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Uncovering the impacts of structural similarity of financial indicators on stock returns at different quantile levels

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  • Xi, Xian
  • Gao, Xiangyun
  • Zhou, Jinsheng
  • Zheng, Huiling
  • Ding, Jiazheng
  • Si, Jingjian

Abstract

The mining industry is the upstream industry of national economic development. In recent years, the mining financial market has rapidly developed. Stock returns have always been a hot topic for investors and researchers. There are many factors affecting stock prices, such as market supply and demand, national policies and the price fluctuations of other financial products. The most essential factor affecting stock price fluctuation is the operating condition of the listed companies that issue shares. A series of financial indicators comprehensively and systematically reflect listed companies' current earnings and future development potential. However, there are few studies on the structure of financial indicators of listed mining companies. Therefore, we take listed mining companies as the research object to explore whether the structural similarity of their financial indicators can uncover their stock returns. The research findings are as follows: (1) The strength of the structural similarity of financial indicators has a significant negative impact on annual returns, so enterprise managers should adjust their business model and attach importance to personalized development. (2) Similar media capabilities have a negative impact on companies with high annual stock returns and a positive impact on companies with low annual stock returns. (3) The impact of similar cohesion on annual returns varies across different networks and it has a positive effect on the earnings of low-returning companies in operation network. A specific analysis should be carried out according to different financial indicator networks to diversify investment.

Suggested Citation

  • Xi, Xian & Gao, Xiangyun & Zhou, Jinsheng & Zheng, Huiling & Ding, Jiazheng & Si, Jingjian, 2021. "Uncovering the impacts of structural similarity of financial indicators on stock returns at different quantile levels," International Review of Financial Analysis, Elsevier, vol. 76(C).
    • Handle: RePEc:eee:finana:v:76:y:2021:i:c:s1057521921001253
    DOI: 10.1016/j.irfa.2021.101787
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    Cited by:

    1. Wang, Xiaoxuan & Gao, Xiangyun & Wu, Tao & Sun, Xiaotian, 2022. "Dynamic multiscale analysis of causality among mining stock prices," Resources Policy, Elsevier, vol. 77(C).
    2. Cerqueti, Roy & Deffains-Crapsky, Catherine & Storani, Saverio, 2022. "Similarity-based heterogeneity and cohesiveness of networked companies issuing minibonds," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    3. Ioan I. Gâf-Deac & Mohammad Jaradat & Florina Bran & Raluca Florentina Crețu & Daniel Moise & Svetlana Platagea Gombos & Teodora Odett Breaz, 2022. "Similarities and Proximity Symmetries for Decisions of Complex Valuation of Mining Resources in Anthropically Affected Areas," Sustainability, MDPI, vol. 14(16), pages 1-22, August.

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