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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Survey of Recent Research on Factors, Regimes and Robustness

Why and how should investors pursue investment premiums associated with factors that explain performance differences among related assets (like common stocks)? In the January 2015 version of his paper entitled “Better Investing Through Factors, Regimes and Sensitivity Analysis”, Cristian Homescu summarizes recent research on: (1) factor-based investing; (2) enhancement of factor-based investing via regime switching models; and, (3) strategy robustness testing. Factor investing means systematic targeting of premiums associated with factors that explain an exploitable portion of return and risk differences among securities within one or several asset classes. Based on recent streams of research, he concludes that:

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Reversal-enhanced Simple Asset Class ETF Momentum Strategy?

A subscriber hypothesized that combining short-term reversal with intermediate-term momentum would enhance momentum strategy performance. To investigate, we test a modification of the “Simple Asset Class ETF Momentum Strategy”, which each month allocates all funds at the end of each month to the one of the following asset class exchange-traded funds (ETF) or Cash with the highest total return over the past five months (Top 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)

The modification each month first identifies the top three ETFs or Cash based on past five-month returns and then picks the one of these three with the lowest return over the past five trading days (Top 3 Loser). This approach should pick intermediate-term winners that tend to benefit (or at least not suffer) from any reversal of short-term movements. Using daily and monthly dividend-adjusted closing prices for the asset class proxies and for SPDR S&P 500 (SPY) and the yield for Cash during February 2006 (when all ETFs are first available) through February 2015 (109 months), we find that: Keep Reading

Credit Risk Premium Magnitude and Dynamics

Is the reward for holding risky bonds material and distinct from the reward for holding stocks and the reward for holding longer term bonds? In their February 2015 paper entitled “Credit Risk Premium: Its Existence and Implications for Asset Allocation”, Attakrit Asvanunt and Scott Richardson measure and explore the predictability and diversification power of the credit (or default) risk premium associated with corporate bonds. They focus on the premium associated with creditworthiness of bonds by first removing the influence of duration/interest rates. They also test whether the credit risk premium diversifies the equity risk premium and the bond term premium. Using data for U.S. corporate bonds, the U.S. stock market, U.S. Treasury securities and economic indicators during 1927 through 2014 and for credit default swaps (CDS) during 2004 through 2014, they find that: Keep Reading

Dependence of Optimal Allocations on Investment Horizon

Does optimal asset allocation, as measured by Sharpe ratio, depend on investment horizon? In their January 2015 paper entitled “Optimal Asset Allocation Across Investment Horizons”, Ronald Best, Charles Hodges and James Yoder explore the optimal (highest Sharpe ratio) mix of long-term U.S. corporate bonds and large-capitalization U.S. common stocks across investment horizons from one to 25 years. They test portfolios ranging from 100%-0% to 0%-100% stocks-bonds in 5% increments with annual rebalancing. They estimate annual returns for stocks and bonds based on 87 years of historical data. They simulate the portfolio return distribution for a given n-year holding period via 2,500 iterations for each of two methods:

  1. Randomly select with replacement n years from the 87 years in the historical sample and use the annual returns for U.S. Treasury bills (T-bills, the risk-free rate), stocks and bonds for those n years in the order selected to calculate portfolio gross compound n-year excess returns. This method assumes year-to-year independence (zero autocorrelations) of annual returns for stocks and bonds, meaning no momentum or reversion.
  2. Randomly select a year from the first 87 – (n-1) years in the historical sample and use the annual returns for T-bills, stocks and bonds for that and the next n-1 consecutive years to calculate portfolio gross compound n-year excess returns. This method preserves historical autocorrelations in return series.

Using annual returns for T-bills, U.S. large-capitalization common stocks and U.S. long-term corporate bonds during 1926 through 2012, they find that: Keep Reading

Global Stocks-bonds Glidepath during Retirement

What is the best mix of stocks and bonds to hold during retirement worldwide? In his January 2015 paper entitled “The Retirement Glidepath: An International Perspective”, Javier Estrada compares outcomes for different stocks-bonds allocation strategies during retirement from a global perspective. He considers declining equity, rising equity and static glidepaths with an annual withdrawal rate of 4% (of the portfolio value at retirement) and annual rebalancing during a 30-year retirement period. He tests the following glidepaths:

  • Four declining equity strategies that begin with 100%-0%, 90%‐10%, 80%‐20% and 70%‐30% stocks-bonds allocations and shift toward bonds linearly via annual rebalancing.
  • Four mirror-image rising equity strategies that begin with 0%-100%, 10%-90%, 20%-80% and 30%-70% stocks-bonds allocations and shift toward stocks linearly via annual rebalancing.
  • Eleven static allocations ranging from 100%-0% to 0%-100% stocks-bonds allocations maintained via annual rebalancing, with focus on conventional or near-conventional 60%-40%, 50%-50% and 40%-60% allocations.

He focuses on the failure rate of these strategies during 81 overlapping 30-year retirement periods during 1900-2009. He also considers average and median terminal wealth/bequest, tail risk, annual volatility (standard deviation of annual returns) and upside potential. He defines tail risk (downside risk) as average terminal wealth for the 1%, 5% or 10% lowest values from the 81 periods. Using annual total real returns for stocks and government bonds for 19 countries (in local currency adjusted by local inflation) and for the world market (in dollars adjusted by U.S. inflation) during 1900 through 2009 (110 years), he finds that: Keep Reading

Simple Asset Class ETF Momentum Strategy as Diversifier

A subscriber inquired whether the “Simple Asset Class ETF Momentum Strategy” is a good diversifier of the U.S. stock market. This strategy allocates funds at the end of each month to the one (Top 1), equally weighted two (EW Top 2) or equally weighted three (EW Top 3) of the following 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 first look at correlations between momentum strategy returns and those of SPDR S&P 500 ETF (SPY) and Vanguard Balanced Index Investor Shares (VBINX), with the latter maintaining an approximately 60% allocation to the broad U.S. stock market and a 40% allocation to the U.S. corporate bond market. We then generate return statistics for portfolios that hold equally weighted combinations of: (1) the Top 1 momentum strategy and SPY, and (2) Top 1 and VBINX. Using monthly dividend-adjusted returns for the specified funds and the monthly Treasury bills yield as a proxy for Cash during January 2003 through January 2015, we find that: Keep Reading

Options for Retirement?

