IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v542y2020ics0378437119313007.html
   My bibliography  Save this article

Dynamic energy stock selection based on shareholders’ coholding network

Author

Listed:
  • Sun, Bowen
  • Li, Huajiao
  • An, Pengli
  • Wang, Ze

Abstract

In stock market investment, the first step is to select stocks. To do so, stock traders have depended on two major tools: fundamental analysis and technical analysis, while ignoring the impact of large shareholder behavior on stocks. The major shareholders in the Chinese stock market show a serious herd effect; they can control or influence the stock price of the listed companies by increasing or reducing their holdings, which may affect the stability of the market. Thus, it is significant to study shareholders’ holding behavior. In this paper, we constructed a shareholder coholding network of listed energy companies in the Chinese stock market based on quarterly shareholder data from 2012 to 2018. We selected stocks by choosing central and peripheral topological indicators in the training period, namely, degree (D), betweenness centrality (BC), closeness centrality (CC) and eigenvector centrality (EC). We also used other traditional trading strategies to select stocks. Then, we used the selected stocks to build the portfolio and measure the performance in the test period. We identified the market conditions in different test periods and evaluated the performance of the portfolios in different market conditions. The results show that the topological indicators of a shareholder coholding network can be used to guide actual investment, and the suggestions for investment in different market environments are presented in the conclusion.

