Excerpt
Table of Content
List of Figures
List of Abbreviations
1. Introduction
1.1 Reasoning and Motivation
1.2 Structure of the Article
2. Risks in the Banking Sector
2.1 Definition of Risk
2.2 Structuring Risks in the Banking Sector
3. Measuring Risk with the Value at Risk
3.1 Definition of the Value at Risk
3.2 Meaning of the VaR for Risk Management in Banks
3.3 Structuring the Types of VaR Models
4. Modelling Credit Risk
4.1 Determinants for Modelling Credit Risk
4.2 Combining the Input Factors
4.3 Distribution of Credit Risk
5. The Monte Carlo Simulation
5.1 Basic Idea of the Monte Carlo Simulation
5.2 Migration Metrics by Random Scenarios
5.3 Discussing Advantages and Disadvantages of the Monte Carlo Approach
6. Development of a Simplified Monte Carlo Tool at the Example of a Bond Portfolio
6.1 Describing the Model
6.2 Setting up the Excel Sheet
6.3 Programming the Monte Carlo in Excel VBA
6.4 Analysing and Interpreting the Results
7. Monte Carlo Models in the German Banking Sector
7.1 General Overview
7.2 CreditPortfolioView: The Solution of the Savings Bank Sector
8. Final Conclusion and Critical Outlook
Bibliography
- Quote paper
- Svend Reuse (Author), 2010, The Monte Carlo Simulation in Banks , Munich, GRIN Verlag, https://www.grin.com/document/152589
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