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A novel (U)MIDAS-SVR model with multi-source market sentiment for forecasting stock returns

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Abstract

From the point view of behavioral finance, market sentiment plays an important role in forecasting stock returns. How to accurately measure the impact of market sentiment is a challenge work. Two issues on nonlinear relationship and mixed-frequency data have to be addressed. To this end, we introduce methods of mixed-frequency data into SVRs and develop a novel (U)MIDAS-SVR model. It can be estimated by solving the Lagrange duality technique of quadratic programming. We then apply the (U)MIDAS-SVR model to predict weekly returns of SHSE and SZSE in China using the mixed-frequency market sentiment as covariates. The empirical results show that the (U)MIDAS-SVR model is promising and MIDAS-SVR is superior to those competing models in terms of MAE and RMSE. In addition, we design seven scenarios by considering different data source combinations and find that the multi-source market sentiment is helpful to improve forecasting performance on stock returns.

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Acknowledgements

The authors are grateful to the Editor-in-Chief, the Associate Editor, and two anonymous referees for their helpful comments and constructive guidance. This work was supported by the National Natural Science Foundation of PR China (71671056, 91846201).

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Authors and Affiliations

  1. School of Management, Hefei University of Technology, Hefei, 230009, Anhui, People’s Republic of China

    Qifa Xu, Liukai Wang, Cuixia Jiang & Yezheng Liu

  2. Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei, 230009, Anhui, People’s Republic of China

    Qifa Xu & Yezheng Liu

Authors
  1. Qifa Xu
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  2. Liukai Wang
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  3. Cuixia Jiang
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  4. Yezheng Liu
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Correspondence to Cuixia Jiang.

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Xu, Q., Wang, L., Jiang, C. et al. A novel (U)MIDAS-SVR model with multi-source market sentiment for forecasting stock returns. Neural Comput & Applic 32, 5875–5888 (2020). https://doi.org/10.1007/s00521-019-04063-6

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  • DOI: https://doi.org/10.1007/s00521-019-04063-6

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