Suggested Citation

  • Sun, Bowen & Li, Huajiao & An, Pengli & Wang, Ze, 2020. "Dynamic energy stock selection based on shareholders’ coholding network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    • Handle: RePEc:eee:phsmap:v:542:y:2020:i:c:s0378437119313007
    DOI: 10.1016/j.physa.2019.122243
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119313007
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.122243?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Huajiao & An, Haizhong & Gao, Xiangyun & Huang, Jiachen & Xu, Qun, 2014. "On the topological properties of the cross-shareholding networks of listed companies in China: Taking shareholders’ cross-shareholding relationships into account," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 80-88.
    2. Li, Jie & Ren, Da & Feng, Xu & Zhang, Yongjie, 2016. "Network of listed companies based on common shareholders and the prediction of market volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 508-521.
    3. Zhao, Longfeng & Wang, Gang-Jin & Wang, Mingang & Bao, Weiqi & Li, Wei & Stanley, H. Eugene, 2018. "Stock market as temporal network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1104-1112.
    4. M. D'Errico & R. Grassi & S. Stefani & A. Torriero, 2009. "Shareholding Networks and Centrality: An Application to the Italian Financial Market," Lecture Notes in Economics and Mathematical Systems, in: Ahmad K. Naimzada & Silvana Stefani & Anna Torriero (ed.), Networks, Topology and Dynamics, pages 215-228, Springer.
    5. Hao, Xiaoqing & An, Haizhong & Sun, Xiaoqi & Zhong, Weiqiong, 2018. "The import competition relationship and intensity in the international iron ore trade: From network perspective," Resources Policy, Elsevier, vol. 57(C), pages 45-54.
    6. An, Pengli & Li, Huajiao & Zhou, Jinsheng & Chen, Fan, 2017. "The evolution analysis of listed companies co-holding non-listed financial companies based on two-mode heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 558-568.
    7. Yao, Juan & Ma, Chuanchan & He, William Peng, 2014. "Investor herding behaviour of Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 12-29.
    8. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    9. Li, Huajiao & An, Haizhong & Huang, Jiachen & Huang, Xuan & Mou, Songtao & Shi, Yanli, 2016. "The evolutionary stability of shareholders’ co-holding behavior for China’s listed energy companies based on associated maximal connected sub-graphs of derivative holding-based networks," Applied Energy, Elsevier, vol. 162(C), pages 1601-1607.
    10. Fei Ren & Ya-Nan Lu & Sai-Ping Li & Xiong-Fei Jiang & Li-Xin Zhong & Tian Qiu, 2017. "Dynamic Portfolio Strategy Using Clustering Approach," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-23, January.
    11. Xi, Xian & An, Haizhong, 2018. "Research on energy stock market associated network structure based on financial indicators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1309-1323.
    12. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2010. "Complex stock trading network among investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4929-4941.
    13. Hendrik Scholz, 2007. "Refinements to the Sharpe ratio: Comparing alternatives for bear markets," Journal of Asset Management, Palgrave Macmillan, vol. 7(5), pages 347-357, January.
    14. Jaehyung Choi, 2012. "Physical approach to price momentum and its application to momentum strategy," Papers 1208.2775, arXiv.org, revised Aug 2014.
    15. Li, Huajiao & Fang, Wei & An, Haizhong & Yan, LiLi, 2014. "The shareholding similarity of the shareholders of the worldwide listed energy companies based on a two-mode primitive network and a one-mode derivative holding-based network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 525-532.
    16. Tan, Lin & Chiang, Thomas C. & Mason, Joseph R. & Nelling, Edward, 2008. "Herding behavior in Chinese stock markets: An examination of A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(1-2), pages 61-77, January.
    17. Ma, Yuan-yuan & Zhuang, Xin-tian & Li, Ling-xuan, 2011. "Research on the relationships of the domestic mutual investment of China based on the cross-shareholding networks of the listed companies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 749-759.
    18. Choi, Jaehyung, 2014. "Physical approach to price momentum and its application to momentum strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 61-72.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Si, Jingjian & Zhou, Jinsheng & Gao, Xiangyun & Ze, Wang & Tao, Wu & Zhao, Yiran, 2022. "Reconstructing a complex financial network using compressed sensing based on low-frequency time series data," Finance Research Letters, Elsevier, vol. 49(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Jie & Ren, Da & Feng, Xu & Zhang, Yongjie, 2016. "Network of listed companies based on common shareholders and the prediction of market volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 508-521.
    2. Fenghua Wen & Yujie Yuan & Wei-Xing Zhou, 2019. "Cross-shareholding networks and stock price synchronicity: Evidence from China," Papers 1903.01655, arXiv.org.
    3. Xi, Xian & An, Haizhong, 2018. "Research on energy stock market associated network structure based on financial indicators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1309-1323.
    4. Li, Huajiao & An, Haizhong & Fang, Wei & Wang, Yue & Zhong, Weiqiong & Yan, Lili, 2017. "Global energy investment structure from the energy stock market perspective based on a Heterogeneous Complex Network Model," Applied Energy, Elsevier, vol. 194(C), pages 648-657.
    5. An, Pengli & Zhou, Jinsheng & Li, Huajiao & Sun, Bowen & Shi, Yanli, 2018. "The evolutionary similarity of the co-shareholder relationship network from institutional and non-institutional shareholder perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 439-450.
    6. An, Feng & Gao, Xiangyun & Guan, Jianhe & Huang, Shupei & Liu, Qian, 2017. "Modeling the interdependent network based on two-mode networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 57-67.
    7. Fenghua Wen & Yujie Yuan & Wei‐Xing Zhou, 2021. "Cross‐shareholding networks and stock price synchronicity: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 914-948, January.
    8. Arjoon, Vaalmikki & Bhatnagar, Chandra Shekhar & Ramlakhan, Prakash, 2020. "Herding in the Singapore stock Exchange," Journal of Economics and Business, Elsevier, vol. 109(C).
    9. Tihana Škrinjarić, 2018. "Revisiting Herding Investment Behavior on the Zagreb Stock Exchange: A Quantile Regression Approach," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 3(2), pages 119-162, December.
    10. Wang, Hu & Li, Shouwei & Ma, Yuyin, 2021. "Herding in Open-end Funds: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    11. SENARATHNE W Chamil & JIANGUO Wei, 2018. "Do Investors Mimic Trading Strategies Of Foreign Investors Or The Market: Implications For Capital Asset Pricing," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 13(3), pages 171-205, December.
    12. Demirer, Rıza & Lien, Donald & Zhang, Huacheng, 2015. "Industry herding and momentum strategies," Pacific-Basin Finance Journal, Elsevier, vol. 32(C), pages 95-110.
    13. Wan, Xiaoyuan, 2018. "Is the idiosyncratic volatility anomaly driven by the MAX or MIN effect? Evidence from the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 1-15.
    14. Batmunkh John Munkh-Ulzii & Michael McAleer & Massoud Moslehpour & Wing-Keung Wong, 2018. "Confucius and Herding Behaviour in the Stock Markets in China and Taiwan," Sustainability, MDPI, vol. 10(12), pages 1-16, November.
    15. Babalos, Vassilios & Stavroyiannis, Stavros & Gupta, Rangan, 2015. "Do commodity investors herd? Evidence from a time-varying stochastic volatility model," Resources Policy, Elsevier, vol. 46(P2), pages 281-287.
    16. Hossein Dastkhan & Naser Shams Gharneh, 2016. "Determination of Systemically Important Companies with Cross-Shareholding Network Analysis: A Case Study from an Emerging Market," IJFS, MDPI, vol. 4(3), pages 1-17, June.
    17. Wanidwaranan, Phasin & Padungsaksawasdi, Chaiyuth, 2020. "The effect of return jumps on herd behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    18. Nha Duc Bui & Loan Thi Bich Nguyen & Nhung Thi Tuyet Nguyen & Gordon Frederick Titman, 2018. "Herding in frontier stock markets: evidence from the Vietnamese stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 59-81, November.
    19. Wang, Xinru & Kim, Maria H. & Suardi, Sandy, 2022. "Herding and China's market-wide circuit breaker," Journal of Banking & Finance, Elsevier, vol. 141(C).
    20. Qing Yao & Tim S Evans & Kim Christensen, 2019. "How the network properties of shareholders vary with investor type and country," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-19, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:542:y:2020:i:c:s0378437119313007. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.