The risk and return framework is generally accepted and discussed by scientists, at least since Markowitz introduced his Portfolio Theory in 1952. Subsequently, models were developed to evaluate investments under consideration of risk and return. Traditionally, practitioners primarily focused on past earnings as a measure of the profitability of an investment, without adequately considering potential risks. Therefore, the development of professional risk management systems was often neglected. Thus, the possibility of high losses was not appropriately incorporated in their investment strategies.
The consequences of such mistreatment became evident in the mid 1990s, when some of the world’s largest companies faced huge losses and sometimes even insolvency. Most of these failures were a direct result of inappropriate use of financial instruments and insufficient internal control mechanisms. The most spectacular debacles even resulted in losses of more than one billion dollars for each affected institution.
In case of Barings Bank, a single trader ruined the 233-year old British financial institution by inappropriate investments in high-risk futures in 1995. The consequent loss of $1.3 billion, realized in a very short period, could not be absorbed and forced the downfall of Barings. At Daiwa Bank, it was also a single trader who caused a $1.1 billion deficit. In contrast, the losses were accumulated over 11 years from 1984. Another well-publicized bankruptcy was declared in 1994 by the Californian Orange County, after losses of $1.8 billion. Such evidence of poor risk management and control shows that proper financial risk management is crucial for all kinds of institutions in order to guarantee stability and continuity.
Therefore, it is necessary to establish adequate risk management processes and to develop appropriate tools, which quantify risk exposures of both entire institutions and single financial instruments. This risk quantification should alert management early enough to prevent exceptional losses. One of the key concepts addressing these prob-lems of modern risk management was introduced in 1993 with the Value-at-Risk (VaR) models.
Inhaltsverzeichnis
- Introduction
- Purpose of the Study
- Calculation of VaR
- Calculation of VaR
- Risk Management Framework
- VaR Concept
- Calculation Methods
- Historical Method
- Monte Carlo Simulation Method
- Analytical Method
- Adaptation ofthe Principle Methods
- Weighting ofPast Observations
- Backtesting
- Scenario Analysis and Stress Testing
- Extreme Value Theory
- Evaluation of VaR
- Method Comparison
- Chances of VaR
- Practicability as a Risk Measure
- Realistic View of Risk
- Effective Risk Monitoring
- Flexibility of VaR models
- Support by Regulatory Body
- Limitations of VaR
- Confidence Interval
- Comparability of Results
- Sub-additivity
- Historical Data
- Application Difficulties
- Estimation Error and Fat-Tails
- Estimation Bias and Manipulation
- Conclusions
- Appendices
- References
Zielsetzung und Themenschwerpunkte
Die Seminararbeit befasst sich mit den Chancen und Grenzen von Value-at-Risk (VaR)-Modellen. Sie untersucht, wie VaR in den Rahmen des Risikomanagements integriert werden kann und welche Vorteile und Nachteile diese Methode bietet. Ziel ist es, die Eignung von VaR als Frühwarnsystem für potenzielle Verluste zu bewerten.
- Die Bedeutung des Risikomanagements für Unternehmen
- Das Konzept von Value-at-Risk (VaR)
- Die verschiedenen Methoden zur Berechnung von VaR
- Die Chancen und Vorteile von VaR-Modellen
- Die Grenzen und Einschränkungen von VaR-Modellen
Zusammenfassung der Kapitel
Das erste Kapitel führt in die Thematik des Risikomanagements ein. Es erläutert die Notwendigkeit eines strukturierten Risikomanagementprozesses, der die Identifizierung, Bewertung und Behandlung von Risiken umfasst. Darüber hinaus werden die verschiedenen Arten von Risiken, wie z. B. Geschäftsrisiken, Nicht-Geschäftsrisiken und Finanzrisiken, vorgestellt.
Im zweiten Kapitel wird das Konzept von Value-at-Risk (VaR) vorgestellt. Es wird erläutert, wie VaR als ein Maß für das potenzielle Verlustrisiko eines Portfolios definiert ist. Die verschiedenen Methoden zur Berechnung von VaR, wie die historische Methode, die Monte-Carlo-Simulation und die analytische Methode, werden detailliert beschrieben. Darüber hinaus werden verschiedene Anpassungen dieser Methoden, wie z. B. die Gewichtung vergangener Beobachtungen, Backtesting und Szenarioanalysen, diskutiert.
Das dritte Kapitel befasst sich mit der Bewertung von VaR-Modellen. Es werden die Chancen und Vorteile von VaR, wie z. B. die Praktikabilität, die Realitätsnähe und die Flexibilität, sowie die Grenzen und Einschränkungen, wie z. B. die Subadditivität, die Abhängigkeit von historischen Daten und die Anfälligkeit für Manipulationsversuche, diskutiert.
Schlüsselwörter
Die Schlüsselwörter und Schwerpunktthemen des Textes umfassen Value-at-Risk (VaR), Risikomanagement, Finanzrisiken, Marktpreisvolatilität, historische Simulation, Monte-Carlo-Simulation, analytische Methode, Chancen und Grenzen von VaR-Modellen, Subadditivität, historische Daten, Backtesting, Szenarioanalysen, Regulierungsbehörden, Basler Ausschuss für Bankenaufsicht, Securities and Exchange Commission (SEC).
- Quote paper
- Alexander Linn (Author), Dennis Röhrig (Author), 2004, What are the chances and limitations of value-at-risk (VaR) models?, Munich, GRIN Verlag, https://www.grin.com/document/55350
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