...Statistical Methods in Credit Risk Modeling by Aijun Zhang A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Statistics) in The University of Michigan 2009 Doctoral Committee: Professor Vijayan N. Nair, Co-Chair Agus Sudjianto, Co-Chair, Bank of America Professor Tailen Hsing Associate Professor Jionghua Jin Associate Professor Ji Zhu c Aijun Zhang 2009 All Rights Reserved To my elementary school, high school and university teachers ii ACKNOWLEDGEMENTS First of all, I would express my gratitude to my advisor Prof. Vijay Nair for guiding me during the entire PhD research. I appreciate his inspiration, encouragement and protection through these valuable years at the University of Michigan. I am thankful to Julian Faraway for his encouragement during the first years of my PhD journey. I would also like to thank Ji Zhu, Judy Jin and Tailen Hsing for serving on my doctoral committee and helpful discussions on this thesis and other research works. I am grateful to Dr. Agus Sudjianto, my co-advisor from Bank of America, for giving me the opportunity to work with him during the summers of 2006 and 2007 and for offering me a full-time position. I appreciate his guidance, active support and his many illuminating ideas. I would also like to thank Tony Nobili, Mike Bonn, Ruilong He, Shelly Ennis, Xuejun Zhou, Arun Pinto, and others I first met in 2006 at the Bank. They all persuaded me to jump into the...
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...Counterparty credit risk in portfolio risk management Prominent financial institution failures reminded market participants that over-the-counter derivatives bring counterparty credit risk. Even as these markets move towards settlement through clearing houses, significant volumes of existing and new transactions remain bilaterally settled, especially as non-standard derivatives may not qualify for central clearing. UBS Delta is providing tools for clients to measure counterparty exposure alongside other investment risk Prudent risk management of credit portfolios includes measurement and limitation of exposure to individual issuers to manage concentration risk. Investment portfolios will have limits, for example, on percentage of current value invested in securities issued by “Bank XYZ”. Where over-the-counter (OTC) derivative counterparties are also issuers of securities held, counterparty risk may be incremental to issuer exposure. If a portfolio includes a swap with Bank XYZ as the counterparty, then exposure to them failing on that swap should be considered alongside exposure to them failing on their debt issues. Counterparty credit risk measurement Counterparty exposure is properly measured not just by the current value of trades with a counterparty, but also by how this value can move as markets move. Where sets of trades with counterparties feature multiple risk drivers/asset classes, modelling the potential exposure becomes a complex problem. Many investment banks have...
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...Raiffeisen Bank International AG, Austria Credit management corporate, Director Counterparty credit risk and underwriting management in European emerging markets with special focus on Russia and Ukraine. 12/2008 – 01/2010 Structuring complex corporate credit transactions such as LBOs and investment loans. Developing an advanced internal tool for calculating Risk weighted assets under both standardised and IRB approaches. Developing and implementing industry concept in credit risk management. Reporting large and complex transactions to the bank’s Credit committee and Management board. Exercising my own approval competences for approval of credit transactions. Mentoring junior professionals and trainees in the department. Raiffeisenbank AD, Bulgaria Corporate credit risk, Head of department Managed a credit risk department of 10 risk professionals responsible for the largest corporate credit risk exposures. Was a voting member of the bank’s credit committee with own approval authorities. Steering the credit committee meetings. Participated in risk related projects originated in head office improvement, Data Quality management, Regular risk reporting). Met National Supervisory in terms of IRB application status of the bank. (Rating model 06/2008 – 11/2008 EFG Eurobank AD, Bulgaria Credit risk management, Head of department Managed a department of 9 risk managers, Responsible for corporate and retail credit risk 08/2005 – 05/2008 Raiffeisenbank...
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...Credit Risk Management Ken Brown Peter Moles CR-A2-engb 1/2012 (1044) This course text is part of the learning content for this Edinburgh Business School course. In addition to this printed course text, you should also have access to the course website in this subject, which will provide you with more learning content, the Profiler software and past examination questions and answers. The content of this course text is updated from time to time, and all changes are reflected in the version of the text that appears on the accompanying website at http://coursewebsites.ebsglobal.net/. Most updates are minor, and examination questions will avoid any new or significantly altered material for two years following publication of the relevant material on the website. You can check the version of the course text via the version release number to be found on the front page of the text, and compare this to the version number of the latest PDF version of the text on the website. If you are studying this course as part of a tutored programme, you should contact your Centre for further information on any changes. Full terms and conditions that apply to students on any of the Edinburgh Business School courses are available on the website www.ebsglobal.net, and should have been notified to you either by Edinburgh Business School or by the centre or regional partner through whom you purchased your course. If this is not the case, please contact Edinburgh Business School at the address below:...
