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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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

Simple Asset Class ETF Momentum Strategy Update

We have updated the detail at “Momentum Strategy” to incorporate the historical data changes described in “Simple Asset Class ETF Momentum Strategy Data Changes”. The principal effects are to decrease the performance of the Top 1 portfolio and increase the performance of the Top 2 portfolio.

Over the coming week, we will accordingly update much of the supporting research listed at “Momentum Strategy”.

Relative Strength of 10-year and 30-year Treasuries as Regime Indicator

Does the relative performance of 10-year U.S. Treasuries and 30-year U.S. Treasuries offer a useful risk-on/risk-off regime change signal? In their February 2014 paper entitled “An Intermarket Approach to Tactical Risk Rotation Using the Signaling Power of Treasuries to Generate Alpha and Enhance Asset Allocation” (the National Association of Active Investment Managers’ 2014 Wagner Award third place winner), Michael Gayed and Charles Bilello examine whether the relationship between the monthly total returns of the 10-year and 30-year Treasuries usefully indicate when to hold (or tilt toward) Treasuries versus stocks. They reason that informed investors migrate toward intermediate-term (long-term) Treasuries when they anticipate strong (weak) economic conditions. Therefore, the relative strength of 10-year and 30-year Treasuries signals when to take an aggressive or defensive investment posture. Using monthly total returns for 10-year and 30-year Treasuries and for the broad U.S. stock market during April 1977 through December 2013, they find that: Keep Reading

Simple Asset Class ETF Momentum Strategy Universe Enhancers?

Would adding a systematically chosen exchange-traded fund (ETF) or note (ETN) asset class proxy to the base set used in the “Simple Asset Class ETF Momentum Strategy” improve performance? To investigate, we consider adding each of the following 14 ETFs/ETNs (suggested over time by subscribers) one at a time to the strategy:

iPath S&P 500 VIX Short-Term Futures (VXX)
iPath S&P 500 VIX Medium-Term Futures (VXZ)
Guggenheim Frontier Markets (FRN)
iPath DJ-UBS Copper Total Return Sub-Index (JJC)
United States Oil (USO)
JPMorgan Alerian MLP Index (AMJ)
iShares 7-10 Year Treasury Bond (IEF)
iShares TIPS Bond (TIP)
iShares iBoxx High-Yield Corporate Bond (HYG)
SPDR Barclays International Treasury Bond (BWX)
PowerShares DB G10 Currency Harvest (DBV)
SPDR Dow Jones International Real Estate (RWX)
PowerShares Global Listed Private Equity  (PSP)
First Trust US IPO Index (FPX)

In measuring strategy performance, we focus on monthly net return-risk ratio (average monthly net return divided by standard deviation of monthly returns). We calculate the return-risk ratio 14 times, each time adding just one of above to the following base set of nine assets (so each test involves ten 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)

We then relate the resulting 14 return-risk ratios to four characteristics of the respectively added assets: (1) average monthly return; (2) standard deviation of monthly returns; (3) average (pairwise) cross-correlation of monthly returns with the base set assets; and, (4) serial correlation of monthly returns. The objective is to determine whether any of these four characteristics explain asset contribution to the momentum strategy. Using dividend/split-adjusted monthly returns for the above 23 asset class proxies as available during January 2003 through April 2014 (a maximum of 135 monthly returns), we find that: Keep Reading

Simple Asset Class ETF Momentum Strategy Universe Sensitivity

How sensitive is the performance of the “Simple Asset Class ETF Momentum Strategy” to exclusion of each asset in the base set? To investigate empirically, we exclude each of the following exchange-traded funds (ETF) or notes (ETN) one at a time from strategy performance calculations:

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 focus on monthly net return-risk ratio (average monthly return divided by standard deviation of monthly returns) as a key strategy performance metric. We calculate the return-risk ratio nine times, each time excluding from consideration one of above nine assets. We then relate the nine return-risk ratios to four characteristics of the respectively excluded assets: (1) average monthly return; (2) standard deviation of monthly returns; (3) average (pairwise) cross-correlation of monthly returns with the other eight assets; and, (4) serial correlation of monthly returns. The objective is to determine whether any of these four characteristics explain asset contribution to the momentum strategy. Using dividend-adjusted monthly returns for the above nine asset class proxies as available during January 2003 through April 2014 (a maximum of 135 monthly returns), we find that: Keep Reading

Asset Class Diversification Effectiveness Factors

What factors make asset class diversification work? To investigate empirically, we consider the following mix of exchange-traded funds (ETF) as asset class proxies (the same used in “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)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

