Quantitative Management of Credit Portfolios

Abstract

Quantitative techniques have long been used to measure and control risk in credit portfolios. More recently, interest has grown in a systematic approach to generating alpha in credit, with the promise of improved scalability and lower management expenses. We review several signals that seek alpha in credit, including value, equity momentum, equity short interest, and post-earnings announcement drift, and demonstrate that such strategies can effectively complement a more fundamental approach. We also show how systematic strategies can exploit index inefficiencies, such as the overselling and subsequent recovery of fallen angels. Company ratings on environmental, social, and governance issues have become central to portfolio management, and we discuss various aspects of their use: how to measure their performance, how to glean alpha signals from them, and how to most effectively constrain them. Finally, liquidity and transaction costs have always been key concerns for credit portfolio managers. We discuss how the liquidity landscape has evolved with the rise in exchange-traded funds and portfolio trading in corporate bonds. Putting it all together, we discuss portfolio construction techniques that can optimally combine signals and integrate transaction costs.