{"title":"(非)参数回归:局部随机波动模型的应用","authors":"P. Henry-Labordère","doi":"10.2139/ssrn.3374875","DOIUrl":null,"url":null,"abstract":"In this short paper, we review various (non)-parametric regression methods, mainly k-nearest neighbors, Nadaraya-Watson, LP(p)-estimators, spline regressor and random forest. They are then compared when calibrating local stochastic volatility models using the particle method.","PeriodicalId":11744,"journal":{"name":"ERN: Nonparametric Methods (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"(Non)-Parametric Regressions: Applications to Local Stochastic Volatility Models\",\"authors\":\"P. Henry-Labordère\",\"doi\":\"10.2139/ssrn.3374875\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this short paper, we review various (non)-parametric regression methods, mainly k-nearest neighbors, Nadaraya-Watson, LP(p)-estimators, spline regressor and random forest. They are then compared when calibrating local stochastic volatility models using the particle method.\",\"PeriodicalId\":11744,\"journal\":{\"name\":\"ERN: Nonparametric Methods (Topic)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Nonparametric Methods (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3374875\",\"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: Nonparametric Methods (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3374875","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
(Non)-Parametric Regressions: Applications to Local Stochastic Volatility Models
In this short paper, we review various (non)-parametric regression methods, mainly k-nearest neighbors, Nadaraya-Watson, LP(p)-estimators, spline regressor and random forest. They are then compared when calibrating local stochastic volatility models using the particle method.
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