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...Credit risk Credit risk is a fast changing discipline at the leading edge of risk management practice. The recent credit crisis brought into focus the need for effective risk management control and highlighted many of the deficiencies of the banks’ approach to measuring credit risk. This has resulted in many financial institutions reviewing their existing approach to the management of credit risk from a process, organisational and systems perspective. At the same time, many institutions are also continuing to develop more sophisticated methods of risk management, such as measuring and hedging Credit Valuation Adjustments (CVA) and modelling economic capital and incremental risk Definitions of Credit risk: ❖ Credit risk is the risk of loss due to a debtor's non-payment of a loan or other line of credit (either the principal or interest (coupon) or both). ❖ Is the risk that another party to an investment transaction will not fulfill its obligations. Credit risk can be associated with the issuer of ❖ The likelihood that an individual will pay his or her credit obligations as agreed. Borrowers who are more likely to pay as agreed pose less risk to creditors and lenders. ❖ Risk of loss that may arise on outstanding contracts should a counter party default on its obligations. ❖ The risk that a counter party to a transaction will fail to perform according to the terms and conditions of the contract, thus causing the holder of the claim to suffer a loss. ...
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...Basel Committee on Banking Supervision International Convergence of Capital Measurement and Capital Standards A Revised Framework Comprehensive Version This document is a compilation of the June 2004 Basel II Framework, the elements of the 1988 Accord that were not revised during the Basel II process, the 1996 Amendment to the Capital Accord to Incorporate Market Risks, and the 2005 paper on the Application of Basel II to Trading Activities and the Treatment of Double Default Effects. No new elements have been introduced in this compilation. June 2006 Requests for copies of publications, or for additions/changes to the mailing list, should be sent to: Bank for International Settlements Press & Communications CH-4002 Basel, Switzerland E-mail: publications@bis.org Fax: +41 61 280 9100 and +41 61 280 8100 © Bank for International Settlements 2006. All rights reserved. Brief excerpts may be reproduced or translated provided the source is stated. ISBN print: 92-9131-720-9 ISBN web: 92-9197-720-9 Contents Introduction ...............................................................................................................................1 Structure of this document........................................................................................................6 Part 1: Scope of Application .....................................................................................................7 I. Introduction.....................
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...kredito rizikos vertinimo įmonėje credit domain (SMEs and larger businesses), that can guide lenders when choosing kredito domenas (MVĮ ir didesnėmis įmonėmis), kurios gali padėti skolintojams renkantis appropriate data and tools. atitinkami duomenys ir įrankiai. Traditionally, lenders relied upon judgmental assessments of Tradiciškai, skolintojai, remtis subjektyvių nuomonių vertinimais the five Cs (capacity, capital, character, collateral, and conditions), but modern 5 Ca (galia, kapitalas, charakteris, įkaitas, ir sąlygos), bet modernus technology has allowed them to amass and capitalise on data. technologija leido jiems kaupti ir pasinaudoti duomenų. Besides judgment, lenders Be nuovoką, skolintojų can also apply scoring, reduced-form, and structural models—with the choice being taip pat gali taikyti įvertinimas balais, sumažinta forma, ir struktūrinio modelių pasirinkimas yra dependent upon the size and nature of the firms being assessed. priklauso nuo vertinamos įmonių dydį ir pobūdį. For the largest Didžiausias companies with traded securities, reduced-form and structural models can be used to bendrovėms, turinčioms vertybinių popierių apyvartą, sumažinti forma ir struktūrinių modelių gali būti naudojamas interpret their prices and price movements. interpretuoti savo kainas ir kainų svyravimus. In contrast, credit scoring is used mostly in Tuo tarpu kredito vertinimo, naudojamas daugiausia data-rich small-business credit environments, but can add value elsewhere...
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...University of Florence Faculty of Economy Master’s Degree in Bank, Insurance and Financial Markets Thesis in Applied Statistics for Banks and Insurances Credit Risk Models: Single Firm Default and Contagion Default Analysis Supervisor: P rof essor Fabrizio Cipollini Student: Marco Gambacciani Academic Year 2009/2010 Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Structural Models 1.1 Terminal Default . . . . . . . . . . . . 1.2 First Passage Models . . . . . . . . . . 1.2.1 The Black and Cox’s Model . . 1.2.2 Longstaff and Schwartz’s Model 1.2.3 Leland and Toft’s Model . . . . 1.2.4 Zhou’s Model . . . . . . . . . . 1.2.5 Random Threshold Model . . . 2 5 5 11 11 15 19 24 30 35 36 39 41 45 48 50 51 56 67 76 77 79 79 82 83 84 94 114 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Modelli reduced form 2.1 Approach With An Homogenous Poisson Process . . 2.2 Approach With a Non-Homogenous Poisson Process 2.3 Approach with a Cox’s Process . . . . . . . . . . . . 2.4 Bond and Spread Valuation . . . . . . . . . . . . . . Models For The Correlation Between Defaults 3.1 Bottom-Up Models . . . . . . . . . . . . . 3.1.1 Structural Apporach . . . . . . . . 3.1.2 Intensity Models Approaches . . . 3.1.3 Approaches with...
