{"title":"使用随机网格进行深度校准","authors":"Fabio Baschetti, Giacomo Bormetti, Pietro Rossi","doi":"10.1080/14697688.2024.2332375","DOIUrl":null,"url":null,"abstract":"We propose a neural network-based approach to calibrating stochastic volatility models, which combines the pioneering grid approach by Horvath et al. [Deep learning volatility: A deep neural networ...","PeriodicalId":20747,"journal":{"name":"Quantitative Finance","volume":"41 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deep calibration with random grids\",\"authors\":\"Fabio Baschetti, Giacomo Bormetti, Pietro Rossi\",\"doi\":\"10.1080/14697688.2024.2332375\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a neural network-based approach to calibrating stochastic volatility models, which combines the pioneering grid approach by Horvath et al. [Deep learning volatility: A deep neural networ...\",\"PeriodicalId\":20747,\"journal\":{\"name\":\"Quantitative Finance\",\"volume\":\"41 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quantitative Finance\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1080/14697688.2024.2332375\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative Finance","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1080/14697688.2024.2332375","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
We propose a neural network-based approach to calibrating stochastic volatility models, which combines the pioneering grid approach by Horvath et al. [Deep learning volatility: A deep neural networ...
期刊介绍：
The frontiers of finance are shifting rapidly, driven in part by the increasing use of quantitative methods in the field. Quantitative Finance welcomes original research articles that reflect the dynamism of this area. The journal provides an interdisciplinary forum for presenting both theoretical and empirical approaches and offers rapid publication of original new work with high standards of quality. The readership is broad, embracing researchers and practitioners across a range of specialisms and within a variety of organizations. All articles should aim to be of interest to this broad readership.
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