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Financial Forecasting, Analysis and Modelling: A Framework for Long-Term Forecasting


Praise for Financial Forecasting, Analysis, and Modelling

"Modeling is one of the tools that you need in your tool kit to do valuation, and this book will help you get more facile with that tool".
—Aswath Damodaran, Professor of Finance at the Stern School of Business at New York University (Kerschner Family Chair in Finance Education)

"An excellent and unique piece of work clearly done by someone who does not only have a deep sectoral but also a comprehensive knowledge of the subject".
—Marios T. Kyriacou, Senior Partner of KPMG

"This book is an excellent guide to financial forecasting, analysis and modelling, covering key areas well and providing thoroughly worked examples that are clear and helpful. I consider this being a most useful book for the novice and the professional alike".
—Vassili Christidis, CEO, Euler Hermes Hellas

"This book builds around a full-length case study of a real world company and walks readers through all the steps of developing a sophisticated financial model which includes business valuation and applied Monte Carlo analysis. The author is clearly intimately familiar with financial modelling, a craft that is nowadays a prerequisite for the finance practitioner".
—Daniel Benardout, Member of the Board of Governors of Technion Israel Institute of Technology

"Financial Forecasting, Analysis, and Modelling is packed with invaluable material for anyone looking to plan effectively for the future of a business. The author provides incisive analysis of financial modeling tips, techniques and templates in Excel for analyzing a company's current financial performance as well as forecasting its future one. Everyone interested in the application of financial forecasting and modeling – whether student or seasoned businessman – would profit from reading this book."
—Alex Ypsilanti, CEO and Co-Founder of Quantifeed, Hong Kong (previously served as Managing Director and research analyst in equity derivatives and quantitative investment strategies with Morgan Stanley and Merrill Lynch)

MICHAEL SAMONAS is a finance professional with extensive experience in Financial Planning, Analysis and Modelling. He is currently the Group CFO of SIDMA S.A, a member of Viohalco Group of companies. He has worked in the past for various multinationals including Vodafone S.A. and Hellenic Telecommunications Organization conducting a range of models for business planning, valuations, mergers, projects and data analysis. For a number of years Michael was instructor at the School of Business & Economics of the University of Laverne, Athens Campus.

Preface xi

Acknowledgments xiii

About the Author xv

Part one Developing Corporate Finance Models 1

Chapter 1 Introduction 3

1.1 What is Financial Modelling? 3

1.2 Defining the Inputs and the Outputs of a Simple Financial Model 6

1.3 The Financial Modelling Process of More Complex Models 9

1.3.1 Step 1: Defining the Problem the Model Will Solve: The Fundamental Business Question 9

1.3.2 Step 2: Specification of the Model 10

1.3.3 Step 3: Designing and Building the Model 11

1.3.4 Step 4: Checking the Model’s Output 13

1.4 Excel as a Tool of Modelling: Capabilities and Limitations 13

Chapter 2 A Short Primer in the Accounting of Financial Statements 17

2.1 The Accounting Equation 17

2.2 The Balance Sheet 20

2.3 The Income Statement 23

2.3.1 Cash Accounting Versus Accrual Accounting 26

2.4 The Cash Flow Statement 26

2.4.1 Operating Activities 27

2.4.2 Investing Activities 27

2.4.3 Financing Activities 27

2.4.4 Income Flows and Cash Flows 27

2.4.5 Preparing the Statement of Cash Flows 28

2.5 The Articulation of Income Statement, Balance Sheet, and Cash Flow Statements 29

2.6 Financial Statement Analysis: Ratio Analysis 32

2.6.1 Profitability Ratios 35

2.6.2 Liquidity Ratios 37

2.6.3 Solvency Ratios 38

2.6.4 Other Ratios 39

2.6.5 The Limitations of Financial Ratios 40

Chapter 3 Financial Statement Modelling 43

3.1 Introduction – How Financial Models Work 43

3.2 Collecting and Analyzing Historical Data 47

3.3 Selecting the Key Forecast Drivers 53

3.4 Modelling the Income Statement 59

3.5 Modelling the Balance Sheet 63

3.6 Modelling Interest and Circular References 66

3.7 Modelling the Cash Flow Statement 69

Chapter 4 Forecasting Performance 75

4.1 Introduction: Designing a Dashboard-like Control Panel 75

4.2 Basic Statistical Methods Used for Forecasting 88

4.3 Forecasting Sales 93

4.3.1 Bottom-up Versus Top-down Forecasting 97

4.3.2 Forecasting Sales of Existing Products or Services 97

4.4 Forecasting Costs 99

4.5 Forecasting CAPEX and Depreciation 103

4.5.1 Forecasting CAPEX and Depreciation for Existing Companies 108

4.6 Forecasting Working Capital and Funding Needs 110

4.6.1 Forecasting Funding Needs 113

Chapter 5 Business Valuation 115

5.1 Valuation Approaches 115

5.2 Steps for Applying the DCF Method 120

5.3 Rewriting Financial Statements – Calculation of Free Cash Flows 121

5.4 Calculating the Weighted Average Cost of Capital 124

5.4.1 Calculating the Weighted Average Cost of Capital of SteelCo 128

5.5 Estimating the Terminal Value 131

5.6 DCF Summary – Enterprise Value Adjustments 132

Part two Planning for Uncertainty 137

Chapter 6 Using Sensitivity Analysis 139

6.1 Introduction 139

6.2 One-Dimensional and 2-Dimensional Sensitivity Analysis 140

6.3 Choosing the Variables to Change 145

6.4 Modelling Example 149

6.4.1 Selecting the Variables to Change 149

6.4.2 Assigning a Range of Values 149

6.4.3 Constructing the 2-dimensional Sensitivity Analysis Table 151

6.4.4 Interpreting the Results 153

Chapter 7 Using Scenarios 157

7.1 Introduction 157

7.2 Using Scenario Analysis with Excel’s Scenario Manager 158

7.2.1 Adding 2 More Scenarios 159

7.3 Alternative Ways to Create Scenarios in Excel 163

7.4 Applying Scenarios to SteelCo’s Case 167

7.4.1 Deciding on the Number of Scenarios and Input Variables under each Scenario 167

7.4.2 Deciding on the Output Variables 168

7.4.3 Assigning Values to the Input Variables under Each Scenario 170

7.4.4 Building the Scenarios in Excel’s Scenario Manager 173

7.4.5 Interpreting the Results 176

Chapter 8 Using Monte Carlo Simulation 179

8.1 Introduction 179

8.2 Building Uncertainty Directly Into the Modelling Process 180

8.3 Probabilities, Cumulative Probabilities, and Frequency Distribution Charts 182

8.4 Modelling Example 187

8.4.1 Identifying the Key Risk Variables 188

8.4.2 Choosing a Probability Distribution for Each Input Variable 188

8.4.3 Performing the Simulation Runs 190 The Simple VBA CODE 192

8.4.4 Creating a Histogram (Frequency Distribution Chart) in Excel 195

8.4.5 Interpreting the Results 200

8.4.6 Some Issues of Concern 201

Appendix 203

1. Walking through the Excel Model Provided with the Book (SteelCo SA 4yr Business Plan) 203

Introduction 203

Structure of the Model 204

2. Other Excel Files Provided with the Book 205

Index 207