Books by Dr. Michael Rees


Published 2018

Originally intended as a Second Edition of Financial Modelling in Practice, this book focusses on the underlying principles and practices to design and build robust and useful models:
  •  Explains how to plan, design and build financial models that are flexible, robust, transparent, and highly applicable to a wide range of planning, forecasting and decision-support contexts.
  • Covers a wide set of financial modelling tools and techniques
  •  Provided practical skills that are grounded in real-world applications.
  • Based on rigorously-tested materials created for consulting projects and training courses.
  • Integrates theory with practice to provide a high-value resource for anyone wanting to gain a practical understanding of the nuances of this topic.

Extensive coverage of:

  • Model design and best practices, including the optimisation of data structures and layout, maximising transparency, balancing complexity with flexibility, dealing with circularity, model audit and error-checking
  • Sensitivity and scenario analysis, simulation, and optimisation
  • Data manipulation and analysis
  • The use and choice of Excel functions and functionality, including advanced functions and those from all categories, as well as of VBA and its key areas of application within financial modelling

The companion website provides approximately 235 Excel files (screen-clips of most of which are shown in the text), which demonstrate key principles in modelling, as well as providing many examples of the use of Excel functions and VBA macros. These facilitate learning and have a strong emphasis on practical solutions and direct real-world application.

Published 2015

  • Risk assessment processes, their objectives and uses, possible approaches to risk quantification, and their associated decision-benefits and organisational challenges.
  • Principles and techniques in the design of risk models, including the similarities and differences with traditional financial models, and the enhancements that risk modelling can provide.
  • In depth coverage of simulation methods, the statistical measurement of risk, the use and selection of probability distributions, the creation of dependency relationships, the alignment of risk modelling activities with general risk assessment processes, and a range of Excel modelling techniques.
  • The implementation of models using both Excel/VBA macros and the @RISK Excel add-in. Each platform may be appropriate depending on the context, whereas the core modelling concepts and risk assessment contexts are largely the same in each case. Some additional features and key benefits of using @RISK are also covered.

Published 2007

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. 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.

The book is structured into six Chapters:

  • Chapter 1 reviews a selection of Excel functions that are generally most relevant for building intermediate and advanced level models. It presents many practical examples of the application of these functions.
  • Chapter 2 discusses the principles involved in designing, structuring and building relevant, accurate and readily understandable models.  Topics covered include the use of sensitivity analysis, best practice modelling principles and related issues, and model auditing tools.
  • Chapter 3 covers the modelling of financial statements and of cash flow valuation.  We discuss a variety of ways to deal with each of the core modelling issues that arise in these applications.
  • Chapter 4 covers risk and uncertainty modelling.  Many practical applications and example models are presented in an intuitive and accessible way.  We use an add-in to Excel to implement simulation models; such an approach also allows readers to rapidly build their own models.
  • Chapter 5 covers options and real options modelling, treating these as a natural extension of risk modelling.  The approach to real options modelling is less theoretical than in some other texts, and does not specifically require knowledge of financial market derivatives.  Models are implemented using Excel as well as add-ins for simulation and decision trees, and readers should be able to build their own models after reading this Chapter.
  • Chapter 6 covers VBA for financial modelling applications.  The topics selected for inclusion have been established by consideration of the core types of financial models that frequently require the use of VBA.  The Chapter should provide beginners in this area with a focussed and practical guide to the topic, and a base on which to discover the richer possibilities available to modellers by using VBA.