Strategic Allocation

Is there a best way to select and weight asset classes for long-term diversification benefits? These blog entries address this strategic allocation question.

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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

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

Update SACEVS Monthly Instead of Quarterly?

“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 are quarterly per the arrival rate of new corporate earnings information. The principal benchmark is a quarterly rebalanced portfolio of 60% SPY and 40% IEF. A subscriber asked whether monthly SACEVS updates outperform quarterly updates. Using monthly S&P 500 Index levelsquarterly S&P 500 earnings and monthly 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 during March 1989 through March 2015 (limited by availability of earnings data), and monthly 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

Optimal Rebalancing Frequency/Months?

Is there a preferred frequency and are there preferred month(s) for rebalancing conventional asset class portfolio holdings? To investigate we consider annual, semiannual and quarterly rebalancing of a simple portfolio targeting a 60-40 stocks-bonds mix. We consider all possible combinations of calendar month ends as rebalancing points. Because of estimation complexity, we ignore rebalancing (and dividend-reinvestment) frictions and tax implications, thereby giving an advantage to frequent rebalancing. Using dividend-adjusted monthly closes for SPDR S&P 500 (SPY) to represent stocks and Vanguard Total Bond Market Index (VBMFX) to represent bonds over the period January 1993 (SPY inception) through April 2015 (268 months or about 22 years), we find that: Keep Reading

Momentum in a Mean-variance Optimization Framework

Is intermediate-term asset class momentum a useful way to generate inputs (return, volatility and correlation forecasts) for a multi-class mean-variance optimization strategy? In their May 2015 paper entitled “Momentum and Markowitz: a Golden Combination”, Wouter Keller, Adam Butler and Ilya Kipnis test the effectiveness of using intermediate-term lookback intervals (1 to 12 months) to generate monthly long-only mean-variance optimized portfolios. They argue that such lookback intervals are more likely than conventional long (multi-year) intervals to provide forecasts that persist during one-month portfolio holding intervals. They name their approach Classical Asset Allocation (CAA). To test CAA, in addition to adopting the practical long-only constraint, they further:

  1. Select from the efficient frontier a target annualized portfolio volatility of either 10% (aggressive) or 5% (conservative).
  2. Forecast asset returns by averaging results from lookback intervals of 1, 3, 6 and 12 months.
  3. Forecast covariances (volatility-correlation relationships) from a 12-month lookback interval.
  4. Cap portfolio weights for risky assets at 25%, but do not cap weights for 3-month U.S. Treasury bills (T-bills) and 10-year U.S. Treasury notes (T-notes).
  5. Consider three universes of 8, 16 and 39 asset class proxies.
  6. Use equal weighting (EW) of all assets in a universe as a benchmark.

They introduce an optimizer program to streamline calculation of optimal portfolio weights. Using monthly total returns for 39 indexes spanning multiple asset classes as available during January 1914 through December 2014, they find that: Keep Reading

Simple Asset Class Leveraged ETF Momentum Strategy

Subscribers have asked whether substituting leveraged exchange-traded funds (ETF) in the “Simple Asset Class ETF Momentum Strategy” might enhance performance. To investigate, we execute the strategy with the following eight 2X leveraged ETFs, plus cash:

ProShares Ultra DJ-UBS Commodity (UCD)
ProShares Ultra MSCI Emerging Markets (EET)
ProShares Ultra MSCI EAFE (EFO)
ProShares Ultra Gold (UGL)
ProShares Ultra S&P500 (SSO)
ProShares Ultra Russell 2000 (UWM)
ProShares Ultra Real Estate (URE)
ProShares Ultra 20+ Year Treasury (UBT)
3-month Treasury bills (Cash)

We allocate all funds at the end of each month to the asset class leveraged ETF or cash with the highest total return over the past five months (5-1). Using monthly adjusted closing prices for the specified ETFs and the yield for Cash over the period January 2010 (the earliest month prices for all eight ETFs are available) through April 2014 (only 64 months), we find that: Keep Reading

Simple Asset Class Value and Momentum Diversification with Mutual Funds

“SACEMS-SACEVS Mutual Diversification” finds that the “Simple Asset Class ETF Value Strategy” (SACEVS) and the “Simple Asset Class ETF Momentum Strategy” (SACEMS) are mutually diversifying. Do the longer samples available for the “Simple Asset Class Value Strategy Applied to Mutual Funds” and the “Simple Asset Class Momentum Strategy Applied to Mutual Funds” confirm this finding? To check, we relate quarterly returns for the Best Value selections from the former and momentum winner (Top 1) mutual fund selections from the latter and look at the performance of an equally weighted portfolio of these two strategies (50-50). Using quarterly gross returns for the two strategies from the second quarter of 1998 through the first quarter of 2015, we find that: Keep Reading

SACEVS Performance When Stocks Rise and Fall

How differently does the “Simple Asset Class ETF Value Strategy (SACEVS)” perform when stocks rise and when stocks fall? This strategy seeks to exploit relative valuation of the term risk premium, the credit (default) risk premium and the equity risk premium via exchange-traded funds (ETF). To investigate, because the sample period available for mutual funds is much longer than that available for ETFs, we use instead the risk premium estimation methods (10-year rolling history of inputs) and strategy performance measurement approach from “Simple Asset Class Value Strategy Applied to Mutual Funds”, Specifically, each quarter we reform a Best Value portfolio (picking the asset associated with the most undervalued of the three premiums, if any) and a Weighted portfolio (weighting assets associated with all undervalued premiums according to degree of undervaluation) from the following four assets:

The benchmark is a quarterly rebalanced portfolio of 60% stocks and 40% U.S. Treasuries (60-40 VWUSX-VFIIX). We say that stocks rise (fall) during a quarter when the return for VWUSX is positive (negative). Using quarterly risk premium calculation data during January 1970 through March 2015, and quarterly dividend-adjusted closing prices for the three asset class mutual funds during June 1980 through March 2015 (140 quarters), we find that:

Keep Reading

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Current Momentum Winners

ETF Momentum Signal
for July 2015 (Final)

Winner ETF

Second Place ETF

Third Place ETF

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Top 3 ETFs SPY
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ETF Value Signal
for 3rd Quarter 2015 (Final)

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The asset with the highest allocation is the holding of the Best Value strategy.
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