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Specifically, the financial time series is decomposed by EEMD into some subseries. Then, the linear portion of each subseries is forecasted by the linear ARIMA model, while the nonlinear portion is predicted by the nonlinear Taylor expansion model. The forecasting results of the linear and nonlinear models are combined into the predicted result of each subseries. The final prediction result is obtained by combining the prediction values of all the subseries. The empirical results with real financial time series data demonstrate that this new hybrid approach outperforms the benchmark hybrid models considered in this paper.<\/jats:p>","DOI":"10.1111\/exsy.12633","type":"journal-article","created":{"date-parts":[[2020,9,3]],"date-time":"2020-09-03T03:10:05Z","timestamp":1599102605000},"update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["A hybrid model for financial time\u2010series<\/scp> forecasting based on mixed methodologies"],"prefix":"10.1111","volume":"38","author":[{"given":"Zhidan","family":"Luo","sequence":"first","affiliation":[{"name":"School of Statistics University of International Business and Economics Beijing China"}]},{"given":"Wei","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Statistics University of International Business and Economics Beijing China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-4252-2360","authenticated-orcid":false,"given":"Qingfu","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute for Financial Studies Fudan University Shanghai China"}]},{"given":"Zhengjun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Statistics University of Wisconsin\u2010Madison Madison Wisconsin USA"}]}],"member":"311","published-online":{"date-parts":[[2020,9,2]]},"reference":[{"issue":"1","key":"e_1_2_8_2_1","first-page":"1","article-title":"A hybrid approach EMD\u2010MA for short\u2010term forecasting of daily stock market time series data","volume":"22","author":"Ahmad M. 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