Credit portfolio management a practitioners guide to the active management of credit risks (global financial markets) (repost

www.ebook3000.com Credit Portfolio Management www.ebook3000.com Also available Gianluca Oricchio Private Company Valuation Michael Wong and Wilson Chan Investing in Asian Offshore Currency Markets Jamie Rogers Strategy, Value and Risk Guy Fraser-Sampson Intelligent Investing Ross McGill US Withholding Tax www.ebook3000.com Credit Portfolio Management A Practitioner’s Guide to the Active Management of Credit Risks Michael Hünseler Managing Director, Assenagon Asset Management S.A www.ebook3000.com © Michael Hünseler 2013 Foreword © Som-lok Leung 2013 Softcover reprint of the hardcover 1st edition 2013 978-0-230-39149-9 All rights reserved No reproduction, copy or transmission of this publication may be made without written permission No portion of this publication may be reproduced, copied or transmitted save with written permission or in accordance with the provisions of the Copyright, Designs and Patents Act 1988, or under the terms of any licence permitting limited copying issued by the Copyright Licensing Agency, Saffron House, 6–10 Kirby Street, London EC1N 8TS Any person who does any unauthorized act in relation to this publication may be liable to criminal prosecution and civil claims for damages The author has asserted his rights to be identified as the author of this work in accordance with the Copyright, Designs and Patents Act 1988 First published 2013 by PALGRAVE MACMILLAN Palgrave Macmillan in the UK is an imprint of Macmillan Publishers Limited, registered in England, company number 785998, of Houndmills, Basingstoke, Hampshire RG21 6XS Palgrave Macmillan in the US is a division of St Martin’s Press LLC, 175 Fifth Avenue, New York, NY 10010 Palgrave Macmillan is the global academic imprint of the above companies and has companies and representatives throughout the world Palgrave® and Macmillan® are registered trademarks in the United States, the United Kingdom, Europe and other countries ISBN 978-1-349-35162-6 DOI 10.1057/9780230391505 ISBN 978-0-230-39150-5 (eBook) This book is printed on paper suitable for recycling and made from fully managed and sustained forest sources Logging, pulping and manufacturing processes are expected to conform to the environmental regulations of the country of origin A catalogue record for this book is available from the British Library A catalog record for this book is available from the Library of Congress 10 22 21 20 19 18 17 16 15 14 13 www.ebook3000.com To my family, Susi and Emmi, who are an inspiration beyond and above any words to me With their patience, encouragement and trust, nothing seems impossible www.ebook3000.com This page intentionally left blank www.ebook3000.com Contents List of Tables xii List of Figures xiii Foreword by Som-lok Leung xvi Preface xix Acknowledgements xxii List of Abbreviations xxiii Part I Charting the Course – Credit Risk Strategies The Case for Credit Portfolio Management 1.1 Evolution and innovation: ups and downs of credit 1.2 The age of credit crises 1.3 Credit risk management at the forefront Credit Risk Strategies 2.1 The risk appetite framework 2.2 Risk culture 2.3 Credit risk strategies 2.3.1 Key requirements for an effective credit risk strategy 2.3.2 Credit risk strategy measures 2.4 Risk limits: framing the credit risk strategy 2.4.1 Forms of credit concentrations and regulatory view 2.4.2 Measurement of concentration risk 2.4.3 Concentration risk limits 2.4.3.1 Definition of risk limits 2.4.3.1.1 Risk limit object 2.4.3.1.2 Risk limit measures 2.4.3.2 Determination of risk limits 2.4.3.2.1 Quantitative risk limits 2.4.3.2.2 Qualitative risk limits: underwriting standards 2.4.3.2.3 Consistency check 2.4.3.3 Limit monitoring 2.4.3.4 Management of limit breaches 2.4.4 Syndication risk limits vii www.ebook3000.com 13 18 18 21 25 26 26 28 32 34 36 37 37 37 38 39 40 41 41 41 43 viii Contents What If: Credit Risk Stress Testing 3.1 Definition and objective of stress tests 3.2 Stressed scenarios 3.2.1 Hypothetical or macroeconomic scenarios 3.2.2 Historical or shock scenarios 3.2.3 Worst-case scenarios 3.2.4 Stress scenario requirements 3.3 Types of stress tests 3.3.1 Sensitivity analysis 3.3.2 Scenario analysis 3.3.3 What-if analysis 3.3.4 Concentration risk analysis 3.3.4.1 Single name concentration risk stress test 3.3.4.2 Sector concentration risk stress test 3.3.5 Reverse stress testing 3.4 Stress test information and subsequent mitigation 3.5 Conclusion 45 47 51 51 52 53 53 54 55 55 56 57 57 58 58 59 60 Part II Credit Portfolio Management in Practice 63 65 Evolution of Portfolio Management Business Models 4.1 From credit advisory to active credit portfolio management 4.2 A full cycle approach to credit portfolio management 4.3 Bridging distinct worlds: loans, bonds and credit derivatives 4.3.1 Asymmetric information in bank loans 4.3.2 Convergence of bank loans and debt capital markets instruments 4.4 The role of loan transfer pricing 4.4.1 Risk-adjusted loan pricing 4.4.2 Loan transfer pricing 4.4.3 Loan transfer pricing based on observable loan market prices 4.4.4 Loan transfer pricing based on observable credit