| dc.description.abstract | Assessing the extreme events is crucial in financial risk management. All risk managers
and financial institutions want to know the risk of their portfolio under rare events scenarios.
This means there is not only a need to design proper risk modelling techniques
which can predict the probability of risky events in normal market conditions but also a
requirement for tools which can assess the probabilities of rare financial events; like the
recent Global Financial Crisis (2007-2008). Extreme Value ;Theory (EVT) is an obvious
candidate, when dealing with extreme financial events and t~e quantification of extreme
market risk. Extreme Value Theory provides well established statistical models for the
computation of extreme risk measures like the Return Level, Value at Risk and Expected
Shortfall.
In this research we propose to describe the theoretical foundation of the extreme value
theory and its potential in financial risk management. In relation to this, we will emphasize
the statistical issues and limitations of the theory with applications in financial risk
management in mind. Moreover, we will discuss how the theory may be applied to financial
data and the specific issues that may arise in such applications. Also, we will introduce the
issue of working with multivariate risk factors using copula theory and discuss some copula
results in multivariate extreme value theory.
The research study will focus on an empirical study of the performance of EVT-based
risk measurement methods based on five selected currency exchange rates: KSH/USD,
KSH/GBP, KSH/EUR, KSH/ JPY and KSH/RAND. The performance of the methods will
be evaluated by their ability to accurately estimate well-known risk measures such as Value
at Risk (VaR) and Expected Shortfall (ES).
Finally, we will compare the performance of EVT-based risk measurement methods for
estimating risk measures. The performance of the model will be evaluated by its ability to
accurately estimate well-known risk measures such as Value at Risk (VaR) and Expected
Shortfall (ES). We will also backtest VaR and ES estimates at different confidence levels
to validate the proposed model.
Keywords: Extreme Value Theory, copula, Value at Risk, and Expected Shortfall. | en_US |
