Details

Quantitative Credit Portfolio Management


Quantitative Credit Portfolio Management

Practical Innovations for Measuring and Controlling Liquidity, Spread, and Issuer Concentration Risk
Frank J. Fabozzi Series, Band 202 1. Aufl.

von: Arik Ben Dor, Lev Dynkin, Jay Hyman, Bruce D. Phelps

74,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 08.11.2011
ISBN/EAN: 9781118167427
Sprache: englisch
Anzahl Seiten: 416

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Beschreibungen

<b>An innovative approach to post-crash credit portfolio management</b> <p>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.</p> <p>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, <i>Quantitative Credit Portfolio Management</i> offers essential insights into understanding the risks of corporate bonds—spread, liquidity, and Treasury yield curve risk—as well as managing corporate bond portfolios.</p> <ul> <li>Presents comprehensive coverage of everything from duration time spread and liquidity cost scores to capturing the credit spread premium</li> <li>Written by the number one ranked quantitative research group for four consecutive years by <i>Institutional Investor</i></li> <li>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?</li> </ul> <p>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.</p>
<p>Foreword xvii</p> <p>Introduction xix</p> <p>Notes on Terminology xxvii</p> <p><b>Part One Measuring the Market Risks of Corporate Bonds</b></p> <p><b>Chapter 1 Measuring Spread Sensitivity of Corporate Bonds 3</b></p> <p>Analysis of Corporate Bond Spread Behavior 5</p> <p>A New Measure of Excess Return Volatility 20</p> <p>Refinements and Further Tests 25</p> <p>Summary and Implications for Portfolio Managers 30</p> <p>Appendix: Data Description 34</p> <p><b>Chapter 2 DTS for Credit Default Swaps 39</b></p> <p>Estimation Methodology 40</p> <p>Empirical Analysis of CDS Spreads 41</p> <p>Appendix: Quasi-Maximum Likelihood Approach 51</p> <p><b>Chapter 3 DTS for Sovereign Bonds 55</b></p> <p>Spread Dynamics of Emerging Markets Debt 55</p> <p>DTS for Developed Markets Sovereigns: The Case of Euro Treasuries 59</p> <p>Managing Sovereign Risk Using DTS 66</p> <p><b>Chapter 4 A Theoretical Basis for DTS 73 </b></p> <p>The Merton Model: A Zero-Coupon Bond 74</p> <p>Dependence of Slope on Maturity 77</p> <p><b>Chapter 5 Quantifying the Liquidity of Corporate Bonds 81</b></p> <p>Liquidity Cost Scores (LCS) for U.S. Credit Bonds 82</p> <p>Liquidity Cost Scores: Methodology 88</p> <p>LCS for Trader-Quoted Bonds 92</p> <p>LCS for Non-Quoted Bonds: The LCS Model 96</p> <p>Testing the LCS Model: Out-of-Sample Tests 102</p> <p>LCS for Pan-European Credit Bonds 113</p> <p>Using LCS in Portfolio Construction 123</p> <p>Trade Efficiency Scores (TES) 129</p> <p><b>Chapter 6 Joint Dynamics of Default and Liquidity Risk 133</b></p> <p>Spread Decomposition Methodology 138</p> <p>What Drives OAS Differences across Bonds? 139</p> <p>How Has the Composition of OAS Changed? 141</p> <p>Spread Decomposition Using an Alternative Measure of Expected Default Losses 145</p> <p>High-Yield Spread Decomposition 147</p> <p>Applications of Spread Decomposition 147</p> <p>Alternative Spread Decomposition Models 150</p> <p>Appendix 152</p> <p><b>Chapter 7 Empirical versus Nominal Durations of Corporate Bonds 157</b></p> <p>Empirical Duration: Theory and Evidence 159</p> <p>Segmentation in Credit Markets 173</p> <p>Potential Stale Pricing and Its Effect on Hedge Ratios 173</p> <p>Hedge Ratios Following Rating Changes: An Event Study Approach 179</p> <p>Using Empirical Duration in Portfolio Management Applications 186</p> <p><b> Part Two Managing Corporate Bond Portfolios</b></p> <p><b>Chapter 8 Hedging the Market Risk in Pairs Trades 197</b></p> <p>Data and Hedging Simulation Methodology 199</p> <p>Analysis of Hedging Results 200</p> <p>Appendix: Hedging Pair-Wise Trades with Skill 208</p> <p><b>Chapter 9 Positioning along the Credit Curve 213</b></p> <p>Data and Methodology 214</p> <p>Empirical Analysis 217</p> <p><b>Chapter 10 The 2007–2009 Credit Crisis 229</b></p> <p>Spread Behavior during the Credit Crisis 229</p> <p>Applications of DTS 234</p> <p>Advantages of DTS in Risk Model Construction 244</p> <p><b>Chapter 11 A Framework for Diversification of Issuer Risk 249</b></p> <p>Downgrade Risk before and after the Credit Crisis 250</p> <p>Using DTS to Set Position-Size Ratios 257</p> <p>Comparing and Combining the Two Approaches to Issuer Limits 260</p> <p><b>Chapter 12 How Best to Capture the Spread Premium of Corporate Bonds? 