Stock Market Prediction Using a Hybrid Model

Akhtar, Zuhaib; Khursheed, Mohammad Omar

doi:10.1007/978-981-15-4301-2_7

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Table IV Homogeneous Base Learners For Regression Base Learn...1

Forecasts Of Base Learners1

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2022

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“…Author(s) ANN [47], [52], [53], [55], [66], [72], [78], [89], [91] LSTM [31], [60], [67], [80], [92] Decision Tree [25], [79] SVR [71], [74] LRW [61] RVFL [86] ANFIS [63] NFS [82] EGARCH-BPNN [54] FNT [35] FNN [38] KNN [59] Random Forest [95]…”

Section: Table IV Homogeneous Base Learners For Regression Base Learn...mentioning

confidence: 99%

“…Stock price [23], [24], [25], [35], [36], [38], [45], [47], [51], [55], [53], [63], [65], [66], [69], [70], [72], [79], [80], [81], [83], [87], [89], [90], [91], [95] IMFs value [26], [31], [59], [60], [59], [60], [67], [74], [76], [86], [92] Technical indicator value [37], [71] Stock return [52], [82] Stock volatility [54], [50] Effect of external factors [50], [51], [78] Interval of time series [61] V. DECISION FUSION METHODS Admittedly, a better prediction can be obtained by fusing multiple forecasts of the base learners. However, the choice of the fusion method is also critical to the performance of the entire model.…”

Section: Forecasts Of Base Learnersmentioning

confidence: 99%

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