{"title":"对数正态收益下两个独立KS Sharpe比率差的推断","authors":"J. Qi, M. Rekkas, A. Wong","doi":"10.1155/2020/6751574","DOIUrl":null,"url":null,"abstract":"<jats:p>A higher-order likelihood-based asymptotic method to obtain inference for the difference between two KS Sharpe ratios when gross returns of an investment are assumed to be lognormally distributed is proposed. Theoretically, our proposed method has <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\">\n <mi>O</mi>\n <mfenced open=\"(\" close=\")\" separators=\"|\">\n <mrow>\n <msup>\n <mrow>\n <mi>n</mi>\n </mrow>\n <mrow>\n <mrow>\n <mrow>\n <mo>−</mo>\n <mn>3</mn>\n </mrow>\n <mo>/</mo>\n <mn>2</mn>\n </mrow>\n </mrow>\n </msup>\n </mrow>\n </mfenced>\n </math>\n </jats:inline-formula> distributional accuracy, whereas conventional methods for inference have <jats:inline-formula>\n <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\">\n <mi>O</mi>\n <mfenced open=\"(\" close=\")\" separators=\"|\">\n <mrow>\n <msup>\n <mrow>\n <mi>n</mi>\n </mrow>\n <mrow>\n <mrow>\n <mrow>\n <mo>−</mo>\n <mn>1</mn>\n </mrow>\n <mo>/</mo>\n <mn>2</mn>\n </mrow>\n </mrow>\n </msup>\n </mrow>\n </mfenced>\n </math>\n </jats:inline-formula> distributional accuracy. Using an example, we show how discordant confidence interval results can be depending on the methodology used. We are able to demonstrate the accuracy of our proposed method through simulation studies.</jats:p>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2020-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2020/6751574","citationCount":"0","resultStr":"{\"title\":\"Inference for the Difference of Two Independent KS Sharpe Ratios under Lognormal Returns\",\"authors\":\"J. Qi, M. Rekkas, A. Wong\",\"doi\":\"10.1155/2020/6751574\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<jats:p>A higher-order likelihood-based asymptotic method to obtain inference for the difference between two KS Sharpe ratios when gross returns of an investment are assumed to be lognormally distributed is proposed. Theoretically, our proposed method has <jats:inline-formula>\\n <math xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\" id=\\\"M1\\\">\\n <mi>O</mi>\\n <mfenced open=\\\"(\\\" close=\\\")\\\" separators=\\\"|\\\">\\n <mrow>\\n <msup>\\n <mrow>\\n <mi>n</mi>\\n </mrow>\\n <mrow>\\n <mrow>\\n <mrow>\\n <mo>−</mo>\\n <mn>3</mn>\\n </mrow>\\n <mo>/</mo>\\n <mn>2</mn>\\n </mrow>\\n </mrow>\\n </msup>\\n </mrow>\\n </mfenced>\\n </math>\\n </jats:inline-formula> distributional accuracy, whereas conventional methods for inference have <jats:inline-formula>\\n <math xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\" id=\\\"M2\\\">\\n <mi>O</mi>\\n <mfenced open=\\\"(\\\" close=\\\")\\\" separators=\\\"|\\\">\\n <mrow>\\n <msup>\\n <mrow>\\n <mi>n</mi>\\n </mrow>\\n <mrow>\\n <mrow>\\n <mrow>\\n <mo>−</mo>\\n <mn>1</mn>\\n </mrow>\\n <mo>/</mo>\\n <mn>2</mn>\\n </mrow>\\n </mrow>\\n </msup>\\n </mrow>\\n </mfenced>\\n </math>\\n </jats:inline-formula> distributional accuracy. Using an example, we show how discordant confidence interval results can be depending on the methodology used. We are able to demonstrate the accuracy of our proposed method through simulation studies.</jats:p>\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2020-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1155/2020/6751574\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/2020/6751574\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2020/6751574","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Inference for the Difference of Two Independent KS Sharpe Ratios under Lognormal Returns
A higher-order likelihood-based asymptotic method to obtain inference for the difference between two KS Sharpe ratios when gross returns of an investment are assumed to be lognormally distributed is proposed. Theoretically, our proposed method has distributional accuracy, whereas conventional methods for inference have distributional accuracy. Using an example, we show how discordant confidence interval results can be depending on the methodology used. We are able to demonstrate the accuracy of our proposed method through simulation studies.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.