Business Risk and Simulation Modelling in Practice – Using Excel, VBA and @RISK +Website de M Rees

Business Risk and Simulation Modelling in Practice – Using Excel, VBA and @RISK +Website: The Wiley Finance Series

M Rees

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.

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Cuprins

Preface xvii About the Author xxiii About the Website xxv PART I An Introduction to Risk Assessment - Its Uses, Processes, Approaches, Benefits and Challenges CHAPTER 1 The Context and Uses of Risk Assessment 3 1.1 Risk Assessment Examples 3 1.2 General Challenges in Decision-Making Processes 7 1.3 Key Drivers of the Need for Formalised Risk Assessment in Business Contexts 14 1.4 The Objectives and Uses of General Risk Assessment 19 CHAPTER 2 Key Stages of the General Risk Assessment Process 29 2.1 Overview of the Process Stages 29 2.2 Process Iterations 30 2.3 Risk Identification 32 2.4 Risk Mapping 35 2.5 Risk Prioritisation and Its Potential Criteria 36 2.6 Risk Response: Mitigation and Exploitation 42 2.7 Project Management and Monitoring 44 CHAPTER 3 Approaches to Risk Assessment and Quantification 45 3.1 Informal or Intuitive Approaches 46 3.2 Risk Registers without Aggregation 46 3.3 Risk Register with Aggregation (Quantitative) 50 3.4 Full Risk Modelling 56 CHAPTER 4 Full Integrated Risk Modelling: Decision-Support Benefits 59 4.1 Key Characteristics of Full Models 59 4.2 Overview of the Benefits of Full Risk Modelling 61 4.3 Creating More Accurate and Realistic Models 62 4.4 Using the Range of Possible Outcomes to Enhance Decision-Making 74 4.5 Supporting Transparent Assumptions and Reducing Biases 84 4.6 Facilitating Group Work and Communication 86 CHAPTER 5 Organisational Challenges Relating to Risk Modelling 87 5.1 "We Are Doing It Already" 87 5.2 "We Already Tried It, and It Showed Unrealistic Results" 89 5.3 "The Models Will Not Be Useful!" 91 5.4 Working Effectively with Enhanced Processes and Procedures 93 5.5 Management Processes, Culture and Change Management 96 PART II The Design of Risk Models - Principles, Processes and Methodology CHAPTER 6 Principles of Simulation Methods 107 6.1 Core Aspects of Simulation: A Descriptive Example 107 6.2 Simulation as a Risk Modelling Tool 112 6.3 Sensitivity and Scenario Analysis: Relationship to Simulation 116 6.4 Optimisation Analysis and Modelling: Relationship to Simulation 122 6.5 Analytic and Other Numerical Methods 133 6.6 The Applicability of Simulation Methods 135 CHAPTER 7 Core Principles of Risk Model Design 137 7.1 Model Planning and Communication 138 7.2 Sensitivity-Driven Thinking as a Model Design Tool 146 7.3 Risk Mapping and Process Alignment 154 7.4 General Dependency Relationships 158 7.5 Working with Existing Models 173 CHAPTER 8 Measuring Risk using Statistics of Distributions 181 8.1 Defining Risk More Precisely 181 8.2 Random Processes and Their Visual Representation 184 8.3 Percentiles 187 8.4 Measures of the Central Point 190 8.5 Measures of Range 194 8.6 Skewness and Non-Symmetry 199 8.7 Other Measures of Risk 203 8.8 Measuring Dependencies 207 CHAPTER 9 The Selection of Distributions for Use in Risk Models 215 9.1 Descriptions of Individual Distributions 215 9.2 A Framework for Distribution Selection and Use 256 9.3 Approximation of Distributions with Each Other 263 CHAPTER 10 Creating Samples from Distributions 273 10.1 Readily Available Inverse Functions 274 10.2 Functions Requiring Lookup and Search Methods 277 10.3 Comparing Calculated Samples with Those in @RISK 279 10.4 Creating User-Defined Inverse Functions 280 10.5 Other Generalisations 287 CHAPTER 11 Modelling Dependencies between Sources of Risk 291 11.1 Parameter Dependency and Partial Causality 291 11.2 Dependencies between Sampling Processes 302 11.3 Dependencies within Time Series 316 PART III Getting Started with Simulation in Practice CHAPTER 12 Using Excel/VBA for Simulation Modelling 327 12.1 Description of Example Model and Uncertainty Ranges 327 12.2 Creating and Running a Simulation: Core Steps 328 12.3 Basic Results Analysis 335 12.4 Other Simple Features 339 12.5 Generalising the Core Capabilities 340 12.6 Optimising Model Structure and Layout 343 12.7 Bringing it All Together: Examples Using the Simulation Template 350 12.8 Further Possible uses of VBA 354 CHAPTER 13 Using @RISK for Simulation Modelling 365 13.1 Description of Example Model and Uncertainty Ranges 365 13.2 Creating and Running a Simulation: Core Steps and Basic Icons 366 13.3 Simulation Control: An Introduction 377 13.4 Further Core Features 384 13.5 Working with Macros and the @RISK Macro Language 405 13.6 Additional In-Built Applications and Features: An Introduction 417 13.7 Benefits of @RISK over Excel/VBA Approaches: A Brief Summary 421 Index 425