Parametric And Nonparametric Approaches To VaR Calculation And Its Application In China Stock Exchange Market

VaR is the abbreviation of Value at Risk. It's a brand new tool of Finance Risk Management rising from West Country and is used to estimate the possible and potential loss of appointed financial products or portfolio according to the fluctuation of prices. The concept of VaR is very simple, but the measurement method is a challenged item in statistics. Surrounding the estimating method of VaR, some specialists and scholars in West Country have made deeper research. In the recent years, some Chinese experts start to apply the tool of VaR and try researching the relevant theory of it. Based on the theories of the former experts, this article makes further statement about Value at Risk and applies some relevant data of China stock market to analyze the application of VaR for risk measurement in our stock market. It's in order to form the operation system of stock risk measurement and to promote the development of our stock market more stable. Value at Risk (VaR) is a fundamental tool for managing market risks. It measures the worst loss to be expected of a portfolio over a given time horizon under normal market conditions at a given confidence level. This dissertation will give brief introduction of five parametric and nonparametric estimation approaches to VaR Calculation as well as their relative advantages in practice. Then, an empirical study of their statistical efficiencies is imposed on the Shanghai Stock Exchange index in China. There will also be an implication of the chosen methods of VaR forecast and test on the risk control of two portfolios of stocks chosen from that market index. Finally, we come to the conclusion that historical simulation always works pretty well for both index and portfolio VaRs at certain confidence level. While parametric approaches still need further improvements that based on the volatility model.