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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.
"An excellent book which presents advanced financial modelling tools and simulations, and applies them to modern aspects of financial management. As a renowned expert in modelling, Michael Rees develops efficient techniques for simulation and sensitivity analysis within an Excel and Excel add-on framework using many useful and transparent applications in the context of company valuation, derivative business and risk management, enabling the reader to develop good models themselves. A unique book which is highly instructive and motivating."
—Professor Dr Dieter Gramlich, University of Cooperative Education, Heidenheim, Germany
"Mike Rees's book fills an important gap in the literature on how to model financial data. It not only provides a whole host of useful suggestions on how to design, structure, build and analyse models; including tips on how use some of the more advanced functionality in Excel, but also in a clear and concise way explains how to include uncertainty in to these models. During the last few years many business's environment have changed, creating the need to explicitly include uncertainty into their decision making rather than hide behind simple (and often flawed) assumptions of what the future may hold. Mike clearly understands the importance of this area and includes several sections which provide an excellent introduction to anyone starting to apply these types of techniques in their financial models for the first time. It is the combination of best practice modelling techniques, plenty of examples and the basics of some of the more advanced approaches that make this book a useful addition to anyone building financial models."
—Andrea Dickens, Decision Analysis Group Leader, Finance Excellence Unilever
Background, Objectives and Approach.
About the Author.
1 Building Blocks: Selected Excel Functions and Tools.
2 Principles of Modelling.
3 Financial Statement, Cash Flow and Valuation Modelling.
4 Risk Modelling.
5 Introduction to Options and Real Options Modelling.
6 VBA for Financial Modelling.
Posted September 7, 2009
Michael Rees succeeds to a large extent in his endeavor of writing a text that addresses the financial modeling process instead of Excel functionality, financial theory, or mathematical models. To his credit, Rees has put together a large number of useful modeling examples in the CD-ROM that is sold with the text. Rees' book assumes that readers have at least an intermediate knowledge of both statistical and financial concepts.
After reviewing select Excel functions and tools relevant to financial modeling, Rees gives his audience of modelers many practical tips about how to design, structure, and build models that are relevant, accurate, and easily understandable. Whoever has experience with models will probably agree with Rees when he writes that the majority of models built are in practice of mediocre quality. Someone other than the author of the model will often experience several challenges in dealing with the model at hand, i.e., too much time spent on understanding the model, complexity of the auditing and validating processes, hard to share with others, over-reliance on the original modeler to maintain or use it, lack of clarity of objectives, and presence of errors and implicit assumptions.
Rees then goes into the modeling of financial statements that is often required in the world of corporate finance for forecasting profit and cash, assessing financing requirements, analyzing credit risk and valuation, etc. This chapter is a little gem. It contains many practical tips. Once again, readers will be reminded that there is not always 100% agreement on the definition of some financial concepts.
Rees then uses Palisade Corporation's add-ins @RISK and PrecisionTree for many modeling examples in the two chapters that he dedicates to risk modeling and real option modeling, respectively. Having some understanding of both statistical and financial concepts is particularly important here to benefit from reading both chapters. Probably, many readers with an advanced knowledge of Excel 2007 will regret that the above-mentioned functionality that Palisade Corporation offers has not yet been systematically integrated into at least Microsoft Office Professional.
Finally, Rees discusses the use of Visual Basic for Applications (VBA) in a range of practical financial modeling situations. Rees points out that many otherwise competent modelers never learn VBA. For this reason, Rees makes the assumption that his audience is not very familiar with VBA. Rees shows how macros, i.e., subroutines and user-defined functions, can be used in a variety of modeling contexts.
In conclusion, Rees has made a valuable contribution to the field of financial modeling. The CD-ROM that is sold with the text plays a key role in achieving this objective.
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