{"title":"基于BSM期权定价的上证50指数etf趋势时机策略蒙特卡罗模拟","authors":"Xiaoping Ren, Ziqiang Wang, Hongyu An","doi":"10.1145/3512676.3512688","DOIUrl":null,"url":null,"abstract":"This paper uses the SSE 50ETF trading data to establish a quantitative timing trading strategy. Based on the SSE 300ETF as the comparison base, the Monte-Carlo simulation and BSM model is used to price the SSE 50ETF call option at 3850 in June 2021 and simulate the volatility path of the 50ETF index.","PeriodicalId":281300,"journal":{"name":"Proceedings of the 2022 5th International Conference on Computers in Management and Business","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Monte Carlo simulation of SSE 50ETF with trend timing strategy based on BSM option pricing\",\"authors\":\"Xiaoping Ren, Ziqiang Wang, Hongyu An\",\"doi\":\"10.1145/3512676.3512688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper uses the SSE 50ETF trading data to establish a quantitative timing trading strategy. Based on the SSE 300ETF as the comparison base, the Monte-Carlo simulation and BSM model is used to price the SSE 50ETF call option at 3850 in June 2021 and simulate the volatility path of the 50ETF index.\",\"PeriodicalId\":281300,\"journal\":{\"name\":\"Proceedings of the 2022 5th International Conference on Computers in Management and Business\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2022 5th International Conference on Computers in Management and Business\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3512676.3512688\",\"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 of the 2022 5th International Conference on Computers in Management and Business","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3512676.3512688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Monte Carlo simulation of SSE 50ETF with trend timing strategy based on BSM option pricing
This paper uses the SSE 50ETF trading data to establish a quantitative timing trading strategy. Based on the SSE 300ETF as the comparison base, the Monte-Carlo simulation and BSM model is used to price the SSE 50ETF call option at 3850 in June 2021 and simulate the volatility path of the 50ETF index.