Investing Research Articles

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Simple Asset Class ETF Value Strategy

Does a simple relative value strategy applied to tradable asset class proxies produce attractive results? To investigate, we test a simple strategy on the following three 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 S&P 500 (SPY)

This set of ETFs relates to three factor risk premiums: (1) the difference in yields between Treasury bills and Treasury note/bonds indicates the term risk premium; (2) the difference in yields between corporate bonds and Treasury notes/bonds indicates the credit (default) risk premium; and, (3) 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 quarterly rebalanced portfolio of 60% stocks and 40% U.S. Treasury notes (60-40 SPY-IEF). Using quarterly S&P 500 Index levels and earnings, quarterly average yields for 3-month Constant Maturity U.S. Treasury bills (T-bills), quarterly average yields for 10-year Constant Maturity U.S. Treasury notes (T-notes), quarterly average yields for Moody’s Seasoned Baa Corporate Bonds during March 1989 through December 2014 (limited by availability of earnings data), and quarterly dividend-adjusted closing prices for the above three asset class ETFs during September 2002 through December 2014 (45 quarters, limited by availability of IEF and LQD), we find that: Keep Reading

Does the Turn-of-the-Month Effect Work for Asset Classes?

Does the Turn-of-the-Month Effect, a concentration of positive stock market returns around the turns of calendar months, work across a broad set of asset classes. To investigate, we measure turn-of-the-month (TOTM) returns for the following eight asset class exchange-traded funds (ETF) used in the “Simple Asset Class ETF Momentum Strategy”:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Emerging Markets Index (EEM)
iShares MSCI EAFE Index (EFA)
SPDR Gold Shares (GLD)
iShares Russell 1000 Index (IWB)
iShares Russell 2000 Index (IWM)
iShares Barclays 20+ Year Treasury Bond (TLT)

We define TOTM as the eight-trading day interval from the close five trading days before the first trading day of a month to the close on the fourth trading day of the month. Using daily dividend-adjusted closes for these ETFs from their respective inceptions (ranging from February 2006 for DBC to May 2000 for IWB) through February 2015 (109-178 months), we find that: Keep Reading

Does the Turn-of-the-Month Effect Work for Sectors?

A reader inquired whether the Turn-of-the-Month Effect, a concentration of positive stock market returns around the turns of calendar months, works for U.S. stock market sectors. To investigate, we measure turn-of-the-month (TOTM) returns for the nine sector exchange-traded funds (ETF) defined by the Select Sector Standard & Poor’s Depository Receipts (SPDR), all of which have trading data back to December 1998:

Materials Select Sector SPDR (XLB)
Energy Select Sector SPDR (XLE)
Financial Select Sector SPDR (XLF)
Industrial Select Sector SPDR (XLI)
Technology Select Sector SPDR (XLK)
Consumer Staples Select Sector SPDR (XLP)
Utilities Select Sector SPDR (XLU)
Health Care Select Sector SPDR (XLV)
Consumer Discretionary Select SPDR (XLY)

We define TOTM as the eight-trading day interval from the close five trading days before the first trading day of a month to the close on the fourth trading day of the month. Using daily dividend-adjusted closes for the sector ETFs and for S&P Depository Receipts (SPY) as a benchmark from December 1998 through February 2015 (195 months), we find that: Keep Reading

Inflation Forecast Update

The Inflation Forecast now incorporates actual total and core Consumer Price Index (CPI) data for February 2015. The actual total (core) inflation rate for February about the same as (the same as) forecasted.

