Bonds

Bonds have two price components, yield and response of price to prevailing interest rates. How much of a return premium should investors in bonds expect? How can investors enhance this premium? These blog entries examine investing in bonds.

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Simple Asset Class Value and Momentum Diversification with Mutual Funds

“SACEMS-SACEVS Mutual Diversification” finds that the “Simple Asset Class ETF Value Strategy” (SACEVS) and the “Simple Asset Class ETF Momentum Strategy” (SACEMS) are mutually diversifying. Do the longer samples available for the “Simple Asset Class Value Strategy Applied to Mutual Funds” and the “Simple Asset Class Momentum Strategy Applied to Mutual Funds” confirm this finding? To check, we relate quarterly returns for the Best Value selections from the former and momentum winner (Top 1) mutual fund selections from the latter and look at the performance of an equally weighted portfolio of these two strategies (50-50). Using quarterly gross returns for the two strategies from the second quarter of 1998 through the first quarter of 2015, we find that: Keep Reading

SACEVS Performance When Stocks Rise and Fall

How differently does the “Simple Asset Class ETF Value Strategy (SACEVS)” perform when stocks rise and when stocks fall? This strategy seeks to exploit relative valuation of the term risk premium, the credit (default) risk premium and the equity risk premium via exchange-traded funds (ETF). To investigate, because the sample period available for mutual funds is much longer than that available for ETFs, we use instead the risk premium estimation methods (10-year rolling history of inputs) and strategy performance measurement approach from “Simple Asset Class Value Strategy Applied to Mutual Funds”, Specifically, each quarter we reform a Best Value portfolio (picking the asset associated with the most undervalued of the three premiums, if any) and a Weighted portfolio (weighting assets associated with all undervalued premiums according to degree of undervaluation) from the following four assets:

The benchmark is a quarterly rebalanced portfolio of 60% stocks and 40% U.S. Treasuries (60-40 VWUSX-VFIIX). We say that stocks rise (fall) during a quarter when the return for VWUSX is positive (negative). Using quarterly risk premium calculation data during January 1970 through March 2015, and quarterly dividend-adjusted closing prices for the three asset class mutual funds during June 1980 through March 2015 (140 quarters), we find that:

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SACEVS Performance When Interest Rates Rise

A subscriber asked how the “Simple Asset Class ETF Value Strategy (SACEVS)” performs when interest rates rise. This strategy seeks to exploit relative valuation of the term risk premium, the credit (default) risk premium and the equity risk premium via exchange-traded funds (ETF). To investigate, because the sample period available for mutual funds is much longer than that available for ETFs, we use instead the risk premium estimation methods (10-year rolling history of inputs) and strategy performance measurement approach from “Simple Asset Class Value Strategy Applied to Mutual Funds”, Specifically, each quarter we reform a Best Value portfolio (picking the asset associated with the most undervalued of the three premiums, if any) and a Weighted portfolio (weighting assets associated with all undervalued premiums according to degree of undervaluation) from the following four assets:

The benchmark is a quarterly rebalanced portfolio of 60% stocks and 40% U.S. Treasuries (60-40 VWUSX-VFIIX). We use the above T-bill yield as the short-term interest rate (SR) and the 10-year Constant Maturity U.S. Treasury note (T-note) yield as the long-term interest rate (LR). We say that each rate rises or falls when the associated average quarterly yield increases or decreases from quarter to quarter. Using quarterly risk premium calculation data during January 1970 through March 2015, quarterly average SR and LR, and quarterly dividend-adjusted closing prices for the three asset class mutual funds during June 1980 through March 2015 (140 quarters), we find that:

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Effects of Execution Delay on Simple Asset Class ETF Value Strategy

“Effects of Execution Delay on Simple Asset Class ETF Momentum Strategy” investigates how delaying signal execution affects strategy performance. How does execution delay affect the performance of the complementary Best Value version of the “Simple Asset Class ETF Value Strategy”? This latter strategy each quarter allocates all funds to the one of the following asset class exchange-traded funds (ETF) associated with the most undervalued risk premium (term, credit or equity), or to cash if none are 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)

To investigate, we compare 23 variations of the strategy that all use end-of-quarter (EOQ) to determine the best value asset but shift execution from the contemporaneous EOQ to the next open or to closes over the next 21 trading days (about one month). For example, an EOQ+5 Close variation uses an EOQ cycle to determine winners but delays execution until the close five trading days after EOQ. Using daily dividend-adjusted opens and closes for the risk premium proxies and the yield for Cash from the end of September 2002 through the end of March 2015 (51 quarters), we find that:

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Comparison of Variable Retirement Spending Strategies

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

Bond Style Performance and Exploitation

Does a factor (style) premium model identify exploitable abnormal corporate bond returns? In their March 2015 paper entitled “Investing with Style in Corporate Bonds”, Ronen Israel, Johnny Kang and Scott Richardson investigate the usefulness of four bond return factors:

  1. Carry – the fixed spread that must be added to the U.S. Treasuries yield curve such that the discounted payments of the corporate bond match its traded market price.
  2. Defensive (low-risk) – corporate bond from an issuer with low levels of market leverage (total debt divided by the sum of total debt and market value of equity).
  3. Momentum – trailing 6-month corporate bond return in excess of the risk-free rate.
  4. Value – corporate bond with a high carry relative to the issuer’s fundamental distance-to-default (measured via linear regression).

