Investing Research Articles

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Weekly Summary of Research Findings: 5/23/16 – 5/27/16

Below is a weekly summary of our research findings for 5/23/16 through 5/27/16. 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-SACEVS Mutual Diversification

Are the “Simple Asset Class ETF Value Strategy” (SACEVS) and the “Simple Asset Class ETF Momentum Strategy” (SACEMS) mutually diversifying. To check, we relate monthly returns for the SACEVS and the SACEMS exchange-traded fund (ETF) selections and look at the performance of an equally weighted portfolio of the two strategies, rebalanced monthly (50-50). Specifically, we consider: SACEVS Best Value paired with SACEMS Top 1; and, SACEVS Weighted paired with SACEMS Equally Weighted (EW) Top 3. Using monthly gross returns for SACEVS Best Value and SACEMS Top 1 since January 2003 and for SACEVS Weighted and SACEMS EW Top 3 since July 2006, all through April 2016, we find that: Keep Reading

Add REITs to SACEVS?

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 four asset class exchange-traded funds (ETF), plus cash:

3-month Treasury bills (Cash)
iShares 7-10 Year Treasury Bond (IEF)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
SPDR Dow Jones REIT (RWR)
SPDR S&P 500 (SPY)

This set of ETFs relates to four factor risk premiums: (1) the difference in yields between Treasury bills and Treasury notes/bonds indicates the term risk premium; (2) the difference in yields between corporate bonds and Treasury notes/bonds indicates the credit (default) risk premium; (3) the difference in yields between equity REITs and Treasury notes/bonds indicates the real estate risk premium; and, (4) the difference in yields between equities and Treasury notes/bonds indicates the equity risk premium. We consider two alternative strategies for exploiting premium undervaluation: Best Value, which picks the most undervalued premium; and, Weighted, which weights all undervalued premiums according to degree of undervaluation. Based on the assets considered, the principal benchmark is a monthly rebalanced portfolio of 60% stocks and 40% U.S. Treasury notes (60-40 SPY-IEF). Using lagged quarterly S&P 500 earnings, end-of-month S&P 500 Index levels and end-of-month yields for the 3-month Constant Maturity 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 April 2016 (limited by availability of earnings data), and daily dividend-adjusted closing prices for the above four asset class ETFs during July 2002 through April 2016 (166 months, limited by availability of IEF and LQD), we find that: Keep Reading

Expert Estimates of 2016 Country Equity Risk Premiums

What are current estimates of annual premiums over risk-free rates demanded in each country by equity investors (equity risk premium, or ERP)? In their May 2016 paper entitled “Market Risk Premium Used in 71 Countries in 2016: A Survey with 6,932 Answers”, Pablo Fernandez, Alberto Ortiz and Isabel Acin summarize results of an April 2016 email survey of international finance/economic professors, analysts and company managers “about the Market Risk Premium (MRP) or Equity Premium used to calculate the required return to equity in different countries.” Based on 6,734 specific and credible responses spanning 71 countries (with at least eight such responses), they find that: Keep Reading

Stock Returns Around Memorial Day

Does the Memorial Day holiday signal any unusual U.S. stock market return effects? By its definition, this holiday brings with it any effects from three-day weekends and sometimes the turn of the month. Prior to 1971, the U.S. celebrated Memorial Day on May 30. Effective in 1971, Memorial Day became the last Monday in May. To investigate the possibility of short-term effects on stock market returns around Memorial Day, we analyze the historical behavior of the stock market during the three trading days before and the three trading days after the holiday. Using daily closing levels of the S&P 500 Index for 1950 through 2015 (66 observations), we find that: Keep Reading

Asset Class Momentum Interaction with Market Volatility

Subscribers have proposed that asset class momentum effects should accelerate (shorter optimal ranking interval) when markets are in turmoil (bear market/high volatility). “Asset Class Momentum Faster During Bear Markets?” addresses this hypothesis in a multi-class, relative momentum environment. Another approach is to evaluate the relationship between time series (intrinsic or absolute) momentum and volatility. Applied to the S&P 500 Index and the S&P 500 Implied Volatility Index (VIX), this alternative offers a longer sample period less dominated by the 2008-2009 equity market crash. Specifically, we examine monthly correlations between S&P 500 Index return over the past 1 to 12 months with next-month return to measure strength of time series momentum (positive correlations) or reversal (negative correlations). We compare correlations by ranked fifth (quintile) of VIX at the end of the past return measurement interval to determine (in-sample) optimal time series momentum measurement intervals for different ranges of VIX. We also test whether: (1) monthly change in VIX affects time series momentum for the S&P 500 Index; and, (2) VIX level affects time series momentum for another asset class (spot gold). Using monthly S&P 500 Index levels and spot gold prices since January 1989 and monthly VIX levels since inception in January 1990, all through April 2016, we find that: Keep Reading

