Forecasting China's stock index: A hybrid method based on decomposition-integrated and mixed-frequency data

CHEN Kaijie, TANG Zhenpeng, WU Junchuan, DU Xiaoxu, CAI Yi

Systems Engineering - Theory & Practice ›› 2022, Vol. 42 ›› Issue (11) : 3105-3120.

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Systems Engineering - Theory & Practice ›› 2022, Vol. 42 ›› Issue (11) : 3105-3120. DOI: 10.12011/SETP2022-0376

Forecasting China's stock index: A hybrid method based on decomposition-integrated and mixed-frequency data

  • CHEN Kaijie1, TANG Zhenpeng2, WU Junchuan3, DU Xiaoxu1, CAI Yi1
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Abstract

Accurate forecasts of the stock market have important implications for both investors and regulators. The decomposition-integration framework is widely used in forecasting research of financial time series. However, most of previous studies only use single historical data to predict the components, which ignoring the influence of other low-frequency heterogeneous data on the components. This study proposes a novel decomposition-integration model EEMD-Mixed Frequency CNN-BiLSTM-Attention/LSTM-LSTM (EE-MFCBA/L-L), which take the advantages of the decomposition-integration and mixing data sampling. Firstlly the stock index is decomposed into several different frequency components by EEMD. Meanwhile the fuzzy entropy algorithm is used to identify the frequency characteristic of the components. Then the components are predicted by MFCBA/L model where the low frequency data will be considered according to the frequency characteristics of the components. Finally, the LSTM model is used to nonlinearly integrate the predictor of each component. The empirical results show that the proposed model can better adapt to the characteristics of returns. Compared with the traditional model, the proposed model has significant advantages in predicting non-stationary and nonlinear return series, with the lowest prediction error and the highest directional prediction accuracy.

Key words

stock index / mixed frequency prediction / ensemble learning / signal decomposition

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CHEN Kaijie , TANG Zhenpeng , WU Junchuan , DU Xiaoxu , CAI Yi. Forecasting China's stock index: A hybrid method based on decomposition-integrated and mixed-frequency data. Systems Engineering - Theory & Practice, 2022, 42(11): 3105-3120 https://doi.org/10.12011/SETP2022-0376

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Funding

The General Program of National Natural Science Foundation of China (71973028, 71573042)
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