Specifically, they measure the ability of these four factors to explain future excess (negating the role of interest rates) returns of different corporate bonds. They also test exploitability via a long-only portfolio with exposure to the factors. Finally, they check the degrees to which actively managed credit hedge and mutual funds actually exploit the factors. Using monthly data for a broad (but filtered) sample of U.S. corporate bonds/issuers (10,825 bonds and 5,300 issuers) and monthly return data for 213 actively managed credit hedge funds and 218 actively managed credit mutual funds during January 1997 through December 2013, they find that: Keep Reading

SACEMS-SACEVS Mutual Diversification

Are the “Simple Asset Class ETF Value Strategy” (SACEVS) and the “Simple Asset Class ETF Momentum Strategy” (SACEMS) mutually diversifying. To check, we relate quarterly returns for the SACEVS Best Value and the SACEMS Top 1 exchange-traded fund (ETF) selections and look at the performance of an equally weighted portfolio of these two strategies (50-50). Using quarterly gross returns for SACEVS Best Value and SACEMS Top 1 during January 2003 through December 2014, we find that: Keep Reading

Simple Asset Class Value Strategy Applied to Mutual Funds

“Simple Asset Class ETF Value Strategy” finds that investors may be able to exploit relative valuation of the term risk premium, the credit (default) risk premium and the equity risk premium via exchange-traded funds (ETF). However, the backtesting period is limited by available histories for ETFs and for the series used to estimate risk premiums. To construct a longer test, we make the following substitutions for potential holdings (selected for length of available samples):

To enable estimation of risk premiums over a longer history, we also substitute:

We retain quarterly average yields for Moody’s Seasoned Baa Corporate Bonds for calculation of the credit risk premium. As with ETFs, we consider two alternative strategies for exploiting premium undervaluation: Best Value, which picks the most undervalued premium; and, Weighted, which weights all undervalued premiums according to degree of undervaluation. Based on the assets considered, the principal benchmark is a quarterly rebalanced portfolio of 60% stocks and 40% U.S. Treasuries (60-40 VWUSX-VFIIX). Using quarterly risk premium calculation data during January 1934 through December 2014 (limited by availability of Moody’s Baa data), and quarterly dividend-adjusted closing prices for the three asset class mutual funds during June 1980 through December 2014 (139 quarters), we find that:

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Simple Asset Class ETF Value Strategy

Does a simple relative value strategy applied to tradable asset class proxies produce attractive results? To investigate, we test a simple strategy on the following three asset class exchange-traded funds (ETF), plus cash:

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

This set of ETFs relates to three factor risk premiums: (1) the difference in yields between Treasury bills and Treasury note/bonds indicates the term risk premium; (2) the difference in yields between corporate bonds and Treasury notes/bonds indicates the credit (default) risk premium; and, (3) the difference in yields between equities and Treasury notes/bonds indicates the equity risk premium. We consider two alternative strategies for exploiting premium undervaluation: Best Value, which picks the most undervalued premium; and, Weighted, which weights all undervalued premiums according to degree of undervaluation. Based on the assets considered, the principal benchmark is a quarterly rebalanced portfolio of 60% stocks and 40% U.S. Treasury notes (60-40 SPY-IEF). Using quarterly S&P 500 Index levels and earnings, quarterly average yields for 3-month Constant Maturity U.S. Treasury bills (T-bills), quarterly average yields for 10-year Constant Maturity U.S. Treasury notes (T-notes), quarterly average yields for Moody’s Seasoned Baa Corporate Bonds during March 1989 through December 2014 (limited by availability of earnings data), and quarterly dividend-adjusted closing prices for the above three asset class ETFs during September 2002 through December 2014 (45 quarters, limited by availability of IEF and LQD), we find that: Keep Reading

Year-end Global Growth and Future Asset Class Returns

Does fourth quarter global economic data set the stage for asset class returns the next year? In their February 2015 paper entitled “The End-of-the-year Effect: Global Economic Growth and Expected Returns Around the World”, Stig Møller and Jesper Rangvid examine relationships between level of global economic growth and future asset class returns, focusing on growth at the end of the year. Their principle measure of global economic growth is the equally weighted average of quarterly OECD industrial production growth in 12 developed countries. They perform in-sample tests 30 countries and out-of-sample tests for these same 12 countries (for which more data are available). Out-of-sample tests: (1) generate initial parameters from 1970 through 1989 data for testing during 1990 through 2013 period; and, (2) insert a three-month delay between economic growth data and subsequent return calculations to account for publication lag. Using global industrial production growth as specified, annual total returns for 30 country, two regional and world stock indexes, currency spot and one-year forward exchange rates relative to the U.S. dollar, spot prices on 19 commodities, total annual returns for a global government bond index and a U.S. corporate bond index, and country inflation rates as available during 1970 through 2013, they find that: Keep Reading

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ETF Momentum Signal
for May 2015 (Final)

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ETF Value Signal
for 2nd Quarter 2015 (Final)

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The asset with the highest allocation is the holding of the Best Value strategy.
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