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...2016 FRM Exam Study Guide ® The designation recognized by risk management professionals worldwide 2016 Financial Risk Manager (FRM®) Exam Study Guide TOPIC OUTLINE, READINGS, able to deal with them effectively. As TEST WEIGHTINGS such, the Exams are comprehensive in The Study Guide sets forth primary nature, testing a candidate on a number topics and subtopics covered in the FRM of risk management concepts and Exam Part I and Part II. The topics were approaches. selected by the FRM Committee as ones that risk managers who work in practice today have to master. The topics and READINGS Questions for the FRM Exams are related their respective weightings are reviewed to and supported by the readings listed yearly to ensure the Exams are timely under each topic outline. These readings and relevant. The study Guide also were selected by the FRM Committee contains a full listing of all the readings to assist candidates in their review of that are recommended as preparation the subjects covered by the Exams. It is for the FRM Exam Part I and Part II. strongly suggested that candidates review Key concepts (knowledge points) these readings in depth prior to sitting for appear as bullet points at the beginning each exam. All of the readings listed in the of each section and are intended to help FRM Study guide are available through candidates identify the major themes GARP. Further...
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...Marsh The effect of lenders' credit risk transfer activities on borrowing firms' equity returns Bank of Finland Research Discussion Papers 31 • 2006 Suomen Pankki Bank of Finland P.O.Box 160 FI-00101 HELSINKI Finland + 358 10 8311 http://www.bof.fi Bank of Finland Research Discussion Papers 31 • 2006 Ian W Marsh* The effect of lenders’ credit risk transfer activities on borrowing firms’ equity returns The views expressed are those of the author and do not necessarily reflect the views of the Bank of Finland. * Cass Business School, London, and Bank of Finland. E-mail: i.marsh@city.ac.uk. This paper was written while the author was visiting the Research Unit of the Bank of Finland. The Bank’s hospitality was exemplary and I am grateful to participants at the Research Unit’s Summer Workshop, the Bank of Finland Economics Seminar, Iftekhar Hasan, Tuomas Takalo, and Wolf Wagner for comments. Susan Yuska at the Chicago Fed was very helpful in guiding me through the Bank Holding Company Database. http://www.bof.fi ISBN 978-952-462-340-7 ISSN 0785-3572 (print) ISBN 978-952-462-341-4 ISSN 1456-6184 (online) Helsinki 2006 The effect of lenders’ credit risk transfer activities on borrowing firms’ equity returns Bank of Finland Research Discussion Papers 31/2006 Ian W Marsh Monetary Policy and Research Department Abstract Although innovative credit risk transfer techniques help to allocate risk more optimally, policymakers...
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...University of Nottingham Credit Risk Management in Major British Banks By Xiuzhu Zhao 2007 A Dissertation presented in part consideration for the degree of “MA Finance and Investment” Acknowledgement I would like to express my special thanks to my supervisor Mrs. Margaret Woods, who has given me strong support and encouragement during the whole research, and I am very appreciate of the expert guidance and inspiration she brought me. I am very grateful to my parents for their love and encouragement during my whole education period. The academic suggestions my father has given help me a lot in designing the dissertation. Last but not least, I would like to thank all my friends especially those in Melton Hall. I will never forget the help they have offered, which raises my confidence in completing this dissertation. i Abstract Credit risk is always treated as the major risk inherent in a bank’s banking and trading activities. And if not well managed, this kind of risk may drag a bank into great trouble or even bankruptcy, which can be proved by various bank failure cases. For banks, managing credit risk is not a simple task since comprehensive considerations and practices are needed for identifying, measuring, controlling and minimizing credit risk. In this dissertation, the credit risk management practices of major British banks are examined through the quantitative research on all Major British Banking Group members and qualitative analysis on the four sample banks....
