Strategic Allocation

Treasury Inflation-Protected Securities (TIPS), offering an explicit inflation hedge, may be an attractive asset for strategic diversification. To check, we add iShares Barclays TIPS Bond Fund (TIP) to the following mix of 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)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for TIP and the average pairwise correlation of TIP monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without TIP. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for TIP and the above nine asset class proxies as available from January 2004 (first available for TIP) through April 2013 (112 monthly returns), we find that: Keep Reading

It is plausible that crude oil as a dominant energy commodity has return characteristics substantially different from those of other commodities and asset classes, and therefore represent a good diversification opprotunity. To check, we add iShares Barclays 7-10 Year Treasury (IEF) to the following mix of 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)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for IEF and the average pairwise correlation of IEF monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without IEF. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for IEF and the above nine asset class proxies as available from January 2003 (the start of the “Simple Asset Class ETF Strategy”) through April 2013 (124 monthly returns), we find that: Keep Reading

A subscriber suggested testing the diversification power of exchange-traded aggregations of U.S. pipeline Master Limited Partnerships, such as JPMorgan Alerian MLP Index ETN (AMJ), as a distinct asset class. To check, we add AMJ to the following mix of 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)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for AMJ and the average pairwise correlation of AMJ monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without AMJ. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for AMJ and the above nine asset class proxies from July 2009 (first return available for AMJ) through April 2013 (only 46 monthly returns), we find that: Keep Reading

It is plausible that crude oil as a dominant energy commodity has return characteristics substantially different from those of other commodities and asset classes, and therefore represents a good diversification opportunity. To check, we add the United States Oil Fund (USO) to the following mix of 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)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for USO and the average pairwise correlation of USO monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without USO. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for USO and the above nine asset class proxies as available from May 2006 (first return available for USO) through April 2013 (84 monthly returns), we find that: Keep Reading

A subscriber suggested testing the diversification power of iPath DJ-UBS Copper ETN (JJC) as a distinct asset class. To check, we add JJC to the following mix of 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)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for JJC and the average pairwise correlation of JJC monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without JJC. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for JJC and the above nine asset class proxies from November 2007 (first return available for JJC) through April 2013 (66 monthly returns), we find that: Keep Reading

Does adding a proxy for the least developed (frontier) equity markets to a diversified portfolio improve its performance? To check, we add Guggenheim Frontier Markets ETF (FRN) to the following mix of 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)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for FRN and the average pairwise correlation of FRN monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without FRN. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for FRN and the above nine asset class proxies from July 2008 (first return available for FRN) through April 2013 (58 monthly returns), we find that: Keep Reading

Market volatility tends to rise as returns fall. Does adding a proxy for intermediate-term U.S. equity market volatility to a diversified portfolio improve its performance? To check, we add iPath S&P 500 VIX Mid-Term Futures (VXZ) to the following mix of 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)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for VXZ and the average pairwise correlation of VXZ monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without VXZ. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for VXZ and the above nine asset class proxies from March 2009 (first return available for VXZ) through April 2013 (only 50 monthly returns), we find that: Keep Reading

Market volatility tends to rise as returns fall. Does adding a proxy for short-term U.S. equity market volatility to a diversified portfolio improve its performance? To check, we add iPath S&P 500 VIX Short Term Futures (VXX) to the following mix of 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)

First, per the findings of “Asset Class Diversification Effectiveness Factors”, we measure the average monthly return for VXX and the average pairwise correlation of VXX monthly returns with the monthly returns of the above assets. Then, we compare cumulative returns and basic monthly return statistics for equally weighted (EW), monthly rebalanced portfolios with and without VXX. We ignore rebalancing frictions, which would be about the same for the alternative portfolios. Using adjusted monthly returns for VXX and the above nine asset class proxies from February 2009 (first return available for VXX) through April 2013 (only 51 monthly returns), we find that: Keep Reading

How should investors think about alternative asset allocation strategies for risk management? In his May 2013 paper entitled “Advances in Portfolio Risk Control. Risk! Parity?”, Winfried Hallerbach offers a practitioner’s review of new and revived portfolio allocation strategies, including: Equal Weight, Maximum Diversification, Minimum Variance; Equal Risk Contribution (Risk Parity); Inverse Volatility; Maximum Sharpe Ratio; and, Volatility Targeting. He addresses their pluses and minuses and compares them to each other. He observes that the large contribution of equities to (downside) risk within portfolios that lean only moderately toward stocks provides the impetus for risk management research. Based on key studies of portfolio risk management and examples using monthly data for four U.S. asset classes (risk-free rate, stocks, aggregate Treasuries, corporate investment grade bonds, and corporate high-yield bonds) during June 2002 through May 2012, he finds that: Keep Reading

Can investors use aggregate pairwise return correlations across asset classes to identify and exploit financial market regimes? In the April 2013 draft of their paper entitled “Handling Risk On/Risk Off Dynamics with Correlation Regimes and Correlation Networks”, Jochen Papenbrock and Peter Schwendner describe an approach for discovering market regimes based on pairwise correlations across 25 series of futures contracts spanning four asset classes. Each month, they calculate the set of pairwise correlations for these series based on daily returns and assign the resulting correlation structure to one of five regimes. They then look at the data within each regime to count the number of distinct groups of assets based on correlation clustering, with the potential that investors could view clusters as de facto asset classes. Using daily returns for 25 series of rolling futures contracts (six government bonds, seven equity indexes, six commodities and six currency exchange rates) during July 1998 through January 2013 to generate 175 sets of 25×25 monthly correlation matrices, they find that: Keep Reading