TY - JOUR T1 - A Model-Based Approach to Constructing Corporate Bond Portfolios JF - The Journal of Fixed Income SP - 57 LP - 71 DO - 10.3905/jfi.2012.22.2.057 VL - 22 IS - 2 AU - Zan Li AU - Jing Zhang AU - Christopher Crossen Y1 - 2012/09/30 UR - https://pm-research.com/content/22/2/57.abstract N2 - The authors develop a model-based approach for constructing investment-grade and high-yield corporate bond portfolios that outperforms their respective prevalent benchmark indices and popular exchange-traded funds (ETFs), with better risk–return profiles—that is, higher returns with lower or similar risk. More importantly, they obtain outperformance after controlling for credit risk, duration risk, and downside risk. The outperformance is robust across a number of different specifications of the strategy and over time. The authors also achieve outperformance by using relatively smaller, more realistic portfolios. These model portfolios can be potentially converted into new fixed-income indices or ETFs. Their model-based approach uses Moody’s Analytics’ EDF™ (expected default frequency) credit measures and the fair-value spread (FVS) valuation framework as powerful tools to control for credit risk and to exploit relative value in the bond market.To make our approach realistic and operational, we compile our investment universe from the Merrill Lynch Corporate Master Indices by applying a number of filtering criteria to our bond selection rules. We assess our model portfolios’ performance relative to Merrill Lynch (ML) and iBoxx indices, the two most widely-used fixed income portfolio benchmarks. To obtain a closer measure of the actual returns investors can achieve, we also compare results to the popular fixed-income Exchange Traded Funds (iShares ETFs) that focus on corporate credit. Additionally, we compare performance relative to the actively managed mutual fund universe, the respective U.S. fixed core fund universe. Our analyses factor in transaction costs.TOPICS: Fixed-income portfolio management, portfolio construction, credit risk management ER -