Weekly Summary of Research Findings: 5/16/16 – 5/20/16

Below is a weekly summary of our research findings for 5/16/16 through 5/20/16. 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

Stock Market Performance Around VIX Peaks

Do peaks in the S&P 500 Implied Volatility Index (VIX) signal positive abnormal U.S. stock market returns? If so, can investors exploit these returns? In the May 2016 version of his paper entitled “Abnormal Stock Market Returns Around Peaks in VIX: The Evidence of Investor Overreaction?”, Valeriy Zakamulin analyzes U.S. stock market returns around VIX peaks. He employs two formal methods to detect peaks:

  1. When a local maximum (minimum) is at least 20% higher (30% lower) than the last local minimum (maximum), it is a peak (trough).
  2. First, identify all local maximums (peaks) and minimums (troughs) within 8-day windows. Then winnow peaks and troughs and systematize alternation by: excluding peaks and troughs in the first and last 20 days; eliminating cycles (peak-to-peak or trough-to-trough) shorter than 22 days; and, excluding phases (trough-to-peak or peak-to-trough) shorter than 10 days, unless daily percentage change exceeds 30%.

He then tests for abnormal stock market returns around VIX peaks and during preceding and following intervals of rising and falling VIX. Abnormal means relative to the average market return for the sample period. Finally, he investigates whether abnormal returns around peaks are due to investor overreaction. Using daily closes for VIX and daily returns of the broad capitalization-weighted U.S. stock market during January 1990 through December 2015, he finds that: Keep Reading

Big Picture on Prevalence of Asset Price Series Trends and Reversals

Do asset price series in general reliably exhibit trends and reversals? In his May 2016 paper entitled “Trend, Mean-Reversion or Random Walk? A Statistical Analysis of Price Behavior in Major Markets”, Theo Athanasiadis tests a wide variety of financial market price series for existence of significant trends and reversals. He considers both spot and futures price series in U.S. dollars for 56 major markets: 16 developed equity market indexes; the S&P 500 implied volatility index (VIX); 25 liquid commodities covering all basic sectors; 5 liquid currency exchange rates versus the U.S. dollar; and, 9 liquid government bonds of varying durations. For futures contract returns, he uses the most liquid contracts (typically nearest or next-nearest) and rolls accordingly. He employs three statistical tests of time-series behavior: autocorrelation, variance ratio and positive/negative runs relative to median. He considers weekly, monthly, quarterly and semiannual returns in both univariate and multivariate tests. Using spot and futures price returns at the specified frequencies for all 56 markets as available during January 1999 through March 2016, he finds that: Keep Reading

Do Conventional SMAs Identify Gold Market Regimes?

Do simple moving averages (SMA) commonly used to identify stock market bull and bear regimes work similarly for the spot gold market? To investigate, we consider two market regime indicators: the 200-day SMA and a combination of the 50-day and 200-day SMAs. Because trading days for gold and stocks are sometimes different, we also check a 10-month SMA based on monthly closes. Using daily and monthly spot gold prices and S&P 500 Index levels during January 1973 through April 2016, we find that: Keep Reading

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Current Momentum Winners

ETF Momentum Signal
for May 2016 (Final)

Winner ETF

Second Place ETF

Third Place ETF

Gross Compound Annual Growth Rates
(Since August 2006)
Top 1 ETF Top 2 ETFs
11.3% 11.5%
Top 3 ETFs SPY
12.4% 7.2%
Strategy Overview
Current Value Allocations

ETF Value Signal
for May 2016 (Final)

Cash

IEF

LQD

SPY

The asset with the highest allocation is the holding of the Best Value strategy.
Gross Compound Annual Growth Rates
(Since September 2002)
Best Value Weighted 60-40
12.7% 9.8% 7.8%
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