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A case study on the shareholder network effect of stock market data: An SARMA approach

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Abstract

One of the key research problems in financial markets is the investigation of inter-stock dependence. A good understanding in this regard is crucial for portfolio optimization. To this end, various econometric models have been proposed. Most of them assume that the random noise associated with each subject is independent. However, dependence might still exist within this random noise. Ignoring this valuable information might lead to biased estimations and inaccurate predictions. In this article, we study a spatial autoregressive moving average model with exogenous covariates. Spatial dependence from both response and random noise is considered simultaneously. A quasi-maximum likelihood estimator is developed, and the estimated parameters are shown to be consistent and asymptotically normal. We then conduct an extensive analysis of the proposed method by applying it to the Chinese stock market data.

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Acknowledgements

The first author was supported by the Major Program of the National Natural Science Foundation of China (Grant No. 11731101) and National Natural Science Foundation of China (Grant No. 11671349). The second author was supported by National Natural Science Foundation of China (Grant No. 72171226), the Beijing Municipal Social Science Foundation (Grant No. 19GLC052) and the National Statistical Science Research Project (Grant No. 2020LZ38). The third author was supported by National Natural Science Foundation of China (Grant Nos. 71532001, 11931014, 12171395 and 71991472) and the Joint Lab of Data Science and Business Intelligence at Southwestern University of Finance and Economics. The fourth author was supported by National Natural Science Foundation of China (Grant No. 11831008) and the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science (Grant No. Klatasds-Moe-Ecnu-Klatasds2101).

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Authors and Affiliations

  1. School of Mathematics and Statistics, Yunnan University, Kunming, 650500, China

    Rong Zhang

  2. Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, 100872, China

    Jing Zhou

  3. The Center of Statistical Research, Southwestern University of Finance and Economics, Chengdu, 611130, China

    Wei Lan

  4. Guanghua School of Management, Peking University, Beijing, 100871, China

    Hansheng Wang

Authors
  1. Rong Zhang
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  2. Jing Zhou
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  3. Wei Lan
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  4. Hansheng Wang
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Correspondence to Jing Zhou.

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Zhang, R., Zhou, J., Lan, W. et al. A case study on the shareholder network effect of stock market data: An SARMA approach. Sci. China Math. 65, 2219–2242 (2022). https://doi.org/10.1007/s11425-021-1917-4

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  • DOI: https://doi.org/10.1007/s11425-021-1917-4

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