spreads 4.4.5 Transfer pricing based on generic curves 4.4.6 Risk adjusted versus transfer pricing 4.5 Practical implementation: organizational and infrastructure challenges 4.5.1 Governance and mandate 4.5.2 Organizational design 4.5.3 Performance measurement and communication www.ebook3000.com 67 72 77 78 80 83 84 85 87 89 92 96 98 99 102 105 Contents ix 4.5.4 Portfolio analytics and IT infrastructure 4.5.5 Implementation of an ACPM function Accounting Complexity and Implications 5.1 Hedge accounting and other solutions for accounting asymmetry 5.1.1 Hedge Accounting for Credit Risk 5.1.1.1 Types of hedge accounting and requirements 5.1.1.2 Assessing fair value changes and measuring hedge effectiveness 5.1.1.3 Hedge accounting eligible assets and strategy 5.1.1.4 Conclusion 5.1.2 Fair valuing loans 5.1.2.1 FVO eligible assets and pricing 5.1.2.2 Regulatory requirements for application of FVO 5.1.2.3 Conclusion 5.1.3 Financial Guarantee 5.1.3.1 Accounting rules for Financial Guarantees 5.1.3.2 Conclusion 5.1.4 Combination of hedge and reinvestment portfolio 5.1.4.1 DV01 neutral hedge and reinvestment strategy 5.1.4.2 Beta neutral hedge and reinvestment strategy 5.1.4.3 Notional neutral hedge and reinvestment strategy 5.1.4.4 Cost (cash flow) neutral hedge and reinvestment strategy 5.1.4.5 Conclusion Regulatory Capital Management under Basel II 6.1 Capital optimization – key considerations 6.2 Regulatory capital relief through CDS and guarantees 6.2.1 Determination of capital relief amount 6.2.2 Adjustments in capital reduction for CRM 6.3 Conclusion Part III Hedging Techniques and Toolkits CDS: Hedging of Issuer and Counterparty Risks 7.1 Mechanism and conventions of CDS 7.1.1 Transaction terms and conditions www.ebook3000.com 106 107 109 114 116 117 119 120 123 124 125 127 127 128 129 130 131 137 139 140 142 144 145 146 148 151 154 157 159 165 168 169 Hedge Strategies for Baskets, Swaptions 237 90 300 80 250 60 200 50 150 40 Indexpoints Spread (bps) 70 30 100 20 50 10 North American CDX index (lhs) 12 04 /0 /2 11 04 /0 /2 10 04 /0 /2 09 /2 04 /0 /2 /0 04 /2 /0 04 08 07 VIX index (rhs) Figure 9.4 VIX Index versus CDX Investmentgrade CDS Index (North America) as of December 2012 Data source: Bloomberg contribution of volatility to the value of an option, option prices reveal an implied volatility which, for most of the time, differs from realized volatility of the underlying The difference reflects supply and demand imbalances as well as expectations regarding volatility trends for which option traders may be prepared to pay a premium For swaptions, there is an overlapping effect since the spreads of CDS indices that serve as the underlying for those options exhibit a notable sensitivity to changes in stock prices and to the amplitude of those changes A measure mostly used for observation of U.S stock volatility is the VIX or CBOE Volatility index that reflects the market estimate of future volatility, based on the weighted average of the implied volatilities for a wide range of option strikes 9.2.3.1 Development of a hedge strategy using swaptions Developing a hedge strategy using CDS options follows five steps: Describing the scenario for which an investor seeks protection, including the probability of the event(s) to materialize; Translating the scenario into a potential impact in relevant measures such as profit and loss; 238 Credit Portfolio Management Determining the hedge strategy which is most suitable in counterbalancing the scenario because of a payoff profile that most closely neutralizes the loss distribution Defining the hedge budget in terms of hedge costs and a maximum loss acceptable resulting from the hedge Subsequent timely monitoring g of the hedge strategy, in particular regarding the effectiveness or the hedge error which arises from residual unprotected risk (basis risk) When describing a view of potential trends or events in credit markets, the historical distribution of spread changes serves as a reference for the scenario Isolating a period of market dislocations helps to identify realistic frequency distributions as a basis for determining potential stress outcomes For example, the frequency distribution of daily spread changes for the European investment-grade CDS index iTraxx is divided into two periods: prior to the Lehman failure4 where spreads mostly moved between +5 bps and –5 bps a day and post Lehman default with significantly more pronounced volatility Developing a hedge strategy using swaptions requires a scenario-derived impact on the distribution of spread changes and spread trends For instance, widening spreads combined with a rise in volatility can be formulated in terms of impact on profit and loss on the credit portfolio to be hedged Based on that loss profile, it is possible to identify the option strategy that responds to the scenario in a way which matches as closely 20 >20 > 18 15 Frequency Distribution of daily iTraxx T spread changes post Lehman defalut (Sep 15th 2008–2012) Daily spread change (bps) 14 10 10 20 004 –5 Frequency Distribution of daily iTraxx T spread changes pre Lehman defalut (2004–Sep 15th 2008) 2005 2006 2007 2008 –10 2009 2010 2011 –2 –6 –10 – –14 – –15 –20 –18 –