Research On Value At Risk In Measuring Financial Market Risk

The large increase in the number of traded assets in the portfolio of most financial institutions has made the measurement of market risk a primary concern for regulators and for internal risk control. After being proposed in 1993, VaR approach has become the standard for risk management industry.Though VaR has many compute methods, they have limitations. Almost all of the traditional methods estimating tail-related risk VaR focus on the central observations or, in other words, on returns under normal market conditions. However, VaR are risk measures that relates solely to the tails of the distribution. The extreme values which lies in the tail are some rarely happened events that have significant influence. Extreme Value Theory(EVT) is the statistical model to study the behavior of extreme values. This paper introduces the basic knowledge of EVT and estimates VaR using VaR. The applications methods of EVT have POT model and mixing methods. And based on the stock date of Shanghai Securities Exchange, this paper makes an empirical analysis of VaR estimation. Empirical findings conclude the EVT can well approximate the tail of financial return distribution.Financial dates analysis shows that the return rates distribution is fat-tailed and doesn't obey normal distribution and there is"leverage effect". We find the GARCH model could describe the fluctuation of price in some degrees. But each of the model has limitations, the sort of those method has an obvious shortcoming is that these models based on the merely recent return data which have neglect the experience data.Moreover, this paper introduction the risk measuring of options, and estimated the VaR of the stock options of"qing hua tong fang"by Monte Carlo Simulation. This is a great help to development of options and stock options.