265</b></p> <p>The Credit Spread Premium 266</p> <p>Measuring the Credit Spread Premium for the IG Corporate Index 266</p> <p>Alternative Corporate Indexes 279</p> <p>Capturing Spread Premium: Adopting an Alternative Corporate Benchmark 288</p> <p><b>Chapter 13 Risk and Performance of Fallen Angels 295</b></p> <p>Data and Methodology 298</p> <p>Performance Dynamics around Rating Events 303</p> <p>Fallen Angels as an Asset Class 319</p> <p><b>Chapter 14 Obtaining Credit Exposure Using Cash and Synthetic Replication 337</b></p> <p>Cash Credit Replication (TCX) 338</p> <p>Synthetic Replication of Cash Indexes 351</p> <p>Credit RBIs 358</p> <p>References 367</p> <p>Index 371</p>
<p><b>ARIK BEN DOR,</b> <b>P<small>H</small>D,</b> is a Director and Senior Analyst in the Quantitative Portfolio Strategy (QPS) Group at Barclays Capital Research. He joined the group in 2004 after completing a PhD in finance from the Kellogg School of Management. Ben Dor has published extensively in the <i>Journal of Portfolio Management, Journal of Fixed Income,</i> and <i>Journal of Alternative Investments</i>. <p><b>LEV DYNKIN, P<small>H</small>D,</b> is the founder and Global Head of the Quantitative Portfolio Strategy Group at Barclays Capital Research. Dynkin and the QPS group joined Barclays Capital in 2008 from Lehman Brothers where the group was a part of fixed income research since 1987—one of the longest tenures for an investor-focused research group on Wall Street. <p><b>JAY HYMAN, P<small>H</small>D,</b> is a Managing Director in the Quantitative Portfolio Strategy Group at Barclays Capital Research. He joined the group in 1991 and has since worked on issues of risk budgeting, cost of investment constraints, improved measures of risk sensitivities, and optimal risk diversification for portfolios spanning all fixed income asset classes. Hyman helped develop a number of innovative measures that have been broadly adopted by portfolio managers and that have changed standard industry practice. <p><b>BRUCE D. PHELPS, P<small>H</small>D,</b> is a Managing Director in the Quantitative Portfolio Strategy Group at Barclays Capital Research, which he joined in 2000. Prior to that, he was an institutional portfolio manager and head of fixed income at Ark Asset Management. Phelps was also senior economist at the Chicago Board of Trade, where he designed derivative contracts and electronic trading systems, and an international credit officer and foreign exchange trader at Wells Fargo Bank. Phelps is a member of the editorial board of the <i>Financial Analysts Journal.</i>
<p>Created by members of the Quantitative Portfolio Strategy Group at Barclays Capital Research—a recognized authority in this field—<i>Quantitative Credit Portfolio Management</i> contains new insights that credit market practitioners, from portfolio managers to research analysts, will find useful, practical, and easy to apply. <p>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. <p>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. <p>In this book, the authors: <ul> <li>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</li> <li>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</li> <li>Demonstrate an approach to optimal diversification of issuer-specific risk in credit portfolios</li> <li>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</li> <li>Examine "fallen angels" themselves, as a separate asset class, with superior risk and return characteristics</li> </ul>

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