How to accurately measure liquidity risk of commercial banks is a significant issue. Nowadays, the primary measurement methods are to apply some simple financial indicators, VaR or L-VaR. Because of the nature defects, these methods would affect the effectiveness of risk measurement in certain extreme environments such as the financial crisis. In the light of the defects, this paper presents a measurement model based on POT-ES(n) in order to capture the liquidity risk that commercial banks face more effectively in extreme cases. The result of Back Test shows that the risk values obtained from POT-ES(n) model perform better in liquidity risk measurement.
Published in:
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
(Volume:2
)
Date of Conference: 11-12 May 2010