{"title":"马尔可夫到达过程的动态多模式组合优化策略","authors":"Jin Fang, Mo Xiaoyun","doi":"10.1109/ICRIS.2017.42","DOIUrl":null,"url":null,"abstract":"Aiming at the characteristics of multi - mode portfolio, a dynamic multi - mode portfolio optimization strategy model is established based on Markovian arrival process analysis method, which provides a decision - making method for portfolio management. The model presents the behavior hypothesis of Markovian arrival process, and improves the relevant theorem system by modifying the range of important parameters. The calculation formula of three kinds of quantitative indexes suitable for dynamic multi - mode investment portfolio is established, and the optimization strategy model based on qualitative and quantitative indexes is established, which makes the optimization strategy more accurate. Finally, the feasibility of the above model is verified by case analysis.","PeriodicalId":443064,"journal":{"name":"2017 International Conference on Robots & Intelligent System (ICRIS)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Dynamic Multi-Mode Portfolio Optimization Strategy for Markovian Arrival Process\",\"authors\":\"Jin Fang, Mo Xiaoyun\",\"doi\":\"10.1109/ICRIS.2017.42\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the characteristics of multi - mode portfolio, a dynamic multi - mode portfolio optimization strategy model is established based on Markovian arrival process analysis method, which provides a decision - making method for portfolio management. The model presents the behavior hypothesis of Markovian arrival process, and improves the relevant theorem system by modifying the range of important parameters. The calculation formula of three kinds of quantitative indexes suitable for dynamic multi - mode investment portfolio is established, and the optimization strategy model based on qualitative and quantitative indexes is established, which makes the optimization strategy more accurate. Finally, the feasibility of the above model is verified by case analysis.\",\"PeriodicalId\":443064,\"journal\":{\"name\":\"2017 International Conference on Robots & Intelligent System (ICRIS)\",\"volume\":\"215 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Robots & Intelligent System (ICRIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRIS.2017.42\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Robots & Intelligent System (ICRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRIS.2017.42","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic Multi-Mode Portfolio Optimization Strategy for Markovian Arrival Process
Aiming at the characteristics of multi - mode portfolio, a dynamic multi - mode portfolio optimization strategy model is established based on Markovian arrival process analysis method, which provides a decision - making method for portfolio management. The model presents the behavior hypothesis of Markovian arrival process, and improves the relevant theorem system by modifying the range of important parameters. The calculation formula of three kinds of quantitative indexes suitable for dynamic multi - mode investment portfolio is established, and the optimization strategy model based on qualitative and quantitative indexes is established, which makes the optimization strategy more accurate. Finally, the feasibility of the above model is verified by case analysis.