极值理论

金融市场风险的度量&基于极值理论和Copula的应用研究

The Application of Financial Market Risk Measurement Based on EVT and Copula

最后将VaR和极值理论结合起来，全面地，真实的认知开放经济中各涉外经济主体所面临的风险状况。

Combines VaR and EVT , perceives foreign invested economic main body in the open economics the conditions of foreign exchange risk finally .

气象参数极值理论频率曲线的Excel实现

Using Excel to Realize the Frequency Curve of the Meteorological Parameters Extremum Theory

基于极值理论的VaR计算方法研究

Study on the Computing Methods of VaR Based on Extreme Value Theory

基于Bayes估计与极值理论的VaR研究

Study on Value at Risk Based on Bayes Estimation and Extreme Value Theory

基于极值理论的风险价值（VaR）研究

Value - at-Risk Based on Extreme Value Theory

基于极值理论和Copula函数的条件VaR计算

Calculate the condition VaR by extreme value theory and Copula function

人民币汇率风险测度的实证研究&基于极值理论的VaR

Empirical Study of CNY Exchange Rate Risk : Using VaR Based on Extreme Value Theory

应用极值理论计算在险价值（VaR）&对恒生指数的实证分析

Calculating VaR with the Extreme Value Theory & An Empirical Analysis of Hang Seng Index

本文介绍了一种复合极值理论，并将其应用到VaR的计算上。

In this paper , compound extreme value theory is introduced and used to evaluate VaR.

在第三章对极值理论进行了介绍，并着重给出了极值理论的POT模型，说明了极值理论在实际使用中的优点和缺陷。

Chapter three introduce extreme value theory emphasizing on POT model and illuminate the advantages and disadvantages .

基于极值理论的我国股票市场流动性调整的VaR和ES研究

Research of Liquidity Adjusted VaR and ES in China Stock Market Based on Extreme Value Theory

基于极值理论和Copula的灾难风险建模研究

Study on synthetical models for catastrophe based on EVT-Copula method

极值理论（EVT）方法用于受险价值（VaR）计算的实证比较与分析

Empirical Analysis of Value-at-Risk Estimation Methods Using Extreme Value Theory

基于极值理论和Copula函数的中国基金市场投资组合VaR研究

The Research of Chinese Fund Market Based on Extreme Value Theory and Copula Function of Portfolio VaR

利用极值理论和方法，建立了极端日收益率数据的广义Pareto分布模型。

Generalized Pareto distributions for extreme daily return are modeled by using extreme value theory and methods .

本文应用统计学中的极值理论于VaR的计算，这是一种崭新的方法。

This paper applies the extreme value theory on VaR calculation , which is a method emerging recently in risk management .

首先对极值理论和柯尔莫诺夫-斯米尔诺夫检验进行介绍，然后将极值理论用到MIMO雷达的目标检测中。

After introducing the extreme value theory and kolmogorov-smirnov statistical test , we use this theory to detect target in MIMO radar .

相对而言，极值理论结合CARR模型所估计的价格变化较为合理。

In contrast , extreme value theory combined CARR model is more reasonable estimate of price changes .

将遗传算法求复杂函数极值理论与三维数字仿真技术相结合，采用VC++编程语言开发馈源n塔支撑最优化系统。

Then , combining with a genetic algorithm of extremum for complicated functions and a digital three dimension simulation technique , an optimization system for the feed support system is programmed by VC + + language .

采用适当的统计方法来估计广义Pareto的分布参数，对于计算基于极值理论的风险值（VaR）具有重要的理论和现实意义。

It is very important to adopt appropriate statistical methods for estimating the parameters of Pareto distribution before calculating VaR based on the extreme value theory .

论文研究了如何将极值理论与VAR计算方法相结合进行应用以提高计量精度，并对其作了实证分析。

The paper studied how to apply the theory of extreme value to the VAR method to rise the degree of estimating precise , and made empirical analysis .

本文正是应用极值理论和下界VaR方法对国内的股票市场和期货市场的风险进行了实证研究，并针对国内市场的风险特征提出了风险管理的建议。

In this paper , the VaR bound method and EVT method are applied to study the risk of domestic stock market and the risk of domestic future market .

用GARCH滤波的历史模拟与极值理论的混合方法也可得到在各个置信水平都有效而准确的VaR估计。

Or use the GARCH processed historical simulation and theory and mixed methods can also get the effective and accurate VaR estimation at various confidence levels .

基于极值理论和Bootstrap方法的E-VaR研究和实证分析

Extreme VaR and its Empirical Analysis Based on EVT and Bootstrap Method

主要使用极值理论中的两种方法对上证指数进行VaR估计，并且进行后验测试以评价该方法的可靠性。

Making use of the two estimation methods of EVT the paper predicts the VaR of Shanghai Securities Composite Index . Then the reliability of the methods has been evaluated by back testing .

在金融领域讨论了重尾场合下金融市场的风险度量，认为传统方法在估计VaR值时存在缺陷，而运用极值理论能更好的估计VaR。

In the field of finance , we discuss the defect of traditional method in estimating of VaR , and regard extreme value theory as a better method to estimate VaR under heavy-tailed occasion .

考虑金融时间序列的厚尾特性，讨论了应用极值理论中的广义Pareto分布模型度量风险的问题。

In view that the fat tail of financial time series , we will discuss how to measure risk with GPD ( general Pareto distribution ) models in extreme value theory .

表明市场风险导致的损失分布确实具有厚尾分布的特点，因而利用极值理论与VAR计算方法相结合来计量金融银行业的重大损失具有较好的效果。

Showing that the lose distribution rising from market risk have the traits of pinnacle and thick tail , so applying the theory of extreme value to the VAR method is better than the ordinary VAR.

初步研究了用Bayes估计计算金融风险值VaR，同时阐明了运用极值理论方法在Bayes估计下的金融风险值计算。

The paper considers how to calculate VaR ( Value at Risk ) by using Bayes estimation , and analyze to use method of Extreme Value Theory calculate VaR when we use Bayes estimation .