{"title":"运用奥曼-塞拉诺风险指数","authors":"Doron Nisani, Amit Shelef, OrrOSON David","doi":"10.1108/raf-04-2022-0134","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe purpose of this study is to estimate the convergence order of the Aumann–Serrano Riskiness Index.\n\n\nDesign/methodology/approach\nThis study uses the equivalent relation between the Aumann–Serrano Riskiness Index and the moment generating function and aggregately compares between each two statistical moments for statistical significance. Thus, this study enables to find the convergence order of the index to its stable value.\n\n\nFindings\nThis study finds that the first-best estimation of the Aumann–Serrano Riskiness Index is reached in no less than its seventh statistical moment. However, this study also finds that its second-best approximation could be achieved with its second statistical moment.\n\n\nResearch limitations/implications\nThe implications of this research support the standard deviation as a statistically sufficient approximation of Aumann–Serrano Riskiness Index, thus strengthening the CAPM methodology for asset pricing in the financial markets.\n\n\nOriginality/value\nThis research sheds a new light, both in theory and in practice, on understanding of the risk’s structure, as it may improve accuracy of asset pricing.\n","PeriodicalId":21152,"journal":{"name":"Review of Accounting and Finance","volume":" ","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Putting the Aumann–Serrano Riskiness Index to work\",\"authors\":\"Doron Nisani, Amit Shelef, OrrOSON David\",\"doi\":\"10.1108/raf-04-2022-0134\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThe purpose of this study is to estimate the convergence order of the Aumann–Serrano Riskiness Index.\\n\\n\\nDesign/methodology/approach\\nThis study uses the equivalent relation between the Aumann–Serrano Riskiness Index and the moment generating function and aggregately compares between each two statistical moments for statistical significance. Thus, this study enables to find the convergence order of the index to its stable value.\\n\\n\\nFindings\\nThis study finds that the first-best estimation of the Aumann–Serrano Riskiness Index is reached in no less than its seventh statistical moment. However, this study also finds that its second-best approximation could be achieved with its second statistical moment.\\n\\n\\nResearch limitations/implications\\nThe implications of this research support the standard deviation as a statistically sufficient approximation of Aumann–Serrano Riskiness Index, thus strengthening the CAPM methodology for asset pricing in the financial markets.\\n\\n\\nOriginality/value\\nThis research sheds a new light, both in theory and in practice, on understanding of the risk’s structure, as it may improve accuracy of asset pricing.\\n\",\"PeriodicalId\":21152,\"journal\":{\"name\":\"Review of Accounting and Finance\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2023-01-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Review of Accounting and Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/raf-04-2022-0134\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Accounting and Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/raf-04-2022-0134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Putting the Aumann–Serrano Riskiness Index to work
Purpose
The purpose of this study is to estimate the convergence order of the Aumann–Serrano Riskiness Index.
Design/methodology/approach
This study uses the equivalent relation between the Aumann–Serrano Riskiness Index and the moment generating function and aggregately compares between each two statistical moments for statistical significance. Thus, this study enables to find the convergence order of the index to its stable value.
Findings
This study finds that the first-best estimation of the Aumann–Serrano Riskiness Index is reached in no less than its seventh statistical moment. However, this study also finds that its second-best approximation could be achieved with its second statistical moment.
Research limitations/implications
The implications of this research support the standard deviation as a statistically sufficient approximation of Aumann–Serrano Riskiness Index, thus strengthening the CAPM methodology for asset pricing in the financial markets.
Originality/value
This research sheds a new light, both in theory and in practice, on understanding of the risk’s structure, as it may improve accuracy of asset pricing.