{"title":"条件分位数自回归的条件波动估计","authors":"D. Mutunga, P. Mwita, B. Muema","doi":"10.12988/IJMA.2014.47210","DOIUrl":null,"url":null,"abstract":"This paper considers the problem of estimating conditional volatility function using conditional quantile autoregression function. We estimate the interquantile autoregression range and the conditional volatility function under known distributional assumptions. The conditional volatility function estimator is found to be theoretically consistent. A small simulation study ascertains that the Volatility Estimator is consistent. Mathematics Subject Classification: 62G05; 62M1","PeriodicalId":431531,"journal":{"name":"International Journal of Mathematical Analysis","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Conditional volatility estimation by conditional quantile autoregression\",\"authors\":\"D. Mutunga, P. Mwita, B. Muema\",\"doi\":\"10.12988/IJMA.2014.47210\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper considers the problem of estimating conditional volatility function using conditional quantile autoregression function. We estimate the interquantile autoregression range and the conditional volatility function under known distributional assumptions. The conditional volatility function estimator is found to be theoretically consistent. A small simulation study ascertains that the Volatility Estimator is consistent. Mathematics Subject Classification: 62G05; 62M1\",\"PeriodicalId\":431531,\"journal\":{\"name\":\"International Journal of Mathematical Analysis\",\"volume\":\"114 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Mathematical Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12988/IJMA.2014.47210\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Mathematical Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12988/IJMA.2014.47210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Conditional volatility estimation by conditional quantile autoregression
This paper considers the problem of estimating conditional volatility function using conditional quantile autoregression function. We estimate the interquantile autoregression range and the conditional volatility function under known distributional assumptions. The conditional volatility function estimator is found to be theoretically consistent. A small simulation study ascertains that the Volatility Estimator is consistent. Mathematics Subject Classification: 62G05; 62M1