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• Author: Keith A. Allman
• Publisher: Wiley
• Publish Date: Pap/Cdr edition (December 10, 2
• ISBN: 0470242051
• Pages: 202

Product Description

A serious source of information for those looking to reverse engineer business deals It’s clear from the current turbulence on Wall Street that the inner workings of its most complex transactions are poorly understood. Wall Street deals parse risk using intricate legal terminology that is difficult to translate into an analytical model. Reverse Engineering Deals on Wall Street: A Step-By-Step Guide takes readers through a detailed methodology of deconstructing the public deal documentation of a modern Wall Street transaction and applying the deconstructed elements to create a fully dynamic model that can be used for risk and investment analysis. Appropriate for the current market climate, an actual residential mortgage backed security (RMBS) transaction is taken from prospectus to model by the end of the book. Step by step, Allman walks the reader through the reversing process with textual excerpts from the prospectus and discussions on how it directly transfers to a model. Each chapter begins with a discussion of concepts with exact references to an example prospectus, followed by a section called "Model Builder," in which Allman translates the theory into a fully functioning model for the example deal. Also included is valuable VBA code and detailed explanation that shows proper valuation methods including loan level amortization and full trigger modeling. Aside from investment analysis this text can help anyone who wants to keep track of the competition, learn from others public transactions, or set up a system to audit one’s own models. Keith A. Allman (New York, NY) is a structured finance professional with a specialization in analytics and modeling, and the author of Modeling Structured Finance Cash Flows with Microsoft Excel (978-0-470-04290-8), from Wiley.

From the Back Cover Economics / Investments & Securities Praise for Reverse Engineering Deals on Wall Street with Microsoft Excel "Allman has written an excellent sequel to his first book Modeling Structured Finance Cash Flows with Microsoft Excel, providing a simple guide on how to deconstruct cash flows through modeling and understanding the collateral by analyzing the prospectus. Whether you are new to the structured finance industry or steeped in structured financing—this book is a must-read."

—Ralph Armenta, PMI Mortgage Insurance/Structured Transactions "The credit crisis has shown that more financial institutions and analysts need to be able to reverse-engineer structured finance deals to assess their values and risks for themselves. Keith Allman has produced a thorough guide for creating reverse-engineered models that both beginners and experienced analysts will find invaluable."

—Chandan Sengupta, author of Financial Modeling Using Excel and VBA A serious source of information for those looking to reverse-engineer business deals How does Wall Street keep track of the competition? They reverse-engineer deals by taking a prospectus or term sheet and recreating a model from it. The skills involved in this task are sophisticated, but are important to understand—especially in today's dynamic business environment. In this practical resource, financial professional Keith Allman demystifies the process by interpreting complicated legal terminology and clearly showing how it can be organized into a dynamic model. Step by step, Allman walks you through this endeavor with textual excerpts from the prospectus and details how it directly transfers to a model. Each chapter begins with a discussion of concepts with exact references to an example prospectus, followed by a section called "Model Builder," in which Allman translates the theory into a fully functioning model for the example deal. In addition, the companion CD-ROM features all of the modeling exercises, as well as a final version of the model that is outlined in the text.

• Paperback: 202 pages
• Publisher: Wiley; Pap/Cdr edition (December 10, 2008)
• Language: English
• ISBN-10: 0470242051
• ISBN-13: 978-0470242056

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