) and equity sector (XLBXLEXLFXLIXLKXLPXLUXLV and XLY) ETFs. We consider also three individual stocks: Apple (AAPL), Berkshire Hathaway (BRK-B) and Wal-Mart (WMT). We focus on compound annual growth rate (CAGR) for comparisons, but also look at a few other performance metrics. Using daily dividend-adjusted closes of these 18 ETFs and three stocks during late July 2000 (limited by IWN and IWO) through mid-January 2019, we find that: Keep Reading

Sloppy Selling of Expert Traders?

Do expert investors (institutional stock portfolio managers) add value both by buying future outperforming stocks and by selling future underperforming stocks? In their December 2018 paper entitled “Selling Fast and Buying Slow: Heuristics and Trading Performance of Institutional Investors”, Klakow Akepanidtaworn, Rick Di Mascio, Alex Imas and Lawrence Schmidt examine trade decisions of experienced institutional (e.g., pension fund) stock portfolio managers to determine whether they buy and sell shrewdly. In their main tests, they evaluate: (1) positions added versus randomly buying more shares of some stock already in the portfolio: and, (2) positions liquidated versus randomly selling some other holding that was not traded on that date. Using data for 783 portfolios involving 4.4 million trades (2.0 million sells and 2.4 million buys), and prices for assets held and traded in U.S. dollars, during January 2000 through March 2016, they find that:

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Stock Market Valuation Ratio Trends

To determine whether the stock market is expensive or cheap, some experts use aggregate valuation ratios, either trailing or forward-looking, such as earnings-price ratio (E/P) and dividend yield. Operating under a belief that such ratios are mean-reverting, most imminently due to movement of stock prices, these experts expect high (low) future stock market returns when these ratios are high (low). Where are the ratios now? Using recent actual and forecasted earnings and dividend data from Standard & Poor’s, we find that: Keep Reading

Weekly Summary of Research Findings: 1/28/19 – 2/1/19

Below is a weekly summary of our research findings for 1/28/19 through 2/1/19. 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

Classic Cars as an Alternative Investment

Are some types of cars attractive alternative investments? In their September 2018 paper entitled “My Kingdom for a Horse (or a Classic Car)”, Dries Laurs and Luc Renneboog investigate price determinants and investment performance of classic cars from veteran cars (built 1888-1907) through modern classics (1975-1990). They estimate returns and risks for several classic car price indexes via a hedonic price methodology that accounts for physical attributes (such as engine displacement), condition, rarity, uniqueness and provenance. They then compare results to those for financial and other real asset classes. Using a sample of 29,002 global auction sales with hedonic model inputs, plus U.S. inflation data and price series for other asset classes, during 1998 through 2017, they find that:

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SACEMS with Momentum Breadth Crash Protection

In response to “SACEMS with SMA Filter”, a subscriber suggested instead crash protection via momentum breadth (proportion of assets with positive momentum) by:

  1. Switching to 100% cash when fewer than four of eight Simple Asset Class ETF Momentum Strategy (SACEMS) non-cash assets have positive past returns.
  2. Scaling from cash into winners when four to eight risk assets have positive past returns (no cash for eight).
  3. Replacing U.S. Treasury bills (T-bills), a proxy for broker money market rates, with iShares Barclays 7-10 Year Treasury Bond (IEF) as “Cash.”

To investigate, we each month rank assets from the following SACEMS universe based on total returns over a specified lookback interval. We also each month measure momentum breadth for the eight non-cash assets using the same lookback interval.

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)

While emphasizing the suggested momentum breadth crash protection threshold, we look at all possible thresholds. While emphasizing a baseline lookback interval, we consider lookback intervals ranging from one to 12 months for the suggested momentum breadth threshold. We focus on compound annual growth rates (CAGR) and maximum drawdowns (MaxDD) for the equal-weighted (EW) Top 3 SACEMS portfolio, but also look at Top 1 and EW Top 2. We also look at EW Top 3 portfolio turnover. Using monthly dividend-adjusted closing prices for SACEMS assets and IEF and the T-bill yield during February 2006 (the earliest all ETFs are available) through December 2018, we find that: Keep Reading

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