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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Optimal Monthly Cycle for Simple Asset Class ETF Momentum Strategy?

As explored for a 10-month simple moving average (SMA) in “Optimal Cycle for Monthly SMA Signals?”, subscribers have inquired whether there is a best time of the month for measuring momentum in the “Simple Asset Class ETF Momentum Strategy”. This strategy each month allocates all funds to the one of the following eight asset class exchange-traded funds (ETF), or cash, with the highest total return over the past five months:

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)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

To investigate, we compare 21 variations of the strategy based on shifting the monthly return calculation cycle relative to trading days from the end of the month (EOM). For example, an EOM+5 cycle ranks assets based on closing prices five trading days after EOM each month. Using daily dividend-adjusted closes for the asset class proxies and the yield for Cash from late July 2002 (or inception if not available then) through early June 2014 (about 143 months), we find that: Keep Reading

Risk Parity Strategy Performance When Rates Rise

Risk parity asset strategies generally make large allocations to low-volatility assets such as bonds, which tend to fall in value when interest rates rise. Is risk parity a safe strategy when rates rise? In their June 2014 research note entitled “Risk-Parity Strategies at a Crossroads, or, Who’s Afraid of Rising Yields?”, Fabian Dori, Manuel Krieger, Urs Schubiger and Daniel Torgler examine how the rising interest rate environment of the U.S. in the 1970s affects risk parity performance. They also examine how inflation and economic growth affect risk parity performance. They use the yield on the 10-year U.S. Treasury note (T-note) as a proxy for the interest rate. Their risk parity model uses 40-day past volatility for risk weighting and allows leverage to target an annualized portfolio volatility (7.5%, per Fabian Dori). They consider two benchmark portfolios: conservative, allocating 60% to bonds, 30% to stocks and 10% to commodities; and, aggressive, allocating 40% to bonds, 40% to stocks and 20% to commodities. They rebalance all portfolios daily, including estimated transaction costs. They compare six-month returns of risk parity and benchmark portfolios across ranked fifths (quintiles) of contemporaneous six-month changes in interest rates, inflation and Gross Domestic Product (GDP) growth rate. Using daily levels of a generic 10-year T-note, the S&P 500 Index and the Goldman Sachs Commodity Index during January 1970 through June 1996 and actual daily futures prices for 2-year, 5-year and 10-year T-notes, the S&P 500 Index, the NASDAQ 100 Index and the DJ UBS Commodity Index during July 1996 through April 2014, along with contemporaneous interest rate, inflation and GDP data, they find that: Keep Reading

Sticky Winner Asset Class ETF Momentum Strategy

A subscriber requested testing of an alternative implementation of the “Simple Asset Class ETF Momentum Strategy”, as follows: “Buy the first winner to establish an initial position. Hold the position as long as it remains among the top three assets; if it drops out of the top three, replace it with the most recent winner. This strategy should suppress trading frictions and may alleviate capital gains taxes.” To investigate, we compare this alternative (Sticky Winner) to the original strategy (Winner), which allocates all funds at the end of each month to the asset class exchange-traded fund (ETF) or cash with the highest total return over the past five months, as applied to the following nine assets:

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)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

Using monthly adjusted closing prices for the asset class proxies and the yield for Cash over the period July 2002 (or inception if not available then) through May 2014 (143 months), we find that: Keep Reading

Unleashing the Snoop Dog on the Simple Asset Class ETF Momentum Strategy?

The “Simple Asset Class ETF Momentum Strategy” each month allocates all funds to the one of the following eight asset class exchange-traded funds (ETF), or cash, with the highest total return over the past five months:

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)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

“Simple Asset Class ETF Momentum Strategy Robustness/Sensitivity Tests” shows that, among uniform ranking intervals, five months is optimal. Citing the optimality of a three-month ranking interval in “Simple Debt Class Mutual Fund Momentum Strategy”, a subscriber inquired whether using a three-month ranking interval just for TLT might improve Simple Asset Class ETF Momentum Strategy performance. To investigate more generally, we compute net terminal values for 108 variations of the strategy by letting the ranking interval for each asset range from one to 12 months, while holding the ranking interval for all other assets at five months. In order to compare ranking intervals of different lengths, we use the average total return per month for ranking. For example, the average monthly total return for a five-month ranking interval is the five-month total return divided by five. Using monthly dividend-adjusted closes for the asset class proxies and the yield for Cash during July 2002 (or inception if not available then) through May 2014 (141 months), we find that:

Keep Reading

Weekly or Monthly Asset Class ETF Momentum?

