Credit portfolio managers traditionally rely on fundamental research for decisions on issuer selection and sector rotation. Quantitative researchers tend to use more mathematical techniques for pricing models and to quantify credit risk and relative value. The information found here bridges these two approaches. In an intuitive and readable style, this book illustrates how quantitative techniques can help address specific questions facing today's credit managers and risk analysts.

A targeted volume in the area of credit, this reliable resource contains some of the most recent and original research in this field, which addresses among other things important questions raised by the credit crisis of 2008-2009. Divided into two comprehensive parts, Quantitative Credit Portfolio Management offers essential insights into understanding the risks of corporate bonds-spread, liquidity, and Treasury yield curve risk-as well as managing corporate bond portfolios.

• Presents comprehensive coverage of everything from duration time spread and liquidity cost scores to capturing the credit spread premium
• Written by the number one ranked quantitative research group for four consecutive years by Institutional Investor
• Provides practical answers to difficult question, including: What diversification guidelines should you adopt to protect portfolios from issuer-specific risk? Are you well-advised to sell securities downgraded below investment grade?

Credit portfolio management continues to evolve, but with this book as your guide, you can gain a solid understanding of how to manage complex portfolios under dynamic events.

Created by members of the Quantitative Portfolio Strategy Group at Barclays Capital Research—a recognized authority in this field—Quantitative Credit Portfolio Management contains new insights that credit market practitioners, from portfolio managers to research analysts, will find useful, practical, and easy to apply.

Written in an intuitive yet quantitatively rigorous style, this timely publication opens with a detailed look at new measures of spread risk, liquidity risk, and Treasury curve risk of credit securities. It presents strong empirical evidence of the benefits these measures offer to portfolio managers compared with current standard industry methods. From there, it moves on to examining applications of these risk measures to portfolio construction and management. The authors also examine the best ways of capturing more of the spread premium in credit portfolios.

All along the way, the authors maintain a sharp focus on the "out-of-sample" predictive power of their research results and their practical implications, with special attention given to the 2007–2009 credit crisis and the subsequent European sovereign crisis.

In this book, the authors:

• Build a case for a Duration Times Spread (DTS) approach to forecasting spread changes and managing risk in credit portfolios based on their finding that spread volatility is linearly related to spread levels
• Introduce a security-level numeric measure of transaction costs—Liquidity Cost Scores (LCS)—which enables investors to quantify the liquidity component of credit spreads and construct portfolios with desired liquidity characteristics
• Demonstrate an approach to optimal diversification of issuer-specific risk in credit portfolios
• Suggest downgrade-tolerant credit portfolios as a way to avoid discarding credit spread premium with the forced liquidation of "fallen angels" as they get dropped from investment grade indices
• Examine "fallen angels" themselves, as a separate asset class, with superior risk and return characteristics