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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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“Real” Assets and Inflation

Which asset class best hedges inflation? In the September 2012 draft of his book chapter entitled “‘Real’ Assets”, Andrew Ang examines the behaviors of the following assets commonly thought to hold their value during times of high inflation (“real” assets): inflation-linked bonds, commodities, real estate and U.S. Treasury bills (T-bill). He focuses on inflation as year-over-year change in the U.S. Consumer Price Index for all urban consumers and all items, but considers also inflation rates for medical care and higher education. He distinguishes inflation hedging (measured by correlation of returns and inflation) from long-run asset class performance. Using asset class proxy returns and U.S. inflation rates as available through 2011, he finds that: Keep Reading

Stock Momentum and Bond Returns

What does price momentum of stocks, whether total or risk-adjusted, imply about future returns of associated corporate bonds? In their August 2012 paper entitled “Residual Equity Momentum for Corporate Bonds”, Daniel Haesen, Patrick Houweling and Jeroen Van Zundert compare the predictive powers of total stock price momentum and risk-adjusted (residual) stock price momentum to predict returns of same-firm bonds. To focus on firm effects, they remove the influence of interest rates by measuring bond returns in excess of duration-matched U.S. Treasury instruments. They form (overlapping) bond portfolios monthly by: (1) ranking firms into fifths (quintiles) based on cumulative stock returns in excess of the risk-free rate over a past interval (base case, six months); (2) skipping a month; and, (3) forming a hedge portfolio that is long (short) for the next 1, 3, 6 or 12 months the equally weighted bonds of firms in the quintile with the highest (lowest) past stock returns. They calculate residual stock returns via 36-month lagged rolling regressions of excess stock returns versus the Fama-French model risk factors (market, size, book-to-market). Using monthly returns for U.S. investment grade and high-yield corporate bonds and associated stocks (2,442 firms), and for duration-matched U.S. Treasury instruments and the three equity risk factors, during January 1994 through September 2011, they find that: Keep Reading

Exploiting Corporate Bond Responses to Aggregate Default Risk Shocks

How do general economic conditions and economy-wide default risk shocks affect corporate bond returns, especially past winners and losers? In the May 2012 draft of their paper entitled “Sources of Momentum in Bonds”, Hwagyun Kim, Arvind Mahajan and Alex Petkevich investigate the relationship between U.S. corporate bond momentum portfolio returns and U.S. aggregate default risk. They measure the momentum effect as average monthly gross returns of overlapping hedge portfolios formed each month by buying (selling) the equally weighted tenth of bonds with the highest (lowest) total cumulative returns over the past six months and holding for six months, with a skip-month between ranking and holding intervals. They measure aggregate default risk as the prior-month yield spread between the Moody’s CCC corporate bond index and the 10-year U.S. Treasury note. They define default risk shocks as deviations from the linear relationships between default risk this month and its values the prior two months. They define high (low) default risk shock conditions as those above (below) the inception-to-date median value of the series. Using price and yield data for all listed U.S. corporate bonds (excluding convertible bonds, asset-backed securities and bonds with very low capitalization) during January 1995 (101 bonds) through December 2010 (2,513 bonds), they find that: Keep Reading

Enhancing Financial Markets Volatility Prediction

Are there economic and financial variables that meaningfully predict return volatilities of financial markets? In their March 2012 paper entitled “A Comprehensive Look at Financial Volatility Prediction by Economic Variables”, Charlotte Christiansen, Maik Schmeling and Andreas Schrimpf investigate the ability of 38 economic and financial variables to predict return volatilities of four asset classes (stocks, foreign exchange, bonds and commodities). Asset class proxies are: (1) the S&P 500 Index; (2) spot levels for a basket of currencies versus the U.S. dollar; (3) 10-year Treasury note futures contract prices; and, (4) the S&P GSCI. They calculate actual (realized) monthly asset class volatilities from daily returns. They construct out-of-sample volatility forecasts based on iterative inception-to-date regressions of volatilities versus predictive variables. They use an autoregressive model (simple realized volatility persistence) as a benchmark. Using monthly data for 13 economic/financial variables and the S&P 500 Index realized volatility over the long period December 1926 through December 2010 (1,009 months) and monthly data for 38 variables and all four asset class volatilities during 1983 through 2010 (366 months), they find that: Keep Reading

