risk excel

To enhance your understanding of the risk management, pricing and regulation of counterparty credit risk, this new title offers the most detailed and comprehensive coverage available. Michael Pykhtin, a globally respected expert in credit risk, has combed the industry’s most important organisations to assemble a winning team of specialist contributors – presenting you with an insider’s view of all the main elements of counterparty credit risk and how it will develop in the future. This new book brings you up-to-date with the very latest developments and innovations in modelling counterparty risk. Offers a detailed and topical analysis of the Basel Committee’s new regulatory capital rules for counterparty credit risk and the underlying models – and explains the changes Basel II will bring. You will learn from authors representing the cream of academia as well as the world’s leading financial and regulatory bodies – many of whom actively participated in the consultations between the industry and regulatory agencies on the new Basel II rules. Topics covered include: modelling collateral agreements, the development of conditional pricing methodology, modelling exposures for credit-sensitive instruments, the development of analytical methods for portfolio credit risk, emergence of expected positive exposure as the foundation for loan equivalent exposure, and the pricing of counterparty risk for credit-sensitive instruments. Additionally, the book reviews already established modelling concepts and methods. A comprehensive reference of lasting value – an essential learning tool for anyone involved with counterparty credit risk.

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Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level is a practical, comprehensive and in-depth guide to financial modelling designed to cover the modelling issues that are relevant to facilitate the construction of robust and readily understandable models.

Based on the authors extensive experience of building models in business and finance, and of training others how to do so this book starts with a review of Excel functions that are generally most relevant for building intermediate and advanced level models (such as Lookup functions, database and statistical functions and so on).  It then discusses the principles involved in designing, structuring and building relevant, accurate and readily understandable models (including the use of sensitivity analysis techniques) before covering key application areas, such as the modelling of financial statements, of cash flow valuation, risk analysis, options and real options. Finally, the topic of financial modelling using VBA is treated. Practical examples are used throughout and model examples are included in the attached CD-ROM.

Aimed at intermediate and advanced level modellers in Excel who wish to extend and consolidate their knowledge, this book is focused, practical, and application-driven, facilitating knowledge to build or audit a much wider range of financial models.

Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

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This book is designed to start with simple examples that progressively develop the reader’s confidence to take on more complex tasks. There is very little theoretical discussion about computer science, operations research algorithms, mathematics, or finance. The thrust of the book is to teach the reader to break complex tasks down into simple tasks. It then looks to implement those simple tasks into VBA code using a critical subset of the features of the language.

The tentative contents is: (1) Why? What? Who? Where? and How? (2) Common Sense (3) Securitizing A Loan Portfolio (4) Understanding the Excel Waterfall (5) Designing the VBA Model (6) Laying the Model Groundwork (7) Recorded Macros: A First Look at the VBA Language (8) Writing Menus: An Introduction to Data, Ranges, Arrays, and Objects (9) Controlling the Flow of the Model (10) Building Messaging Capabilities (11) Designing the Model’s Reports (12) Main Program and Menus (13) Writing the Collateral Selection Code (14) Calculating the Cash Flows (15) Running the Waterfall: Producing Initial Results (16) Debugging the Model (17) Validating the Model (18) Running the Model (19) Building Additional Capabilities (20) Documentation of the Model (21) Managing the Growth of the Model (22) Building Portfolio Monitoring Model (23) Valuation Techniques: How do we Determine Price? (24) Challenging Times For the Deal (25) Parting Admonitions

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Prebuilt Code for Modeling and Pricing Today’s Complex Derivatives

 

Justin London shows how to implement pricing algorithms for a wide variety of complex derivatives, including rapidly emerging instruments covered in no other book. Utilizing actual Bloomberg data, London covers credit derivatives, CDOs, mortgage-backed securities, asset-backed securities, fixed-income securities, and today’s increasingly important weather, power, and energy derivatives. His robust models are designed for both ease of use and ease of adaptation, and may be downloaded by the book’s purchasers from a secured Web site.

 

Modeling Derivatives Applications in Matlab, C++, and Excel will be indispensable to sell-side professionals who model derivatives; buy-side professionals who must understand the derivatives offered to them; experienced quants; developers at Wall Street firms; and any financial engineering practitioner or student entering the derivatives field for the first time.

• Presents broader coverage and more models than any competitive book Covers everything from swaps to interest rate models, mortgage- and asset-backed securities to the HJM model
• Includes code for all three leading derivatives development platforms The only book to present models for Matlab, C++, and Excel
• Addresses the fastest-growing areas of derivatives development Includes models for weather, power, and energy derivatives, CDOs, and more
• Contains extensive real-world examples.

The entire book utilizes Matlab, C++, and Excel.  Users need Matlab installed, Visual C++, and Excel.  In addition, some examples using Matlab toolkits are used: Chapter 1 makes use of the Fixed-Income Toolkit.  Appendix A makes use of the Financial Derivatives Toolkit and Matlab Excel Link.  These toolkits do not come with the book, but can be obtained from Mathworks.