Subscribers asked whether weekly measurement of asset class momentum works better than monthly measurement as described in  “Simple Asset Class ETF Momentum Strategy”. To investigate, we compare simple weekly and monthly strategies as applied to 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 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)

For the weekly (monthly) strategy, we allocate all funds at the end of each week (month) to the asset class ETF or cash with the highest total return over the past 20 weeks (five months), designating the strategy as 20W-1W (5M-1M). Using weekly and monthly dividend-adjusted closing prices for the asset class proxies and the yield for Cash during July 2002 (or inception if not available then) through May 2014 (143 months), we find that: Keep Reading

Simple Asset Class ETF Momentum Strategy vs. Luck

The basic Simple Asset Class Momentum Strategy allocate all funds at the end of each month to the one of the following asset class ETFs or cash with the highest total return over the past five months (5-1). 

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)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

Can pure luck beat this strategy? To investigate, we run 1,000 trials of a competing “strategy” that allocates all funds each month to one of the nine assets picked at random. Using monthly adjusted closing prices for the asset class proxies and the yield for Cash over the period July 2002 (or inception if not available then) through May 2014 (143 months), we find that: Keep Reading

Asset Class Momentum Faster During Bear Markets?

A subscriber asked whether the optimum ranking interval for the “Simple Asset Class ETF Momentum Strategy” shrinks from five months to three months during bear markets for U.S. stocks. To investigate, we compare strategy performance during U.S. stock market bull and bear conditions for different ranking intervals, as applied to 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 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 consider both a visualization of U.S. equity bull and bear conditions and a tradable rule that conditions are bullish or bearish when the S&P 500 Index at the previous monthly close is above or below its 10-month simple moving average (SMA10). We consider ranking intervals ranging from one month (1-1) to 12 months (12-1), all with one-month holding intervals. We use a switching friction of 0.25% (0.125% each way) to estimate net monthly returns. Using monthly closes for the dividend-adjusted prices of the asset class proxies, the yield for Cash and the level of the S&P 500 Index during July 2002 (or inception if not available then) through May 2014 (143 months), we find that: Keep Reading

Simple Asset Class ETF Momentum Strategy Robustness/Sensitivity Tests

How sensitive is the performance of the “Simple Asset Class ETF Momentum Strategy” to selecting ranks other than winners and to choosing a momentum ranking interval other than five months? This strategy each month ranks the following eight asset class exchange-traded funds (ETF), plus cash, on past return and rotates to the strongest class:

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)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

Available data are so limited that sensitivity test results may mislead. With that reservation, we perform two robustness/sensitivity tests: (1) comparison of returns for all nine ranks of winner through loser based on a ranking interval of five months and a holding interval of one month (5-1); and, (2) comparison of winner returns for ranking intervals ranging from one to 12 months (1-1 through 12-1) and for a six-month lagged six-month ranking interval (12:7-1) per “Isolating the Decisive Momentum (Echo?)”, all with one-month holding intervals. Using monthly adjusted closing prices for the asset class proxies and the yield for Cash over the period July 2002 (or inception if not available then) through May 2014 (143 months), we find that: Keep Reading

Alternative Asset Class ETF Momentum Allocations

A subscriber suggested an alternative to the “Simple Asset Class ETF Momentum Strategy” that weights asset class ETFs according to five-month past return ranking (such as 35-25-20-10-4-3-2-1) rather than allocating all funds to the winner. Do the diversification benefits of this alternative outweigh the loss of momentum purity? To investigate, we return to 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 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)

As one benchmark, we allocate 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 (5-1). As another benchmark, we maintain an equal-weighted (EW), monthly rebalanced portfolio of all nine asset classes. As alternatives, we test two momentum rank-weighted (RW), linearly-scaled combinations of all nine classes, one steep across ranks and one shallow. We also test EW combinations of the Top 5, Top 4, Top 3 and Top 2 momentum ranks. Using monthly adjusted closing prices for the asset class proxies and the yield for Cash over the period February 2006 (the earliest all ETFs are available) through May 2014 (100 months), we find that: Keep Reading

Simple Asset Class ETF Momentum Strategy

Does a simple relative momentum strategy applied to tradable asset class proxies produce attractive results? To investigate, we test a simple strategy on 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 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)

This set of ETFs: (1) offers opportunities to capture momentum across U.S., non-U.S. developed and emerging equity markets, large and small U.S. equities and bonds and commodities; (2) offers gold and cash as safe havens; (3) offers histories long enough for backtesting across multiple market environments; and, (4) keeps it simple in recognition of the trade-off between number of ETFs and trading frequency. We allocate 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 (5-1). The five-month ranking period is optimal based on sensitivity tests. Using monthly dividend-adjusted closing prices for the asset class proxies and the yield for Cash during July 2002 (or inception if not available then) through May 2014 (143 months), we find that: Keep Reading

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