We calculate the monthly gross return-risk ratio (average monthly return divided by standard deviation of monthly returns) for an equally weighted, monthly rebalanced portfolio of all nine asset class proxies. We then recalculate the return-risk ratio nine times, each time excluding one of the assets, and relate the resulting return-risk ratios to three characteristics of the respectively excluded assets: (1) average monthly return; (2) standard deviation of monthly returns; and, (3) average (pairwise) cross-correlation of monthly returns with the other eight assets. The objective is to determine whether any of these three characteristics explain asset contribution to diversification benefit.  We ignore trading frictions associated with monthly rebalancing, which would be similar for all combinations. Using dividend-adjusted monthly returns for the above nine asset class proxies during September 2006 (so that monthly returns for all assets are available in equal-weight calculations) through April 2014 (92 monthly returns), we find that: Keep Reading

Add Stop-gain to Asset Class Momentum Strategy?

In response to “Add Stop-loss to Asset Class Momentum Strategy?”, a subscriber inquired whether a stop-gain rule would harvest positive volatility and thereby improve the performance of 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 (designated the 5-1 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)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

To investigate, we add to this strategy a stop-gain rule that: (1) exits the current winner ETF if its intra-month return exceeds a specified threshold; and, (2) re-enters the basic strategy by buying the next winner ETF at the end of the month. Using monthly unadjusted monthly highs and closes (in stop-gain calculations) and adjusted closes (in return calculations) for the asset class proxies and the yield for Cash during July 2002 (or inception if not available then) through March 2014 (141 months), we find that: Keep Reading

Realistic Long-short Strategy Performance

How well do long-short stock strategies work, after accounting for all costs? In their February 2014 paper entitled “Assessing the Cost of Accounting-Based Long-Short Trades: Should You Invest a Billion Dollars in an Academic Strategy?”, William Beaver, Maureen McNichols and Richard Price examine the net attractiveness of several long-short strategies as stand-alone investments (as for a hedge fund) and as diversifiers of the market portfolio. They also consider long-only versions of these strategies. Specifically, they consider five anomalies exposed by the extreme tenths (deciles) of stocks sorted by:

  1. Book-to-Market ratio (BM) measured annually.
  2. Operating Cash Flow (CF) measured annually as a percentage of average assets.
  3. Accruals (AC) measured annually as earnings minus cash flow as a percentage of average assets.
  4. Unexpected Earnings (UE) measured as year-over-year percentage change in quarterly earnings.
  5. Change in Net Operating Assets (ΔNOA) measured annually as a percentage of average assets.

For strategies other than UE, they reform strategy portfolios (long the “good” decile and short the “bad” decile) annually at the end of April using accounting data from the prior fiscal year. For UE, they reform the portfolio at the ends of March, June, September and December using prior-quarter data. They highlight cost of capital, financing costs and rebates received on short positions, downside risk and short-side contribution to performance. They assume that the same amount of capital supports either a long-only portfolio, or a portfolio with equal long and short sides (with the long side satisfying Federal Reserve Regulation T collateral requirements for the short side). They account for shorting costs as fees for initiating short positions plus an ongoing collateral rate set at least as high as the federal funds rate, offset by a rebate of 0.25% per year interest on short sale proceeds. They estimate stock trading costs as the stock-by-stock percentage bid-ask spread. They consider two samples (including delistings): (1) all U.S. listed stocks; and, (2) the 20% of stocks with the largest market capitalizations. Using accounting data as described above for all non-ADR firms listed on NYSE, AMEX and NASDAQ for fiscal years 1992 through 2011, and associated monthly stock returns during May 1993 through April 2013, they find that: Keep Reading

Add Stop-loss to Asset Class Momentum Strategy?

In response to “Stop-losses to Avoid Stock Momentum Crashes?”, a subscriber inquired whether a stop-loss rule would improve the performance of 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 (designated the 5-1 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)
SPDR Dow Jones REIT (RWR)
iShares Barclays 20+ Year Treasury Bond (TLT)
3-month Treasury bills (Cash)

To investigate, we add to this strategy a stop-loss rule that: (1) exits the current winner ETF if its intra-month return falls below a specified threshold; and, (2) re-enters the basic strategy by buying the next winner ETF at the end of the month. Using monthly dividend-adjusted/split-adjusted monthly lows and closes for the asset class proxies and the yield for Cash during July 2002 (or inception if not available then) through March 2014 (141 months), we find that: Keep Reading

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ETF Momentum Signal
for November 2014 (Final)

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