{"title":"广义Pearson分布在金融时间序列建模中的应用","authors":"S. Stavroyiannis","doi":"10.2139/ssrn.2308436","DOIUrl":null,"url":null,"abstract":"We elaborate on a new distributional scheme resulting from the generalised Pearson distribution with application to financial modelling. As case studies, we consider the major historical indices daily returns, DJIA, NASDAQ composite, FTSE100, CAC40, DAX and S%P500, as well as, high-frequency returns of the Euro/Japanese Yen foreign currency exchange rates. Using non-linear optimisation techniques, we compare the results of the maximum likelihood estimator of the new distribution to the results of the Pearson type-IV distribution. The main findings indicate that the new distribution improves the value of the estimator in all cases, with significant improvement below the 60-min sampling.","PeriodicalId":445453,"journal":{"name":"ERN: Other Econometric Modeling: International Financial Markets - Foreign Exchange (Topic)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the Generalized Pearson Distribution for Application in Financial Time Series Modeling\",\"authors\":\"S. Stavroyiannis\",\"doi\":\"10.2139/ssrn.2308436\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We elaborate on a new distributional scheme resulting from the generalised Pearson distribution with application to financial modelling. As case studies, we consider the major historical indices daily returns, DJIA, NASDAQ composite, FTSE100, CAC40, DAX and S%P500, as well as, high-frequency returns of the Euro/Japanese Yen foreign currency exchange rates. Using non-linear optimisation techniques, we compare the results of the maximum likelihood estimator of the new distribution to the results of the Pearson type-IV distribution. The main findings indicate that the new distribution improves the value of the estimator in all cases, with significant improvement below the 60-min sampling.\",\"PeriodicalId\":445453,\"journal\":{\"name\":\"ERN: Other Econometric Modeling: International Financial Markets - Foreign Exchange (Topic)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Other Econometric Modeling: International Financial Markets - Foreign Exchange (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2308436\",\"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 Econometric Modeling: International Financial Markets - Foreign Exchange (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2308436","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the Generalized Pearson Distribution for Application in Financial Time Series Modeling
We elaborate on a new distributional scheme resulting from the generalised Pearson distribution with application to financial modelling. As case studies, we consider the major historical indices daily returns, DJIA, NASDAQ composite, FTSE100, CAC40, DAX and S%P500, as well as, high-frequency returns of the Euro/Japanese Yen foreign currency exchange rates. Using non-linear optimisation techniques, we compare the results of the maximum likelihood estimator of the new distribution to the results of the Pearson type-IV distribution. The main findings indicate that the new distribution improves the value of the estimator in all cases, with significant improvement below the 60-min sampling.