Fitting Local Volatility最新文献

{"title":"FRONT MATTER","authors":"","doi":"10.1142/9789811212772_fmatter","DOIUrl":"https://doi.org/10.1142/9789811212772_fmatter","url":null,"abstract":"","PeriodicalId":299787,"journal":{"name":"Fitting Local Volatility","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127153533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BACK MATTER","authors":"","doi":"10.1142/9789811212772_bmatter","DOIUrl":"https://doi.org/10.1142/9789811212772_bmatter","url":null,"abstract":"","PeriodicalId":299787,"journal":{"name":"Fitting Local Volatility","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131460845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regression-based Methods","authors":"A. Itkin","doi":"10.1142/9789811212772_0004","DOIUrl":"https://doi.org/10.1142/9789811212772_0004","url":null,"abstract":"In this chapter we describe the second and, perhaps, the most popular approach to building the local volatility surface by regressions. Regression-based methods include both parametric and non-parametric fits. Usually, all these methods deal with construction of the implied volatility surface while the local volatility can be found afterwards by using Eq.(3.2) or any its flavor.","PeriodicalId":299787,"journal":{"name":"Fitting Local Volatility","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131841742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geometric Local Variance Gamma Model","authors":"P. Carr, A. Itkin","doi":"10.3905/jod.2019.1.084","DOIUrl":"https://doi.org/10.3905/jod.2019.1.084","url":null,"abstract":"This article describes another extension of the local variance gamma model originally proposed by Carr in 2008 and then further elaborated by Carr and Nadtochiy in 2017 and Carr and Itkin in 2018. As compared with the latest version of the model developed by Carr and Itkin and called the “expanded local variance gamma” (ELVG) model, two innovations are provided in this article. First, in all previous articles the model was constructed on the basis of a gamma time-changed arithmetic Brownian motion: with no drift in Carr and Nadtochiy, with drift in Carr and Itkin, and with the local variance a function of the spot level only. In contrast, this article develops a geometric version of this model with drift. Second, in Carr and Nadtochiy the model was calibrated to option smiles assuming that the local variance is a piecewise constant function of strike, while in Carr and Itkin the local variance was assumed to be a piecewise linear function of strike. In this article, the authors consider three piecewise linear models: the local variance as a function of strike, the local variance as a function of log-strike, and the local volatility as a function of strike (so, the local variance is a piecewise quadratic function of strike). The authors show that for all these new constructions, it is still possible to derive an ordinary differential equation for the option price, which plays the role of Dupire’s equation for the standard local volatility model, and moreover, it can be solved in closed form. Finally, similar to in Carr and Itkin, the authors show that given multiple smiles the whole local variance/volatility surface can be recovered without requiring solving any optimization problem. Instead, it can be done term-by-term by solving a system of nonlinear algebraic equations for each maturity, which is a significantly faster process. TOPICS: Derivatives, statistical methods, options Key Findings • An extension of the Local Variance Gamma model is proposed on the basis of the Geometric Brownian motion with drift. • Three piecewise linear models: the local variance as a function of strike, the local variance as function of log-strike, and the local volatility as a function of strike (so, the local variance is a piecewise quadratic function of strike) are considered. • For all these new constructions an ODE is derived which replaces the Dupire equation and can be solved in closed form.","PeriodicalId":299787,"journal":{"name":"Fitting Local Volatility","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126300058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}