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...Kong Or by e-mail to: Basel2@hkma.gov.hk by end-March 2005 Table of Contents 1. Weighting framework for credit risk (Standardised Approach) 2. Credit risk mitigation under the Standardised Approach 41 3. Weighting framework for credit risk (IRB Approach) 75 4. Criteria for transition to IRB Approach 137 5. Weighting framework for operational risk 161 1 3 (This page is intentionally left blank.) 2 WEIGHTING FRAMEWORK FOR CREDIT RISK (STANDARDISED APPROACH) Hong Kong Monetary Authority February 2005 3 Weighting Framework for Credit Risk (Standardised Approach) Contents 1. Introduction 1.1 1.2 2. Terminology Scope and application Measurement methodology 2.1 2.2 Credit risk mitigation 2.3 3. Standard portfolios for risk-weighting Calculation of risk-weighted amount Risk weights based on external credit assessment 3.1 Introduction 3.2 The risk weights for individual claims (a) Claims on sovereigns (b) Claims on public sector entities (c) Claims on multilateral development banks (d) Claims on banks (e) Claims on securities firms (f) Claims on corporates 3.3 3.4 4. Short-term claims Application of external credit assessment Risk weights based on standard characteristics of exposures 4.1 The risk weights for individual claims (g) (h) Regulatory retail exposures (i) Residential mortgage loans (j) Past...
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..................................................................................................................................1 A. Strengthening the global capital framework ....................................................................2 1. 2. 3. 4. Raising the quality, consistency and transparency of the capital base ..................2 Enhancing risk coverage........................................................................................3 Supplementing the risk-based capital requirement with a leverage ratio ...............4 Reducing procyclicality and promoting countercyclical buffers ..............................5 Cyclicality of the minimum requirement .................................................................5 Forward looking provisioning .................................................................................6 Capital conservation...............................................................................................6 Excess credit growth ..............................................................................................7 5. B. 1. 2. 3. C. D. I. Addressing systemic risk and interconnectedness...
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...≈√ Guidelines on Credit Risk Management Rating Models a n d Va l i d a t i o n These guidelines were prepared by the Oesterreichische Nationalbank (OeNB) in cooperation with the Financial Market Authority (FMA) Published by: Oesterreichische Nationalbank (OeNB) Otto Wagner Platz 3, 1090 Vienna, Austria Austrian Financial Market Authority (FMA) Praterstrasse 23, 1020 Vienna, Austria Produced by: Oesterreichische Nationalbank Editor in chief: Gunther Thonabauer, Secretariat of the Governing Board and Public Relations (OeNB) ‹ Barbara Nosslinger, Staff Department for Executive Board Affairs and Public Relations (FMA) ‹ Editorial processing: Doris Datschetzky, Yi-Der Kuo, Alexander Tscherteu, (all OeNB) Thomas Hudetz, Ursula Hauser-Rethaller (all FMA) Design: Peter Buchegger, Secretariat of the Governing Board and Public Relations (OeNB) Typesetting, printing, and production: OeNB Printing Office Published and produced at: Otto Wagner Platz 3, 1090 Vienna, Austria Inquiries: Oesterreichische Nationalbank Secretariat of the Governing Board and Public Relations Otto Wagner Platz 3, 1090 Vienna, Austria Postal address: PO Box 61, 1011 Vienna, Austria Phone: (+43-1) 40 420-6666 Fax: (+43-1) 404 20-6696 Orders: Oesterreichische Nationalbank Documentation Management and Communication Systems Otto Wagner Platz 3, 1090 Vienna, Austria Postal address: PO Box 61, 1011 Vienna, Austria Phone: (+43-1) 404 20-2345 Fax: (+43-1) 404 20-2398 Internet: ...
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...1 MINING INDUSTRY - OVERVIEW AND RISKS FACTORS Definition of the Industry The mining industry encompasses a wide range of companies involved in different supply chain positions that represent exploration, development, extraction, processing, refining and sale of minerals and coal. With respect to the diverse set of business factors that affect the mining process, the business risk rating for the mining industry would be best qualified in terms of a credit rating of BBB (low). The justification for this rating follows: a) Higher than average profitability of the industry – related to the need to provide adequate returns on large capital investments b) Threat of competitors is about on the same level as other industries – based on multiple suppliers and buyers and the prevalence of homogenous products (nonbranded) c) Inherent volatility in earnings and underlying cash flows – due to volatile pricing of commodity products and responsiveness to economic cycles d) Above average and increasing prospect of industry regulation e) Above average and uncertain political risk – industry players have to pursue operations where mineral resources are found and in many cases this would include politically unstable regions f) Below average technology risks – due to the basic nature of the materials produced and licensing production technologies and methods among players in the industry 2 The BBB rating is applicable only to industry players...
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