作业代写：EVT工具的使用

作业代写：EVT工具的使用

EVT是一种统计工具,处理正常的值显示极端变化值位于值的概率分布。EVT估计极端风险的可能性,而VaR处理坐落在中间值。极值理论作为一种工具来分析金融问题了重要性在最近的过去(辛格,et al .,2011),因为研究表明,EVT赋予最准确的估计股票市场风险进行成功(豪氏威马,et al .,2001),(Gilli & K¨ellezi,2006)。EVT下,风险评估估计比任何极端的事件之前已经观察到(麦克尼尔&弗雷,2000)。短缺的极值TheoryEVT不是一个有效的工具,当估计渐近独立的系列的风险。换句话说,值是独立的,也同分布随机变量不能准确使用EVT分析。

作业代写：EVT工具的使用
如果EVT用于这样的价值观,会高估风险。高估的程度将直接比例值的随机性评估(Longin,2004)。因此,结果基于这样的系列EVT时不准确预测与事件相关联的风险。动荡的股市被认为是决定因素反映在投资组合的风险评估和管理。看看历史值表明,财务回报往往依赖,但连续un-correlated。在这种情况下,需要一个模型,该模型是有效的,正常的和极端的价值观是实现通过使用EVT,在结合VaR。模型测试值在不同股票市场同时使用历史和当前值。受欢迎指数用于本研究的目的是日经指数、富时,DAX指数和标准普尔。

作业代写：EVT工具的使用

EVT is a statistical tool that deals with the values that show extreme variations from the normal values that are located around the median of probability distribution. EVT estimates the possibilities of extreme risk, while VaR deals with values located around the median. Extreme Value Theory as a tool to analyse financial issues has gained importance in the recent past (Singh, et al., 2011), since studies showing that EVT gives the most accurate estimates of stock market risk have been conducted successfully (Huisman, et al., 2001), (Gilli & K¨ellezi, 2006). Under EVT, risk is assessed by estimating an event that is more extreme than any that has been previously observed (McNeil & Frey, 2000).Shortfalls of Extreme Value TheoryEVT is not an effective tool when estimating the risk of series that are asymptotically independent. In other words, values that are independent and also identically distributed or random variables cannot be accurately analysed using EVT.

作业代写：EVT工具的使用
If EVT were to be used for such values, the risk would be overestimated. The degree of overestimation would be directly proportionate with the randomness of the values being assessed (Longin, 2004). Therefore, the result based on such series when EVT is applied does not accurately predict the risk that is associated with the event.The volatile stock markets are seen to be determining factors that are reflected in the risk assessment and management of portfolios. A look at historical values show that financial returns tend to be dependent, but serially un-correlated. In this scenario, the need for a model which is effective for both normal and extreme values is fulfilled by using EVT and VaR in conjugation. The model is tested on values across various stock markets using both historical and current values. The popular indices used for the purpose of this study are Nikkei, FTSE, DAX and S&P500.