{"title":"期权定价模型与历史市场数据的大规模比较","authors":"Kim Mills, Michael Vinson, Gang Cheng","doi":"10.1109/FMPC.1992.234885","DOIUrl":null,"url":null,"abstract":"A set of stock option pricing models is implemented on the Connection Machine-2 and the DECmpp-12000 to compare model prices and historical market data. Improved models which incorporate stochastic volatility with American call generally have smaller pricing errors than simpler models which are based on constant volatility and European call. In a refinement of the comparison between model and market prices, a figure of merit based on the bid/ask spread in the market and the use of optimization techniques for model parameter estimation, are evaluated. Optimization appears to hold great promise for improving the accuracy of existing pricing models, especially for stocks which are difficult to price with conventional models.<<ETX>>","PeriodicalId":117789,"journal":{"name":"[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1992-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"A large scale comparison of option pricing models with historical market data\",\"authors\":\"Kim Mills, Michael Vinson, Gang Cheng\",\"doi\":\"10.1109/FMPC.1992.234885\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A set of stock option pricing models is implemented on the Connection Machine-2 and the DECmpp-12000 to compare model prices and historical market data. Improved models which incorporate stochastic volatility with American call generally have smaller pricing errors than simpler models which are based on constant volatility and European call. In a refinement of the comparison between model and market prices, a figure of merit based on the bid/ask spread in the market and the use of optimization techniques for model parameter estimation, are evaluated. Optimization appears to hold great promise for improving the accuracy of existing pricing models, especially for stocks which are difficult to price with conventional models.<<ETX>>\",\"PeriodicalId\":117789,\"journal\":{\"name\":\"[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FMPC.1992.234885\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FMPC.1992.234885","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A large scale comparison of option pricing models with historical market data
A set of stock option pricing models is implemented on the Connection Machine-2 and the DECmpp-12000 to compare model prices and historical market data. Improved models which incorporate stochastic volatility with American call generally have smaller pricing errors than simpler models which are based on constant volatility and European call. In a refinement of the comparison between model and market prices, a figure of merit based on the bid/ask spread in the market and the use of optimization techniques for model parameter estimation, are evaluated. Optimization appears to hold great promise for improving the accuracy of existing pricing models, especially for stocks which are difficult to price with conventional models.<>