VaR Risk Measurements And The Sensitivity Analysis Based On The Jump-Vasicek Model

As a financial risk measurement tool, VaR was put forward by the G30 (Group of Thirty) international economic and financial consultancy in the report of "the derivatives of practices and principles". VaR, in briefly, is the potential biggest loss which the given risk assets faced in a certain holding period as well as a certain degree of confidence.On the valuation of VaR, in recent years, one of the topics is using the market interest rates to discount the risky assets, then to give the VaR measurement indirectly. For example, Na Song et al. (2012) considered the market interest rates satisfied the Merton, Vasicek, CIR diffusion model, and studied the problem on the VaR risk measurement and the characteristics about risk and so on under the different models. Because of the real financial markets tend to be influenced by many unexpected events (financial policy changes, political instability, etc.), there may be exist the jump phenomena in the market interest rates, Therefore, there are both theoretical and practical meaning for the problem of VaR valuation under the interest rates satisfying Vasicek model containing a Jump-diffusion proess.Firstly, based on Na Song’ work, we assume in this paper that the stochastic interest rates follow the Jump-Vasicek model, and compute the mean and variance for the risky assets’ expects loss, then evaluate the risky assets’ VaR under a given confidence level.Secondly, by using the MATLAB algorithm, this paper gives a detail study about the sensibility of the related parameters on stochastic interest rates and VaR risk measurement values. Through MATLAB chart it gives the influence of various parameters under the Jump-Vasicek model on stochastic interest rates and the final risk measurement VaR;Finally, the paper makes a numerical comparison between the VaR risk measurement under the Vasicek model and that under the Jump-Vasicek model, it concludes that the decision based on Jump-diffusion process VaR risk measurement is more robustness.The result posed here can be regarded as a natural generalization of the work by Na Song, et al.