Is use of long-term stock index call options effective for those approaching retirement with desires of limiting exposure to crashes without sacrificing all benefit of equity exposure? In his January 2015 paper entitled “Individuals Approaching Retirement Have Options (Literally) to Secure a Comfortable Retirement”, Bryan Foltice proposes retirement strategies that employ stock index options during the five years before retirement (when prospective retirees tend to become very risk-averse) to limit equity risk while retaining some reward. These alternatives to conventional (100% stocks, 60%-40% stocks-bonds and 100% minus age in stocks) asset allocation strategies put core funds in Treasury Inflation-Protected Securities (TIPS) to secure retirement income at a real 75% of final working income and funds in excess of the core to buy long-term at-the-money stock index call options. He considers three option-based strategies:

  1. Buy 5-year options at age 60.
  2. Buy a 3-year option at age 60 and a 2-year option at age 63.
  3. Buy 1-year call options each year using the final five annual contributions.

Base modeling assumptions use 1928-2013 historical return statistics, with robustness tests assuming (1) an increased equity risk premium and (2) expectations derived from 2014 data through October. Modeling includes expected costs/fees. Using simulations based on estimates for U.S. stock market capital gains/dividends and for the TIPS real yield, he finds that: Keep Reading

Optimal Monthly Cycle for Simple Debt Class Mutual Fund Momentum Strategy?

In reference to “Optimal Monthly Cycle for Simple Asset Class ETF Momentum Strategy?”, a subscriber asked about an optimal monthly cycle for the “Simple Debt Class Mutual Fund Momentum Strategy”. This latter strategy each month allocates the entire portfolio value to the one of the following 12 debt class mutual funds with the highest past total return (optimally over the last two months):

T. Rowe Price New Income (PRCIX)
Thrivent Income A (LUBIX)
Vanguard GNMA Securities (VFIIX)
T. Rowe Price High-Yield Bonds (PRHYX)
T. Rowe Price Tax-Free High Yield Bonds (PRFHX)
Vanguard Long-Term Treasury Bonds (VUSTX)
T. Rowe Price International Bonds (RPIBX)
Fidelity Convertible Securities (FCVSX)
PIMCO Short-Term A (PSHAX)
Fidelity New Markets Income (FNMIX)
Eaton Vance Government Obligations C (ECGOX)
Vanguard Long-Term Bond Index (VBLTX)

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 funds based on closing prices five trading days after EOM each month. We use the historically optimal two-month fund momentum measurement interval. Using daily dividend-adjusted closes for the 12 funds during mid-December 1994 through mid-January 2015 (241 months), we find that: Keep Reading

Extended Simple Momentum Strategy Test of TSP Funds/Proxies

A subscriber asked about extending “Simple Momentum Strategy Applied to TSP Funds” back in time to 1988. That test employs the following five funds all available to U.S. federal government employees via the Thrift Savings Plan (TSP) starting in January 2001:

G Fund: Government Securities Investment Fund (G)
F Fund: Fixed Income Index Investment Fund (F)
C Fund: Common Stock Index Investment Fund (C)
S Fund: Small Cap Stock Index Investment Fund (S)
I Fund: International Stock Index Investment Fund (I)

S Fund and I Fund data limit the sample period. To extend the test back to first availability of G Fund, F Fund and C Fund data in February 1988 (January 1988 data is partial for TSP funds), we use Vanguard Small Cap Index Investors Fund (NAESX) as a proxy for the S Fund and Vanguard International Value Investors Fund (VTRIX) as a proxy for the I Fund prior to 2001. The subscriber requested first a sensitivity test of ranking intervals (one to 12 months), and then performance tests using the optimal ranking interval on portfolios consisting of the one fund with the highest past total return (Top 1), an equally weighted portfolio of the top two funds (EW top 2) and an equally weighted portfolio of the Top 3 funds (EW Top 3). Using monthly returns for the five TSP funds as available during February 1988 through December 2014 (323 months) and monthly returns for NAESX and VTRIX during February 1988 through December 2000, we find that: Keep Reading

Simple Asset Class ETF Momentum Strategy with SHY Return Filter

A subscriber suggested using iShares 1-3 Year Treasury Bond ETF (SHY) as a return filter for the“Simple Asset Class ETF Momentum Strategy” as a way to suppress maximum drawdown. The basic strategy each month allocates funds to the one, two or three of the following eight exchange-traded funds (ETF) plus cash, as proxied by U.S. Treasury bills (T-bills), with the highest returns 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)

The T-bill yield is an approximation of the (non-negative) yield paid on cash by brokers. SHY can have negative returns in response to a rise in interest rates because it holds U.S. Treasury notes of terms 1-3 years. We investigate in two steps: (1) substitute SHY for T-bills in the basic strategy; and, (2) apply the SHY filter, substituting SHY for any winning ETF with a lower past return than SHY. Using monthly dividend-adjusted closing prices for the specified ETFs and the yield on T-bills during February 2006 (when all ETFs become available) through December 2014 (107 months), we find that:

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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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