 

Downloadable models available ONLY to purchasers of this book.

Purchasers receive a unique access code enabling secure access to downloadable, prebuilt code and templates for Matlab, C++, and Excel.

 

                       Preface  xv

                        Acknowledgments  xix

                        About the Author  xxi

Chapter 1       Swaps and Fixed Income Instruments  1 

Chapter 2       Copula Functions  67 

Chapter 3       Mortgage-Backed Securities  91 

Chapter 4       Collateralized Debt Obligations  163

Chapter 5       Credit Derivatives  223

Chapter 6       Weather Derivatives  299

Chapter 7       Energy and Power Derivatives  333

Chapter 8       Pricing Power Derivatives: Theory and Matlab Implementation  407 

Chapter 9       Commercial Real Estate Asset-Backed Securities  447

Appendix A     Interest Rate Tree Modeling in Matlab  473

Appendix B     Chapter 7 Code  503

                        References  543 

                        Index   555 

 

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Value-at-Risk has emerged as the standard tool for measuring and reporting financial market risk. Currently, more than eighty commercial vendors offer enterprise or trading risk management systems that provide VAR-like measures. Risk managers are therefore often left with the daunting task of having to choose from this plethora of risk measures.
While basic VAR textbooks describe average VAR situations, the vast majority of these situations are abnormal. Elements of Financial Risk Management focuses on implementation, especially recent techniques which facilitate “bridging the gap” between standard textbooks on risk and real-life risk management systems. This book will appeal to practitioners in the financial services and investment industries, as well as graduate students and advanced undergraduates who want exposure to these techniques.

*Pinpoints key features of risk asset returns and captures them in tractable statistical models in the companion website *Presents step-by-step approaches as a means to solve problems *Visible patterns in the data motivate the choices of tools, and when tools fall short, it presents the next tool

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In this book, two of America’s leading economists provide the first integrated treatment of the conceptual, practical, and empirical foundations for credit risk pricing and risk measurement. Masterfully applying theory to practice, Darrell Duffie and Kenneth Singleton model credit risk for the purpose of measuring portfolio risk and pricing defaultable bonds, credit derivatives, and other securities exposed to credit risk. The methodological rigor, scope, and sophistication of their state-of-the-art account is unparalleled, and its singularly in-depth treatment of pricing and credit derivatives further illuminates a problem that has drawn much attention in an era when financial institutions the world over are revising their credit management strategies.

Duffie and Singleton offer critical assessments of alternative approaches to credit-risk modeling, while highlighting the strengths and weaknesses of current practice. Their approach blends in-depth discussions of the conceptual foundations of modeling with extensive analyses of the empirical properties of such credit-related time series as default probabilities, recoveries, ratings transitions, and yield spreads. Both the “structura” and “reduced-form” approaches to pricing defaultable securities are presented, and their comparative fits to historical data are assessed. The authors also provide a comprehensive treatment of the pricing of credit derivatives, including credit swaps, collateralized debt obligations, credit guarantees, lines of credit, and spread options. Not least, they describe certain enhancements to current pricing and management practices that, they argue, will better position financial institutions for future changes in the financial markets.

Credit Risk is an indispensable resource for risk managers, traders or regulators dealing with financial products with a significant credit risk component, as well as for academic researchers and students.

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Many financial institutions around the world must prove minimum compliance to the Basel II Accord by 2015. For several banks, implementing internal risk rating systems (IRRS) is simply Basel II compliance. However, when carried out with a proper focus on bottom-line growth, this regulation has been shown to enhance a bank’s risk-management practices and competitiveness in the market. Basel II Implementation is an invaluable guide that puts a potent combination of theory and real-world practice at your fingertips.

Written by two of the most globally recognized and sought-after thought leaders in Basel II implementation, this how-to book maps out, step-by-step, implementable solutions that are both academically credible and practical, making them defendable to regulators and executable within the constraints of data, resources, and time. Organized to sequentially follow IRRS development under Basel II, each section of this go-to guide provides:

• An introduction to the Basel II concept
• A variety of techniques for reaching compliance, based on research conducted by the authors and supported by Standard & Poor’s
• Corporate case examples that illustrate implementation in the real world

To complement the holistic approach in Basel II Implementation, which offers end-to-end analysis of various credit risk problems, an accompanying CD-ROM features a wealth of useful spreadsheet templates that will facilitate the efficient and accurate execution of covered techniques.

Stay ahead of the curve with the expert strategies and advice found in Basel II Implementation.

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This work provides a practical, accessible step-by-step analysis of the theory and practicalities of credit risk measurement and management. Topics covered include: default probabilities; expected and unexpected losses; time effects; default correlations; and loss distributions.

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