The Monte Carlo Simulation in Banks

Simplified Example in MS Excel and Practical Approach in German Savings Banks


Essai Scientifique, 2010

29 Pages


Extrait


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

Fin de l'extrait de 29 pages

Résumé des informations

Titre
The Monte Carlo Simulation in Banks
Sous-titre
Simplified Example in MS Excel and Practical Approach in German Savings Banks
Université
Masaryk University  (Fakultät für Wirtschaft und Verwaltung)
Cours
---
Auteur
Année
2010
Pages
29
N° de catalogue
V152589
ISBN (ebook)
9783640645824
ISBN (Livre)
9783640645855
Taille d'un fichier
814 KB
Langue
anglais
Mots clés
Value at Risk, Monte Carlo, Credit Risk, Bank, CreditPortfolioView, CreditRisk+, CreditMetrics, Excel Tool
Citation du texte
Svend Reuse (Auteur), 2010, The Monte Carlo Simulation in Banks , Munich, GRIN Verlag, https://www.grin.com/document/152589

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