{"title":"多个夏普比率相等性的检验","authors":"J. Wright, S. Yam, Siu Pang Yung","doi":"10.21314/JOR.2014.289","DOIUrl":null,"url":null,"abstract":"This paper provides a test for the equality of multiple Sharpe ratios. First we extend the multivariate Sharpe ratio statistic of Leung and Wong for the case when excess returns are independently and identically distributed. We then provide a test that holds under the much more general assumption that the excess returns are stationary and ergodic, making use of the generalized method of moments and heteroscedasticity and autocorrelation consistent estimation of covariance matrixes. We repeat Leung and Wong’s testing for equality of the Sharpe ratios f 18 iShares using our new tests and conclude that the hypothesis of equality cannot be rejected at the 1% level.","PeriodicalId":365755,"journal":{"name":"ERN: Other Econometrics: Mathematical Methods & Programming (Topic)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"A Test for the Equality of Multiple Sharpe Ratios\",\"authors\":\"J. Wright, S. Yam, Siu Pang Yung\",\"doi\":\"10.21314/JOR.2014.289\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper provides a test for the equality of multiple Sharpe ratios. First we extend the multivariate Sharpe ratio statistic of Leung and Wong for the case when excess returns are independently and identically distributed. We then provide a test that holds under the much more general assumption that the excess returns are stationary and ergodic, making use of the generalized method of moments and heteroscedasticity and autocorrelation consistent estimation of covariance matrixes. We repeat Leung and Wong’s testing for equality of the Sharpe ratios f 18 iShares using our new tests and conclude that the hypothesis of equality cannot be rejected at the 1% level.\",\"PeriodicalId\":365755,\"journal\":{\"name\":\"ERN: Other Econometrics: Mathematical Methods & Programming (Topic)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Other Econometrics: Mathematical Methods & Programming (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21314/JOR.2014.289\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Other Econometrics: Mathematical Methods & Programming (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21314/JOR.2014.289","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper provides a test for the equality of multiple Sharpe ratios. First we extend the multivariate Sharpe ratio statistic of Leung and Wong for the case when excess returns are independently and identically distributed. We then provide a test that holds under the much more general assumption that the excess returns are stationary and ergodic, making use of the generalized method of moments and heteroscedasticity and autocorrelation consistent estimation of covariance matrixes. We repeat Leung and Wong’s testing for equality of the Sharpe ratios f 18 iShares using our new tests and conclude that the hypothesis of equality cannot be rejected at the 1% level.