{"title":"金融时间序列分析的MATLAB实现","authors":"Xinyuan Zheng","doi":"10.20849/abr.v4i3.687","DOIUrl":null,"url":null,"abstract":"This report contains two parts. For part A, performing a Principle Components Analysis (PCA) and analyzing the drivers. Then, carrying out factor analyses and comparing them. For part B, employing 5 different quantitative models to forecast and generate moving origin horizon one forecasts of both return and volatility. Then, figuring out the optimal weights for the portfolio and assigning the optimal portfolio. Finally, comparing the returns and risk measure from all portfolio and models.","PeriodicalId":37159,"journal":{"name":"Asian Journal of Business Research","volume":"82 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Financial Time Series Analysis by Using MATLAB\",\"authors\":\"Xinyuan Zheng\",\"doi\":\"10.20849/abr.v4i3.687\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This report contains two parts. For part A, performing a Principle Components Analysis (PCA) and analyzing the drivers. Then, carrying out factor analyses and comparing them. For part B, employing 5 different quantitative models to forecast and generate moving origin horizon one forecasts of both return and volatility. Then, figuring out the optimal weights for the portfolio and assigning the optimal portfolio. Finally, comparing the returns and risk measure from all portfolio and models.\",\"PeriodicalId\":37159,\"journal\":{\"name\":\"Asian Journal of Business Research\",\"volume\":\"82 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Journal of Business Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20849/abr.v4i3.687\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Journal of Business Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20849/abr.v4i3.687","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Social Sciences","Score":null,"Total":0}
This report contains two parts. For part A, performing a Principle Components Analysis (PCA) and analyzing the drivers. Then, carrying out factor analyses and comparing them. For part B, employing 5 different quantitative models to forecast and generate moving origin horizon one forecasts of both return and volatility. Then, figuring out the optimal weights for the portfolio and assigning the optimal portfolio. Finally, comparing the returns and risk measure from all portfolio and models.
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