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Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level


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

Michael Rees gained a BA with First Class Honours and a Doctorate in Mathematics from Oxford University in 1985 and 1988 respectively. In 1992 he gained an MBA with Distinction from INSEAD, and in 2003 graduated in first position on the Certificate in Quantitative Finance program, also winning the Wilmott award.

Since 2002 Michael has worked independently as a consultant and trainer in financial modelling. Prior to this he worked as a strategy consultant with Braxton Associates and Mercer Management Consulting, and also as an analyst at J.P. Morgan.

Michael lives in Richmond, UK. He was born in Canada, has lived in several countries, and is fluent in French and German.

Background, Objectives and Approach.

About The Author.


1. Building Blocks: Selected Excel Functions and Tools.

Core Functions for Financial Modelling.

Arithmetic Operations.

Logical Operations.

Financial Calculations.

Database Functions, Features and Pivot Tables.

Statistical Functions.

Lookup and Reference Functions.

Text Functions.

Information Functions.

Array Functions, Formulae and Matrix Calculations.

GoalSeek and Solver.

The Analysis ToolPak and Other Add-ins.

Selected Excel Short-cuts.

2. Principles of Modelling.

What is a Good Model?.

Model Design.

Selection of Model Variables and their Dependencies.

Level of Detail or Aggregation.

Model Structure and Planning.

Logical Flow.


Named Ranges.

Circular References.

Model Building.

Formatting and Comments.

Creating Robust Formulae.

Results Presentation and Other Uses of Sensitivity Analysis.

General Remarks on Presentation.

Using Data Tables to Conduct Sensitivity Analysis.

Hiding and Protecting Models.

Model Auditing.

3. Financial Statement, Cash Flow and Valuation Modelling.

Financial Statement Modelling: Core Points and Example.

General Comments.

Income Statement Forecasting.

Balance Sheet Forecasting.

Cash Flow Statement Forecasting.

Error Checks and Feasibility Checks.

General Error Checking Tools.

Feasibility Checking and Ratio Analysis.

Adding Generality.

Cash Flow Valuation.

Calculation of Free Cash Flow.

Discounting Free Cash Flow.

Terminal Value Calculations.

Further Adjustments.

Sensitivity Analysis.

4. Risk Modelling.

Benefits and Challenges of Risk Modelling.

The Risk Modelling Process.

An Introduction to Simulation Techniques.

The Language of Probability Distributions.

Quick Guide to using @RISK.

Types of Dependency Relationships in Risk Models.

The Selection and Use of Distributions.

Pragmatic Approaches and Distributions.

Data-Driven Approaches and Distributions.

Scientific Approaches and Distributions: The Basics.

Further Aspects of the Science of Distributions.

Further Example Models.

5. Introduction to Options and Real Options Modelling.

Financial Market Derivatives: An Introduction.

Real Options Modelling.

Uses and Relationships to Other Types of Analysis.

Examples using Simulation.

Examples using Trees.

6. VBA for Financial Modelling.


The Bare Essentials.

Simple Examples.

Building Blocks.

Working with Ranges.

Writing Robust Code.

Further Topics.

Object Orientation: An Introduction.

Controlling Execution and Related Topics.

Working with Functions.

Checking and Debugging Code.

Examples: Recording Macros and Related Topics.


Using GoalSeek and Solver.

Examples: Simulation Modelling.


Examples: User-defined Functions.

Creating Functions.


Structure and Organisation: Further Topics.

Further Reading.