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Weekly Summary of Research Findings: 6/29/15 – 7/2/15

Below is a weekly summary of our research findings for 6/29/15 through 7/2/15. 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

Sector vs. Factor U.S. Stock Diversification?

Which is better, sector-based or factor-based stock investing? In their June 2015 paper entitled “Factor-Based v. Industry-Based Asset Allocation: The Contest”, Marie Briere and Ariane Szafarz compare the attractiveness of sector-based and factor-based U.S. stock allocations. From Kenneth French’s data library, they extract return series for 10 sectors and five factors (size, value, profitability, investment and momentum). They expand the factor set to 10 by using long and short portfolios for each factor. They consider three trials:

  1. Which group, sectors or factors, yields the dominantly more attractive efficient frontier?
  2. Which group offers the clearly superior gross Jensen’s alphas across single-sector/factor portfolios and portfolios diversified across sectors or factors based on maximizing estimated Sharpe ratio, minimizing estimated volatility or equal weighting?
  3. Do portfolios diversified across sectors or factors (based on maximizing estimated Sharpe ratio, minimizing estimated volatility or equal weighting) offer the best gross Sharpe ratios?

For each trial, they test long-only and long-short factor portfolios. Also for each trial, they test the overall sample, economic recession and expansion subsamples (per the National Bureau of Economic Research) and bull and bear market subsamples (per Forbes magazine). Using monthly U.S. stock market factor and sector returns from Kenneth French’s library spanning July 1963 through November 2014, they find that: Keep Reading

Real-world Equity Fund Performance Benchmarks

Do equity style mutual funds look more attractive when benchmarked to matched style stock indexes than to more theoretical factor models of stock returns? In their April 2015 paper entitled “On Luck versus Skill When Performance Benchmarks are Style-Consistent”, Andrew Mason, Sam Agyei-Ampomah, Andrew Clare and Steve Thomas compare alphas for U.S. equity style mutual funds as calculated with conventional factor models and as calculated with matched Russell style indexes. The factor models they consider are the 1-factor capital asset pricing model (CAPM), the Fama-French 3-factor model (market, size, book-to-market) and the Carhart 4-factor model (adding momentum). They consider both value (net asset value)-weighted and equal-weighted portfolios of mutual funds. They also perform simulations to control for differences in the precision of alpha estimates due to differences in fund sample sizes. Using monthly gross and net returns and equity styles for 2,384 surviving and dead U.S. diversified equity funds, and returns for Russell equity style indexes and market/size/value/momentum factors, during January 1990 through December 2011, they find that: Keep Reading

Momentum Strategy, Value Strategy and Trading Calendar Updates

We have updated the the monthly asset class ETF momentum winners and associated performance data at Momentum Strategy. We have updated the the quarterly ETF weights and associated performance data at Value Strategy.

We have updated the Trading Calendar to incorporate data for June 2015.

Preliminary Momentum and Value Strategy Updates

The home page and “Momentum Strategy” now show preliminary asset class ETF momentum strategy positions for July 2015. The differences in past returns among the top four places are fairly large, and the past returns for the top three positions are sufficiently above the Cash return, that selections are unlikely to change by the close. However, markets are volatile.

The home page and “Value Strategy” now show preliminary ETF allocations related to term, credit and equity premiums for the third quarter of 2015. These allocations could shift slightly by the close.

More International Equity Market Granularity for SACEMS?

A subscriber asked whether more granularity in international equity choices for the “Simple Asset Class ETF Momentum Strategy” (SACEMS), as considered by the Decision Moose, would improve performance. To investigate, we replace the iShares MSCI Emerging Markets Index (EEM) and the iShares MSCI EAFE Index (EFA) with four regional international equity exchange-traded funds (ETF). The universe of assets then becomes:

PowerShares DB Commodity Index Tracking (DBC)
iShares MSCI Pacific ex Japan (EPP)
iShares MSCI Japan (EWJ)
SPDR Gold Shares (GLD)
iShares Europe (IEV)
iShares Latin America 40 (ILF)
iShares Russell 1000 Index (IWB)
iShares Russell 2000 Index (IWM)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

We compare original (SACEMS) and modified (SACEMS Granular) winner portfolios, allocating all funds at the end of each month to the asset class ETF or cash with the highest total return over the past five months. Using monthly dividend-adjusted closing prices for the asset class proxies and the yield for Cash over the period July 2002 through May 2015 (156 months), we find that: Keep Reading

Update SACEVS with End-of-quarter Instead of Quarterly Average Yields?

