{"title":"用于金融应用的高效黄土","authors":"K. Haven","doi":"10.2139/ssrn.3949349","DOIUrl":null,"url":null,"abstract":"An improved efficiency version of the LOESS algorithm is proposed that is applicable to the Monte Carlo pricing tasks common in financial engineering. A self-contained overview of the LOESS algorithm is presented followed by the suggested efficiency modifications and a discussion of strategies for variable selection that can reduce dimensionality for further improvements in efficiency as well as stability. Some numerical results are shown as a demonstration of the suggested approach.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficient LOESS For Financial Applications\",\"authors\":\"K. Haven\",\"doi\":\"10.2139/ssrn.3949349\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An improved efficiency version of the LOESS algorithm is proposed that is applicable to the Monte Carlo pricing tasks common in financial engineering. A self-contained overview of the LOESS algorithm is presented followed by the suggested efficiency modifications and a discussion of strategies for variable selection that can reduce dimensionality for further improvements in efficiency as well as stability. Some numerical results are shown as a demonstration of the suggested approach.\",\"PeriodicalId\":209192,\"journal\":{\"name\":\"ERN: Asset Pricing Models (Topic)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Asset Pricing Models (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3949349\",\"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: Asset Pricing Models (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3949349","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An improved efficiency version of the LOESS algorithm is proposed that is applicable to the Monte Carlo pricing tasks common in financial engineering. A self-contained overview of the LOESS algorithm is presented followed by the suggested efficiency modifications and a discussion of strategies for variable selection that can reduce dimensionality for further improvements in efficiency as well as stability. Some numerical results are shown as a demonstration of the suggested approach.
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