{"title":"应用极端价值理论,以此为量化市场定价风险测试达克斯和MSCI欧洲过去的极端压力与相关性","authors":"M. Pohl","doi":"10.3790/KUK.44.2.243","DOIUrl":null,"url":null,"abstract":"The Extreme Value Theory is an approach designed with the objective to quantify risks which occur with a very low probability. The empirical application of the Extreme Value Theory in terms of the Peaks Over Threshold (POT)-Method to the index declines of the DAX and the MSCI Europe on 11.9.01, 21.1.08 and 16.10.08 in this paper shows that the quality of risk assessment highly depends on the underlying data source. As the analysis shows the resulting risk level during the considered days is clearly linked to the applied threshold. Nevertheless it is shown that the POT-Method beats the assumption of normal distribution and GARCH models with normally distributed and t-distributed innovations – especially after periods of high market volatility – concerning the goodness of risk quantification for the examined events.","PeriodicalId":280048,"journal":{"name":"Kredit Und Kapital","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Anwendung der Extremwerttheorie zur Quantifizierung von Marktpreisrisiken – Test der Relevanz anhand vergangener Extrembelastungen von DAX und MSCI Europe\",\"authors\":\"M. Pohl\",\"doi\":\"10.3790/KUK.44.2.243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Extreme Value Theory is an approach designed with the objective to quantify risks which occur with a very low probability. The empirical application of the Extreme Value Theory in terms of the Peaks Over Threshold (POT)-Method to the index declines of the DAX and the MSCI Europe on 11.9.01, 21.1.08 and 16.10.08 in this paper shows that the quality of risk assessment highly depends on the underlying data source. As the analysis shows the resulting risk level during the considered days is clearly linked to the applied threshold. Nevertheless it is shown that the POT-Method beats the assumption of normal distribution and GARCH models with normally distributed and t-distributed innovations – especially after periods of high market volatility – concerning the goodness of risk quantification for the examined events.\",\"PeriodicalId\":280048,\"journal\":{\"name\":\"Kredit Und Kapital\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Kredit Und Kapital\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3790/KUK.44.2.243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kredit Und Kapital","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3790/KUK.44.2.243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Anwendung der Extremwerttheorie zur Quantifizierung von Marktpreisrisiken – Test der Relevanz anhand vergangener Extrembelastungen von DAX und MSCI Europe
The Extreme Value Theory is an approach designed with the objective to quantify risks which occur with a very low probability. The empirical application of the Extreme Value Theory in terms of the Peaks Over Threshold (POT)-Method to the index declines of the DAX and the MSCI Europe on 11.9.01, 21.1.08 and 16.10.08 in this paper shows that the quality of risk assessment highly depends on the underlying data source. As the analysis shows the resulting risk level during the considered days is clearly linked to the applied threshold. Nevertheless it is shown that the POT-Method beats the assumption of normal distribution and GARCH models with normally distributed and t-distributed innovations – especially after periods of high market volatility – concerning the goodness of risk quantification for the examined events.