Bonds

Is global diversification within asset classes disappearing as worldwide economic and financial integration increases? In their August 2016 paper entitled “Globalization and Asset Returns”, Geert Bekaert, Campbell Harvey, Andrea Kiguel and Xiaozheng Wang examine whether economic and financial integration increases global comovement of country equity, bond and currency exchange market returns. They examine three measures of return comovement for each asset class: average pairwise correlation, average beta relative to the world market and average idiosyncratic volatility. They apply these measures separately to developed markets and emerging markets. Using monthly equity, bond and currency exchange market returns in U.S. dollars for 26 developed markets and 32 emerging markets as available from various inceptions through December 2014, they find that: Keep Reading

A subscriber proposed adding an equity style momentum underlay to the Best Value version of the “Simple Asset Class ETF Value Strategy” (SACEVS). SACEVS each month allocates all capital to the one of the following asset class exchange-traded funds (ETF) corresponding to the most undervalued of the term, credit and equity risk premiums at prior month end, or to cash if no premium is undervalued:

3-month Treasury bills (Cash)
iShares 7-10 Year Treasury Bond (IEF)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
SPDR S&P 500 (SPY)

The proposed momentum underlay chooses SPY, iShares S&P 500 Value (IVE) or iShares S&P 500 Growth (IVW) based on highest five-month past return whenever the equity risk premium is most undervalued. Based on availability of inputs for month-end risk premium estimates, return calculations are based on closing prices for the first trading day of the next month. Using SACEVS premium estimate inputs since March 1989, first trading day of the month dividend-adjusted closes for SPY, IVE and IVW since IVE-IVW inception in May 2000 and first trading day of the month dividend-adjusted closes for IEF and LQD since their inception in July 2002, all through July 2016, we find that:

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Are high-yield government bonds good bets? In his January 2016 paper entitled “Finding Yield in A 2% World”, Mebane Faber applies a simple value metric to global government bonds. He specifies a value portfolio as the equally weighted third (Top 33%) of 30 government bonds with the highest nominal yields, reformed/rebalanced monthly. He considers two benchmarks: (1) an equally weighted portfolio of all 30 bonds (Equal Weight); and, (2) a GDP-weighted index of 10-year government bonds of 17 non-U.S. developed countries (Foreign 10-year). He also considers performance of U.S. government Treasury bills (T-bills), 10-year notes and 30-year bonds. Using monthly total returns for the specified bonds in U.S. dollars during 1950 through 2012, he finds that: Keep Reading

What do company valuation experts think about the level of the risk-free rate and the equity risk premium? In their October 2015 paper entitled “Huge Dispersion of the Risk-Free Rate and Market Risk Premium Used by Analysts in 2015”, Pablo Fernandez, Alberto Pizarro and Isabel Acín summarize assumptions about the risk-free rate (R_F) and the market/equity risk premium (MRP or ERP) used by expert analysts to value companies in six countries (France, Germany, Italy, Spain, UK and U.S.). Using 156 company valuation reports from 2015, they find that: Keep Reading

Are frontier government bonds useful as incremental diversifiers of diversified portfolios? In their September 2015 paper entitled “Frontier and Emerging Government Bond Markets”, Vanja Piljak and Laurens Swinkels examine the diversification value of U.S. dollar-denominated frontier government bonds at aggregate, regional and country levels. They first look at return correlations and then consider mean-variance portfolio optimization with global equities, U.S. Treasury bonds, U.S. high-yield corporate bonds, emerging government bonds and frontier government bonds. Using weekly total returns in U.S. dollars for 29 frontier government bond markets in the J.P. Morgan Next Generation Markets Index and for other J.P. Morgan bond indexes and the MSCI All Country World Index during December 2001 through December 2013, they find that: Keep Reading

We have made three changes to the “Simple Asset Class ETF Value Strategy” (SACEVS) based on results of  robustness tests and subscriber comments:

1. To employ fresher data, we decrease the SACEVS S&P 500 Index level and bond/bill yield measurement interval from quarterly to monthly. S&P 500 Index operating earnings updates are still quarterly.
2. To employ fresher data, we use end-of-measurement interval (end-of-month) bond/bill yields rather than average yields during the measurement interval.
3. To account for a lag in availability of bill/bond yield data, we delay signal execution by one trading day.

These changes are logical, but introduce some additional noise. They result in somewhat higher risk-adjusted performance for SACEVS, at the expense of some additional trading. Effects on the Weighted version of the strategy are greater than those on the Best Value version.

We are updating “Value Strategy” and some related tests accordingly.

“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 levels, quarterly 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

“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 levels, quarterly 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

Does the interaction of paradigmatic indicators of optimism (lumber demand) and pessimism (gold demand) tell investors when to take risk and when to avoid risk? In their May 2015 paper entitled “Lumber: Worth Its Weight in Gold: Offense and Defense in Active Portfolio Management”, Charles Bilello and Michael Gayed examine the recent relative performance of lumber (a proxy for economic activity via construction) and gold (a safe haven) as an indicator of future stock market and bond market performance. Specifically, if lumber futures outperform (underperform) spot gold over the prior 13 weeks, they go on offense (defense) the next week. They test this strategy on combinations of seven indexes comprising a spectrum of risk (listed lowest to highest): BofA Merrill Lynch 5-7 Year Treasury Index (Treasuries); CBOE S&P 500 Buy-Write Index (BuyWrite); S&P 500 Low Volatility Index (Low Volatility); S&P 500 Index (SP500); Russell 2000 Index (R2000); Morgan Stanley Cyclicals Index (Cyclicals); and, S&P 500 High Beta Index (High Beta). Using weekly nearest futures contract prices for random length lumber, weekly spot gold prices and weekly total returns for the seven test indexes during November 1986 (November 1990 for Low Volatility and High Beta) through January 2015, they find that: Keep Reading

Do variable retirement spending strategies offer greater utility than fixed-amount or fixed-percentage strategies? In his March 2015 paper entitled “Making Sense Out of Variable Spending Strategies for Retirees”, Wade Pfau compares via simulation ten retirement spending strategies based on a common set of assumptions. He classifies these strategies into two categories: (1) those based on decision rules (such as fixed real spending and fixed percentage spending); and, (2) actuarial models based on remaining portfolio balance and estimated remaining longevity. His bases comparisons on 10,000 Monte Carlo runs for each strategy. He assumes a retirement portfolio of 50% U.S. stocks and 50% U.S. government bonds with initial value $100,000, rebalanced annually after end-of-year 0.5% fees and beginning-of-year withdrawals. He calibrates initial spending where feasible by imposing a probability of X% (X=10) that real spending falls below $Y (Y=1,500) by year Z of retirement (Z=30). He treats terminal wealth as unintentional (in fact, undesirable), with the essential trade-off between spending more now and having to cut spending later. He ignores tax implications. Using historical return data from Robert Shiller and current levels of inflation and interest rates (see the chart below), he finds that: Keep Reading