“Simple Asset Class ETF Value Strategy” (SACEVS) tests a simple relative value strategy that each quarter allocates funds to one or more of the following three asset class exchange-traded funds (ETF), plus cash, based on degree of undervaluation of measures of the term risk, credit risk and equity risk premiums:

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

One version of SACEVS (Best Value) picks the most undervalued premium. Another (Weighted) weights all undervalued premiums according to degree of undervaluation. Premium calculations and SACEVS portfolio allocations derive from quarterly average yields for 3-month Constant Maturity U.S. Treasury bills (T-bills), 10-year Constant Maturity U.S. Treasury notes (T-notes) and Moody’s Seasoned Baa Corporate Bonds (Baa). A subscriber asked whether fresh end-of-quarter yields might work better than quarterly average yields. Using monthly S&P 500 Index levelsquarterly S&P 500 earnings and daily T-note, T-bill and Baa yields during March 1989 through March 2015 (limited by availability of earnings data), and quarterly dividend-adjusted closing prices for the above three asset class ETFs during September 2002 through March 2015 (154 months, limited by availability of IEF and LQD), we find that: Keep Reading

Weekly Summary of Research Findings: 6/22/15 – 6/26/15

Below is a weekly summary of our research findings for 6/22/15 through 6/26/15. 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

Continue to archive for older articles

Editor Archive Picks

Factor Model of Country Stock Market Returns?

…ersion of his paper entitled “Country Selection Strategies Based on Value, Size and Momentum”, Adam Zaremba investigates country-level value, size and momentum premiums, and tests whether the value and momentum premiums are equally strong across markets of different sizes and evaluates a country-level multi-factor asset pricing model. He measures factors at the country level as: Value: aggregate book-to-market ratio, with aggregate 12…

Low-volatility Effect Across Country Stock Markets?

…sk taken? In his December 2014 paper entitled “Is There a Low-Risk Anomaly Across Countries?”, Adam Zaremba relates country stock market performance to four market risk metrics: beta (relative to the capitalization-weighted world stock market), standard deviation of returns, value at risk (fifth percentile of observations) and idiosyncratic (unexplained by world market) volatility. He uses historical intervals of 12 to 24 months as av…

Quality as Discriminator of Country Stock Markets

…markets? In his December 2014 paper entitled “Country Selection Strategies Based on Quality”, Adam Zaremba investigates whether quality metrics effectively predict country stock market index performance. He also examines whether (1) quality-size and quality-value double sorts enhance country-level value and size strategies; and, (2) high-quality markets offer a hedge during times of market distress. He considers six quality metrics:…

Country Stock Market Factor Strategies

…5 version of their paper entitled “Do Quantitative Country Selection Strategies Really Work?”, Adam Zaremba and Przemysław Konieczka test 16 country stock market selection strategies based on relative market value, size, momentum, quality and volatility. For each of 16 factors across these categories, they sort country stock markets into fifths (quintiles) and measure the factor premium as return on the highest minus lowest quintiles….

Impact of Commodities Financialization on Strategies

…entitled “Strategies Based on Momentum and Term Structure in Financialized Commodity Markets”, Adam Zaremba investigates impacts of financialization of commodity markets on the profitability of momentum and term structure strategies. His base momentum strategy is each month long (short) the half of commodity futures with higher (lower) returns over the past month. His base term structure strategy is long (short) the half of commodity…

Popular Articles

    Momentum Strategy, Value Strategy and Trading Calendar Updates

    We have updated the the monthly asset class ETF momentum winners and associated performance data at Momentum Strategy. We have updated the the quarterly ETF weights and associated performance data at Value Strategy. We have updated the Trading Calendar to incorporate data for June 2015.

    Preliminary Momentum and Value Strategy Updates

    The home page and “Momentum Strategy” now show preliminary asset class ETF momentum strategy positions for July 2015. The differences in past returns among the top four places are fairly large, and the past returns for the top three positions are sufficiently above the Cash return, that selections are unlikely to change by the close. However, markets are volatile. The More

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    The Inflation Forecast now incorporates actual total and core Consumer Price Index (CPI) data for May 2015. The actual total (core) inflation rate for May is a little higher than (about the same as) forecasted.

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    In the introduction to their 2015 book entitled Invest with the Fed: Maximizing Portfolio Performance by Following Federal Reserve Policy, authors Robert Johnson, Gerald Jensen and Luis Garcia-Feijoo state: “Our purpose in writing this book is to provide a general overview of the Fed’s role in the financial markets, but, more important, to offer investors a road More

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    In the preface to the 2015 Third Edition of Irrational Exuberance, author Robert Shiller states: “…evidence of bubbles has accelerated since the [2007-2009 world financial] crisis. Valuations in the stock and bond markets have reached high levels in the United States and some other countries, and valuations in the housing market have been increasing rapidly in many countries. …The More

    The Decision Moose Asset Allocation Framework

    A reader suggested a review of the Decision Moose asset allocation framework of William Dirlam. “Decision Moose is an automated framework for making intermediate-term investment decisions.” Decision Moose focuses on asset class momentum, as augmented by monetary policy, exchange rate and interest rate indicators. Its signals tell followers when to switch from one index fund More

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Current Momentum Winners

ETF Momentum Signal
for July 2015 (Final)

Winner ETF

Second Place ETF

Third Place ETF

Gross Compound Annual Growth Rates
(Since August 2006)
Top 1 ETF Top 2 ETFs
13.8% 14.1%
Top 3 ETFs SPY
14.0% 7.5%
Strategy Overview
Current Value Allocations

ETF Value Signal
for 3rd Quarter 2015 (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
13.4% 9.4% 8.4%
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