Safe Haven Asset Dynamics

How does the effectiveness of safe havens vary over time? In the February 2012 draft of their paper entitled “Safe Haven Assets and Investor Behaviour under Uncertainty”, Dirk Baur and Thomas McDermott examine the roles of gold and U.S. Treasury instruments as safe haven assets during times of financial markets uncertainty. They define a safe haven asset as an asset that is either uncorrelated or negatively correlated with other assets when those other assets are in distress. They focus on the effects of changes in uncertainty (shocks) on asset values and on the pairwise relationships between stocks, bonds and gold. Using daily returns in U.S. dollars for a global stock market index, U.S. Treasuries (2-year, 10-year and 30-year) and gold bullion (spot and futures) from 1980 through 2010 (more than 8,000 daily returns over 31 years), they find that: Keep Reading

Bond Market-Aggregate Earnings Interactions

Do aggregate corporate earnings predict bond market returns? In his January 2012 paper entitled “Aggregate Earnings and Corporate Bond Markets”, Xanthi Gkougkousi investigates the relationship between aggregate earnings and corporate bond market returns. Using quarterly aggregate earnings for a broad sample of U.S. stocks with fiscal years ending in March, June, September and December and total quarterly returns for ten U.S. corporate bond indexes during January 1973 through December 2010 (360,614 firm-quarter observations), he finds that: Keep Reading

Stocks versus Bonds as Investment Horizon Lengthens

Should investors believe in the superiority of stocks for the long run and bonds for the short run? In his December 2011 paper entitled “Stocks, Bonds, Risk, and the Holding Period: An International Perspective”, Javier Estrada examines how the absolute and relative risks of stocks and bonds evolve as investment horizon grows (time diversification). Considering both annual and cumulative returns and various measures of variability/risk, he focuses on the question of whether stocks become less risky than bonds for long holding periods. Using annual total returns for stocks and bonds in 19 countries during 1900 through 2009, he finds that: Keep Reading

Real Value of TIPS for Investors

Can Treasury Inflation-Protected Securities (TIPS), with principal indexed to the U.S. non-seasonally adjusted Consumer Price Index for all urban consumers (CPI), play a valuable role in asset class diversification? In the January 2011 draft of their paper entitled “Optimal Portfolio Choice in Real Terms: Measuring the Benefits of TIPS”, Alvaro Cartea, Jonatan Saul and Juan Toro apply mean-variance optimization to measure the empirical diversification benefits of TIPS for long-term and short-term investors with portfolios including various combinations of equities, nominal Treasuries, commodities and real estate. Using nominal monthly returns for all TIPS issued before August 2009, grouped by maturity, for the period March 1997 through March 2010 (157 monthly observations) and contemporaneous returns for nominal U.S. Treasury instruments, U.S. stocks, commodities and U.S. home prices, they find that: Keep Reading

Futures Market Open Interest as Return Predictor

Do changes in the level of futures markets activity predict returns for corresponding asset classes? In their January 2011 paper entitled “What Does Futures Market Interest Tell Us about the Macroeconomy and Asset Prices?”, Harrison Hong and Motohiro Yogo relate futures markets open interest (the number of contracts outstanding) to future asset class returns. They focus on the 12-month change in open interest and 12-month future return. As noted by the authors, simple logic suggests that open interest should be a non-directional because each futures contract involves countering long and short positions. However, changes in the number of futures contracts could indicate changes in anticipated economic risks. Using monthly open interest data for 30 commodity futures, eight currency futures, ten bond futures, 14 stock index futures and corresponding asset class returns for periods from earliest availability of data through 2008, they find that: Keep Reading

Hedges and Safe Havens Across Asset Classes

How effectively and consistently do equities, bonds, oil, gold and the dollar serve as hedges and safe havens for each other? In their September 2010 paper entitled “Hedges and Safe Havens – An Examination of Stocks, Bonds, Oil, Gold and the Dollar”, Cetin Ciner, Constantin Gurdgiev and Brian Lucey investigate pairwise hedging and safe haven relationships among these five major assets/asset classes. The define an asset as a hedge (safe haven) for another if respective returns are uncorrelated or negatively correlated on average over the long term (during relatively short intervals of stress). They define the long term (relatively short intervals) as their entire sample period (rolling four-month subperiods). They define intervals of stress as returns in the lowest fourth of observations. Using daily levels of the S&P 500 Index, an index of 10-year Treasuries, nearest-month gold and oil futures and the Federal Reserve Nominal Trade Weighted Effective Index for the dollar from January 1985 through October 2009 (nearly 25 years), they find that: Keep Reading

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