{"title":"量子电路学习计算期权价格及其敏感性","authors":"T. Sakuma","doi":"10.2139/ssrn.3922040","DOIUrl":null,"url":null,"abstract":"Quantum circuit learning is applied to computing option prices and their sensitivities. The advantage of this method is that a suitable choice of quantum circuit architecture makes it possible to compute the sensitivities analytically by applying parameter-shift rules. We expect our numerical result to pave the way for using quantum machine learning for option pricing.","PeriodicalId":306152,"journal":{"name":"Risk Management eJournal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Quantum Circuit Learning to Compute Option Prices and Their Sensitivities\",\"authors\":\"T. Sakuma\",\"doi\":\"10.2139/ssrn.3922040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantum circuit learning is applied to computing option prices and their sensitivities. The advantage of this method is that a suitable choice of quantum circuit architecture makes it possible to compute the sensitivities analytically by applying parameter-shift rules. We expect our numerical result to pave the way for using quantum machine learning for option pricing.\",\"PeriodicalId\":306152,\"journal\":{\"name\":\"Risk Management eJournal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Risk Management eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3922040\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Risk Management eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3922040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantum Circuit Learning to Compute Option Prices and Their Sensitivities
Quantum circuit learning is applied to computing option prices and their sensitivities. The advantage of this method is that a suitable choice of quantum circuit architecture makes it possible to compute the sensitivities analytically by applying parameter-shift rules. We expect our numerical result to pave the way for using quantum machine learning for option pricing.
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