Malliavin衍生证券衍生品

Tom P. Davis
{"title":"Malliavin衍生证券衍生品","authors":"Tom P. Davis","doi":"10.3905/jod.2022.30.2.065","DOIUrl":null,"url":null,"abstract":"The Malliavin calculus has been used successfully to derive efficient formulas for delta and gamma. This article extends these results to all higher-order spatial derivatives with respect to the underlying asset for arbitrary payoffs in both the Black-Scholes (Black and Scholes 1973) (lognormal) and Bachelier (normal) models. The former reproduces a well-known result from Peter Carr (2000), whereas the latter extends this work to the normal case.","PeriodicalId":34223,"journal":{"name":"Jurnal Derivat","volume":"30 1","pages":"65 - 73"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Malliavin Derivatives of Derivative Securities\",\"authors\":\"Tom P. Davis\",\"doi\":\"10.3905/jod.2022.30.2.065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Malliavin calculus has been used successfully to derive efficient formulas for delta and gamma. This article extends these results to all higher-order spatial derivatives with respect to the underlying asset for arbitrary payoffs in both the Black-Scholes (Black and Scholes 1973) (lognormal) and Bachelier (normal) models. The former reproduces a well-known result from Peter Carr (2000), whereas the latter extends this work to the normal case.\",\"PeriodicalId\":34223,\"journal\":{\"name\":\"Jurnal Derivat\",\"volume\":\"30 1\",\"pages\":\"65 - 73\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Derivat\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3905/jod.2022.30.2.065\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Derivat","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3905/jod.2022.30.2.065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

Malliavin微积分已被成功地用于推导有效的delta和gamma公式。本文将这些结果推广到Black-Scholes(Black and Scholes 1973)(lognormal)和Bachelier(normal)模型中任意收益的所有关于基础资产的高阶空间导数。前者再现了彼得·卡尔(2000)的一个著名结果,而后者将这项工作扩展到了正常情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Malliavin Derivatives of Derivative Securities
The Malliavin calculus has been used successfully to derive efficient formulas for delta and gamma. This article extends these results to all higher-order spatial derivatives with respect to the underlying asset for arbitrary payoffs in both the Black-Scholes (Black and Scholes 1973) (lognormal) and Bachelier (normal) models. The former reproduces a well-known result from Peter Carr (2000), whereas the latter extends this work to the normal case.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
11
审稿时长
24 weeks
期刊最新文献
Lattice Approach for Option Pricing under Lévy Processes Caplets/Floorlets with Backward-Looking Risk-Free Rates under the One- and Two-Factor Hull-White Models Editor’s Letter Vol, Skew, and Smile Trading Option Valuation with Nonmonotonic Pricing Kernel and Embedded Volatility Component Premiums
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1