Extreme Value Theory and its Applications to Financial Risk Management
The phenomenon of high volatility in financial markets stemming from the increased complexity of financial instruments traded, as well as the evidence of losses due to natural and man-made catastrophes, highlight the need for sophisticated risk management practices. The analysis concerning the statistical distribution of extreme events (e.g. stock market crashes), is considered to be important for modern risk management. In this review paper, an introduction to the basic results of Extreme Value Theory (EVT) is made. More specifically, the methodological basis of EVT for quantile estimation is introduced. Moreover, EVT methods for estimating conditional probabilities concerning tail events, given that we incur a loss beyond a certain threshold u, are presented. Finally, the application of the theory is demonstrated by considering an example using equity return data
|Date of creation:||1998|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: https://mpra.ub.uni-muenchen.de
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:6281. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht)
If references are entirely missing, you can add them using this form.