| 1. | How could we talk about a normal distribution of extreme events
极端的事件怎麽有办法谈论常态分布？ |
| 2. | In other words , investors are becoming less worried about extreme events
换句话说，投资者对极端事件变得不那么担心了。 |
| 3. | Illustrate : you are invited to take part in extreme events , in return , the victory finished three rounds , will be a huge bonus
游戏介绍：你被邀请参加这项极端的赛事，作为回报，胜利过完三个回合的话，会得到丰厚的奖金。 |
| 4. | Any aggregation or segmentation , cross platform . normal non - normal market distributions for everyday and extreme events , including scenario analysis
基于整合分割平台，为每天和极端事件提供正态和非正态的市场分析，如情境分析。 |
| 5. | The risks are especially great given that extreme events seem to occur more often than standard statistical theory suggests they should
这是十分危险的? ?无异于虎口拔牙，尤其是在极端事件的出现频率远高于标准统计理论所推断的时候。 |
| 6. | Climate change will produce new challenges for countries to face , including increased occurrence of extreme events , flooding , and new patterns of disease
气候变化将为各国带来新的挑战，如极端现象更加频繁、洪水泛滥以及新的疾病等。 |
| 7. | Public is becoming increasingly concerned about the safety of the structure which could be subjected to severe levels of structural motions induced by extreme event
但是，许多建筑结构都处在地震活动较活跃的地带，随之而来的安全问题逐渐引起人们的关注。 |
| 8. | " this means this is potentially an extreme event in terms of hurricane generation so in that sense it is no surprise that we are seeing these intense hurricanes
从飓风的产生这一角度来看，这种情况的出现或许意味着我们正在面临一个极为严峻的局面，如此说来，前面那几场强飓风的到来就并不令人感到意外了。 |
| 9. | Because evt mainly studies extreme value and models the tail of distribution financial return , it can effectively forecasts and guards against the financial risk on the condition of lacking of sample data . more and more people recognize the great potentials of evt dealing with the risk of extreme event . especially evt can be used in application to value at risk due to modeling the tail of distribution
极值理论主要以极值为研究对象，它注重模拟收益分布的尾部，比较有效地解决了在缺少样本的客观条件下如何预测和防范金融风险的问题，因此，越来越多的人认识到极值理论在极端事件风险管理中的巨大潜力，特别指出的是极值理论是一种模拟收益分布尾部的理论，所以可以应用于风险价值的测量。 |
| 10. | So it can avoid risk of model and computer rightly the var of extreme event . this article presents the theory of extreme value and character of tail of distribution and gives the example of var with index of shanghai stock market by evt , then compares the var result of different computation methods and concludes that traditional var method is static state model and var with evt is dynamic conservative model and has the ability of forecasting risk out of sample comparing to historical simulation method
本文系统地阐述了极值理论和极值分布特征，以上证指数为例，将极值理论应用于风险价值的计算，并将应用结果与传统var方法计算的结果进行了比较分析，最后得出结论：传统的var计算模型是静态的模型，应用极值理论计算var的模型是动态的、相对保守的模型；与历史模拟法相比较，极值理论具有超越样本的预测能力。 |
