Bank capital regulation : a comparison of risk measurements based on the GVAR model

Risk measures are the core indicator of risk management and a proper risk assessment model is essential for successful financial institutions. Value at Risk and Expected Shortfall are the two most popular and acceptable risk measurement methods presently employed to assess risks in the financial market. In the past few years, researchers have attempted to demonstrate that Expected Shortfall performs better against the traditional Value at Risk method. However, the lack of elicitability and difficult backtesting of this method suggest that the popularisation of ES might be gradual. This thesis will present a comparison of these two methods not only from a traditional perspective, such as the measurement of tail risk, but also form the perspective of risk capital requirement. Through Historical Simulation and Filtered Historical Simulation, it concludes that switching from Value at Risk to Expected Shortfall method would reduce risk capital requirement and enhance financial leverage of organisations. Additionally, this research also combines macroeconomic elements, the financial market and central banks, and analyses the influence of a positive leverage shock on the macro-economy through a Global Vector Autoregression model.