吉首大学学报（自然科学版）2018，Vol.39Issue(3)：14-19,6.DOI:10.3969/j.cnki.jdxb.2018.03.004
基于改进的分形插值与SVM的股指预测模型
Prediction of Stock Index Based on Fractal Interpolation and SVM
摘要
Abstract
In order to better analyze and predict the short-term trend of stock index time series ,we pro-pose a new method to determine the free parameters of fractal interpolation ,and establish an improved fractal interpolation model .This model is the combined with the support vector machine model to estab-lish a mixed prediction model .The daily closing data of Shanghai composite index is selected as the re-search object which is shown to have long-range dependence thorugh R/S analysis .The time series of Shanghai composite index are analyzed and predicted by the mixed prediction model .The empirical re-sults show that and the new mixed model proposed in this paper has good fitting performance and higher accuracy in short-term prediction .关键词
分形插值/SVM模型/股指序列/预测Key words
fractal interpolation/SVM model/stock index series/prediction分类
管理科学引用本文复制引用
黎红,王宏勇..基于改进的分形插值与SVM的股指预测模型[J].吉首大学学报（自然科学版）,2018,39(3):14-19,6.基金项目
教育部人文社科规划基金(12YJAZH020 ) （12YJAZH020 ）
南京财经大学现代服务业协同创新中心资助项目(ZWFXT14001) （ZWFXT14001）
江苏省普通高校学术学位研究生科研创新计划项目(KYLX16＿1337) （KYLX16＿1337）
