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The complete guide to the principles and practice of risk quantification for business applications.The assessment and quantification of risk provide an indispensable part of robust decision-making; to be effective, many professionals need a firm grasp of both the fundamental concepts and of the tools of the trade. Business Risk and Simulation Modelling in Practice is a comprehensive, in-depth, and practical guide that aims to help business risk managers, modelling analysts and general management to understand, conduct and use quantitative risk assessment and uncertainty modelling in their own situations. Key content areas include:* Detailed descriptions of 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 the principles and concepts in 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 simulation techniques 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.Business Risk and Simulation Modelling in Practice reflects the author's many years in training and consultancy in these areas. It provides clear and complete guidance, enhanced with an expert perspective. It uses approximately one hundred practical and real-life models to demonstrate all key concepts and techniques; these are accessible on the companion website.

Business Risk and Simulation Modelling in Practice: Using Excel, VBA and @RISK

Preface xviiAbout the Author xxiiiAbout the Website xxvPART I An Introduction to Risk Assessment - Its Uses, Processes, Approaches, Benefits and ChallengesCHAPTER 1 The Context and Uses of Risk Assessment 31.1 Risk Assessment Examples 31.2 General Challenges in Decision-Making Processes 71.3 Key Drivers of the Need for Formalised Risk Assessment in Business Contexts 141.4 The Objectives and Uses of General Risk Assessment 19CHAPTER 2 Key Stages of the General Risk Assessment Process 292.1 Overview of the Process Stages 292.2 Process Iterations 302.3 Risk Identification 322.4 Risk Mapping 352.5 Risk Prioritisation and Its Potential Criteria 362.6 Risk Response: Mitigation and Exploitation 422.7 Project Management and Monitoring 44CHAPTER 3 Approaches to Risk Assessment and Quantification 453.1 Informal or Intuitive Approaches 463.2 Risk Registers without Aggregation 463.3 Risk Register with Aggregation (Quantitative) 503.4 Full Risk Modelling 56CHAPTER 4 Full Integrated Risk Modelling: Decision-Support Benefits 594.1 Key Characteristics of Full Models 594.2 Overview of the Benefits of Full Risk Modelling 614.3 Creating More Accurate and Realistic Models 624.4 Using the Range of Possible Outcomes to Enhance Decision-Making 744.5 Supporting Transparent Assumptions and Reducing Biases 844.6 Facilitating Group Work and Communication 86CHAPTER 5 Organisational Challenges Relating to Risk Modelling 875.1 "We Are Doing It Already" 875.2 "We Already Tried It, and It Showed Unrealistic Results" 895.3 "The Models Will Not Be Useful!" 915.4 Working Effectively with Enhanced Processes and Procedures 935.5 Management Processes, Culture and Change Management 96PART II The Design of Risk Models - Principles, Processes and MethodologyCHAPTER 6 Principles of Simulation Methods 1076.1 Core Aspects of Simulation: A Descriptive Example 1076.2 Simulation as a Risk Modelling Tool 1126.3 Sensitivity and Scenario Analysis: Relationship to Simulation 1166.4 Optimisation Analysis and Modelling: Relationship to Simulation 1226.5 Analytic and Other Numerical Methods 1336.6 The Applicability of Simulation Methods 135CHAPTER 7 Core Principles of Risk Model Design 1377.1 Model Planning and Communication 1387.2 Sensitivity-Driven Thinking as a Model Design Tool 1467.3 Risk Mapping and Process Alignment 1547.4 General Dependency Relationships 1587.5 Working with Existing Models 173CHAPTER 8 Measuring Risk using Statistics of Distributions 1818.1 Defining Risk More Precisely 1818.2 Random Processes and Their Visual Representation 1848.3 Percentiles 1878.4 Measures of the Central Point 1908.5 Measures of Range 1948.6 Skewness and Non-Symmetry 1998.7 Other Measures of Risk 2038.8 Measuring Dependencies 207CHAPTER 9 The Selection of Distributions for Use in Risk Models 2159.1 Descriptions of Individual Distributions 2159.2 A Framework for Distribution Selection and Use 2569.3 Approximation of Distributions with Each Other 263CHAPTER 10 Creating Samples from Distributions 27310.1 Readily Available Inverse Functions 27410.2 Functions Requiring Lookup and Search Methods 27710.3 Comparing Calculated Samples with Those in @RISK 27910.4 Creating User-Defined Inverse Functions 28010.5 Other Generalisations 287CHAPTER 11 Modelling Dependencies between Sources of Risk 29111.1 Parameter Dependency and Partial Causality 29111.2 Dependencies between Sampling Processes 30211.3 Dependencies within Time Series 316PART III Getting Started with Simulation in PracticeCHAPTER 12 Using Excel/VBA for Simulation Modelling 32712.1 Description of Example Model and Uncertainty Ranges 32712.2 Creating and Running a Simulation: Core Steps 32812.3 Basic Results Analysis 33512.4 Other Simple Features 33912.5 Generalising the Core Capabilities 34012.6 Optimising Model Structure and Layout 34312.7 Bringing it All Together: Examples Using the Simulation Template 35012.8 Further Possible uses of VBA 354CHAPTER 13 Using @RISK for Simulation Modelling 36513.1 Description of Example Model and Uncertainty Ranges 36513.2 Creating and Running a Simulation: Core Steps and Basic Icons 36613.3 Simulation Control: An Introduction 37713.4 Further Core Features 38413.5 Working with Macros and the @RISK Macro Language 40513.6 Additional In-Built Applications and Features: An Introduction 41713.7 Benefits of @RISK over Excel/VBA Approaches: A Brief Summary 421Index 425