Study On Financial Risk Theory And Its Application

As financial market develops, risk grows much more complication. Risk is future's uncertain loss. Facing the financial risk, how to measure it accurately is an important research subject. The emergence of Value at Risk (VaR) enables us to quantify the maximum loss of financial portfolios in certain period. VaR has become a common tool to measure market risk, and can also be taken as the benchmark in the risk management up to now.At first, a deeper research has been done on VaR system in this paper. It has introduced in detail three primary calculational methods of VaR and analyzed comparatively their respective strongpoints or shortcomings and applicability. Although the VaR method was popular in recent years, it has various theoretical deficiencies as a measure of market risk. Conditional VaR (CVaR) is an alternative risk measure to the quantile, which overcomes the theoretical deficiencies of VaR. Therefore, the paper has simultaneously considered these two risk measure methods, and has carried on the comparison in the empirical analysis.Secondly, this paper uses the parameter method. The mothod usually supposes that financial sequence submits to normal distribution. However, the mass literatures indicate that financial sequence is not normal, but heavy tails and skew. Therefore this article introduces a kind of new asymmetrical Laplace distribution, whose structure is simpler than general asymmetrical Laplace distribution. It has some good nature and can reflect on these characters. This article discusses its properties and estimations of parameter at length. Finally, we use it to simulate the distribution of return rate in Chinese stock market. By statistical analysis, Fitting effect of asymmetric Laplace distribution is better than normal distribution and symmetric Laplace distribution.Finally, this paper presents the basic definition and nature of copula function and calculates investment profolio VaR by using Monte Carlo analogy procedure. The empirical analysis indicates that the Copula function can describe the financial sequence relevance well and has certain guiding sense to the financial risk's measure in the investment profolio aspect.