{"title":"用极值理论建模共同基金赎回风险","authors":"Sascha Desmettre, M. Deege","doi":"10.21314/JOR.2016.336","DOIUrl":null,"url":null,"abstract":"We show how redemption risks of mutual funds can be modeled using the peaks-over-threshold approach from extreme value theory. The resulting risk measure liquidity-at-risk is adapted to cover issues arising when fund redemption data from the real world is used, and we give guidelines for what should be considered in practice. We also provide an automated and easily applicable procedure for determining the threshold parameter of a generalized Pareto distribution by means of a given data set. Moreover, we supplement our findings with a thorough backtesting analysis.","PeriodicalId":46697,"journal":{"name":"Journal of Risk","volume":"1 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Modeling Redemption Risks of Mutual Funds Using Extreme Value Theory\",\"authors\":\"Sascha Desmettre, M. Deege\",\"doi\":\"10.21314/JOR.2016.336\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We show how redemption risks of mutual funds can be modeled using the peaks-over-threshold approach from extreme value theory. The resulting risk measure liquidity-at-risk is adapted to cover issues arising when fund redemption data from the real world is used, and we give guidelines for what should be considered in practice. We also provide an automated and easily applicable procedure for determining the threshold parameter of a generalized Pareto distribution by means of a given data set. Moreover, we supplement our findings with a thorough backtesting analysis.\",\"PeriodicalId\":46697,\"journal\":{\"name\":\"Journal of Risk\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2016-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Risk\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.21314/JOR.2016.336\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Risk","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.21314/JOR.2016.336","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Modeling Redemption Risks of Mutual Funds Using Extreme Value Theory
We show how redemption risks of mutual funds can be modeled using the peaks-over-threshold approach from extreme value theory. The resulting risk measure liquidity-at-risk is adapted to cover issues arising when fund redemption data from the real world is used, and we give guidelines for what should be considered in practice. We also provide an automated and easily applicable procedure for determining the threshold parameter of a generalized Pareto distribution by means of a given data set. Moreover, we supplement our findings with a thorough backtesting analysis.
期刊介绍:
This international peer-reviewed journal publishes a broad range of original research papers which aim to further develop understanding of financial risk management. As the only publication devoted exclusively to theoretical and empirical studies in financial risk management, The Journal of Risk promotes far-reaching research on the latest innovations in this field, with particular focus on the measurement, management and analysis of financial risk. The Journal of Risk is particularly interested in papers on the following topics: Risk management regulations and their implications, Risk capital allocation and risk budgeting, Efficient evaluation of risk measures under increasingly complex and realistic model assumptions, Impact of risk measurement on portfolio allocation, Theoretical development of alternative risk measures, Hedging (linear and non-linear) under alternative risk measures, Financial market model risk, Estimation of volatility and unanticipated jumps, Capital allocation.