Turn-of-the-Month Effect Persistence and Robustness

Is the Turn-of-the-Month (TOTM) effect, a concentration of positive stock market returns around the turns of calendar months, persistent over time and robust to different market conditions. Does it exist for all calendar months? Does it interact with the U.S. political cycle? Does it work for different indexes? To investigate, we define TOTM as the interval from the close five trading days before to the close four trading days after the last trading day of the month (a total of eight trading days, centered on the monthly close). Using daily closes for the S&P 500 Index during February 1950 through February 2015 (782 TOTMs) and for the Russell 2000 Index during October 1987 through February 2013 (330 TOTMs), we find that: Keep Reading

Survey of Recent Research on Factors, Regimes and Robustness

Why and how should investors pursue investment premiums associated with factors that explain performance differences among related assets (like common stocks)? In the January 2015 version of his paper entitled “Better Investing Through Factors, Regimes and Sensitivity Analysis”, Cristian Homescu summarizes recent research on: (1) factor-based investing; (2) enhancement of factor-based investing via regime switching models; and, (3) strategy robustness testing. Factor investing means systematic targeting of premiums associated with factors that explain an exploitable portion of return and risk differences among securities within one or several asset classes. Based on recent streams of research, he concludes that:

Keep Reading

Bollinger Bands: Buy Low and Sell High?

Are Bollinger Bands useful for specifying low and high levels of the overall U.S. stock market? In other words, can an investor beat a buy-and-hold strategy by systematically buying (selling) when the market crosses below (above) the lower (upper) Bollinger Band? To check, we examine the historical behavior of of Bollinger Bands around the 21-trading day (one month) simple moving average of S&P 500 SPDR (SPY) as a tradable proxy for the U.S. stock market. Using daily dividend-adjusted closes of SPY and contemporaneous yields for 13-week Treasury bills (T-bill) from the end of January 1993 (SPY inception) through February 2015, we find that… Keep Reading

Weekly Summary of Research Findings: 3/16/15 – 3/20/15

Below is a weekly summary of our research findings for 3/16/15 through 3/20/15. 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

Interactions among Stock Size, Stock Price and the January Effect

Is there an exploitable interaction between a stock’s market capitalization and its price? In their February 2015 paper entitled “Nominal Prices Matter”, Vijay Singal and Jitendra Tayal examine the relationship between stock prices and returns after: (1) controlling for market capitalization (size); (2) isolating the month of January; and, (3) excluding very small stocks. They each year perform double-sorts based on end-of-November data first into ranked tenths (deciles) by size and then within each size decile into price deciles. They calculate returns for January and for the calendar year with and without January. Using monthly prices and end-of-November market capitalizations for the 3,000 largest U.S. common stocks during December 1962 through December 2013, quarterly institutional ownership data for each stock during December 1980 through December 2013, and actual number of shareholders for each stock during 2004 through 2012, they find that: Keep Reading

Year-end Global Growth and Future Asset Class Returns

Does fourth quarter global economic data set the stage for asset class returns the next year? In their February 2015 paper entitled “The End-of-the-year Effect: Global Economic Growth and Expected Returns Around the World”, Stig Møller and Jesper Rangvid examine relationships between level of global economic growth and future asset class returns, focusing on growth at the end of the year. Their principle measure of global economic growth is the equally weighted average of quarterly OECD industrial production growth in 12 developed countries. They perform in-sample tests 30 countries and out-of-sample tests for these same 12 countries (for which more data are available). Out-of-sample tests: (1) generate initial parameters from 1970 through 1989 data for testing during 1990 through 2013 period; and, (2) insert a three-month delay between economic growth data and subsequent return calculations to account for publication lag. Using global industrial production growth as specified, annual total returns for 30 country, two regional and world stock indexes, currency spot and one-year forward exchange rates relative to the U.S. dollar, spot prices on 19 commodities, total annual returns for a global government bond index and a U.S. corporate bond index, and country inflation rates as available during 1970 through 2013, they find that: Keep Reading

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Current Momentum Winners

ETF Momentum Signal
for March 2015 (Final)

Winner ETF

Second Place ETF

Third Place ETF

Gross Compound Annual Growth Rates
(Since August 2006)
Top 1 ETF Top 2 ETFs
15.0% 15.8%
Top 3 ETFs SPY
15.2% 8.0%
Strategy Overview
Current Value Allocations

ETF Value Signal
for 1st Quarter 2015 (Final)









Gross Compound Annual Growth Rates
(Since September 2002)
Best Value Weighted 60-40
13.9% 9.7% 8.6%
Strategy Overview
Recent Research
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