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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 [...] 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 [...] 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.
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 [...] 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 [...] 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.
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 [...] 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 [...] 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.
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 [...] 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 [...] 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.
Über den Autor
MICHAEL REES is an independent consultant and trainer for financial modelling. He works for a wide range of clients, including major corporations, private equity firms, fund managers, strategy consultants and risk management consultants.
Inhaltsverzeichnis
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 [...] 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 [...] 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 [...] Macro Language 405
13.6 Additional In-Built Applications and Features: An Introduction 417
13.7 Benefits of [...] over Excel/VBA Approaches: A Brief Summary 421
Index 425
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 [...] 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 [...] 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 [...] Macro Language 405
13.6 Additional In-Built Applications and Features: An Introduction 417
13.7 Benefits of [...] over Excel/VBA Approaches: A Brief Summary 421
Index 425
Details
| Erscheinungsjahr: | 2015 |
|---|---|
| Fachbereich: | Betriebswirtschaft |
| Genre: | Wirtschaft |
| Rubrik: | Recht & Wirtschaft |
| Medium: | Buch |
| Seiten: | 464 |
| Inhalt: | 464 S. |
| ISBN-13: | 9781118904053 |
| ISBN-10: | 1118904052 |
| Sprache: | Englisch |
| Herstellernummer: | 1W118904050 |
| Einband: | Gebunden |
| Autor: | Rees, Michael |
| Hersteller: |
Wiley
John Wiley & Sons |
| Maße: | 251 x 172 x 32 mm |
| Von/Mit: | Michael Rees |
| Erscheinungsdatum: | 21.09.2015 |
| Gewicht: | 0,948 kg |
Über den Autor
MICHAEL REES is an independent consultant and trainer for financial modelling. He works for a wide range of clients, including major corporations, private equity firms, fund managers, strategy consultants and risk management consultants.
Inhaltsverzeichnis
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 [...] 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 [...] 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 [...] Macro Language 405
13.6 Additional In-Built Applications and Features: An Introduction 417
13.7 Benefits of [...] over Excel/VBA Approaches: A Brief Summary 421
Index 425
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 [...] 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 [...] 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 [...] Macro Language 405
13.6 Additional In-Built Applications and Features: An Introduction 417
13.7 Benefits of [...] over Excel/VBA Approaches: A Brief Summary 421
Index 425
Details
| Erscheinungsjahr: | 2015 |
|---|---|
| Fachbereich: | Betriebswirtschaft |
| Genre: | Wirtschaft |
| Rubrik: | Recht & Wirtschaft |
| Medium: | Buch |
| Seiten: | 464 |
| Inhalt: | 464 S. |
| ISBN-13: | 9781118904053 |
| ISBN-10: | 1118904052 |
| Sprache: | Englisch |
| Herstellernummer: | 1W118904050 |
| Einband: | Gebunden |
| Autor: | Rees, Michael |
| Hersteller: |
Wiley
John Wiley & Sons |
| Maße: | 251 x 172 x 32 mm |
| Von/Mit: | Michael Rees |
| Erscheinungsdatum: | 21.09.2015 |
| Gewicht: | 0,948 kg |
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