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Regional characteristics of sports industry profitability: Evidence from China’s province level data

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  • Wang, Yan
  • Wang, Yue
  • Li, Ming-Xia

Abstract

Given its regionally lopsided development, the sports industry in China now largely features spatial and geographical agglomeration. Profitability is an important parameter for the sustainable development of an industry. It is interesting to make clear whether the profitability of Chinese sports industry features regional agglomeration. We firstly make a statistical analysis and probability density analysis by Random Matrix Theory (RMT) based on monthly provincial profit margin data of the sporting goods manufacturing industry listed from 2011 to 2015. We find that the profit margin of this industry is not randomly distributed over the regions. We also focus on the collective market effects of the profitability of this industry. Through the method of regression analysis on the largest 3 eigenvalues of the profit margin, we find that the eigenvalues reflect the collective market effects in Profit to Cost Ratio (PCR) and Return on Sales (ROS). At last, we search each correlation matrix of the profit margin for the clusters of provinces by using the clustering methods. We find the majority of the provinces can be categorized into clusters and most of the correlated provinces are adjacency or proximity. Our analysis provides a new understanding of the regional characteristics of sports industry profitability and offers potential practical values for the government and entrepreneurs.

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  • Wang, Yan & Wang, Yue & Li, Ming-Xia, 2019. "Regional characteristics of sports industry profitability: Evidence from China’s province level data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 946-955.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:946-955
    DOI: 10.1016/j.physa.2019.03.066
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    as
    1. Chester Curme & Michele Tumminello & Rosario N. Mantegna & H. Eugene Stanley & Dror Y. Kenett, 2015. "Emergence of statistically validated financial intraday lead-lag relationships," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1375-1386, August.
    2. Fang, Libing & Xiao, Binqing & Yu, Honghai & You, Qixing, 2018. "A stable systemic risk ranking in China’s banking sector: Based on principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1997-2009.
    3. X. F. Jiang & B. Zheng, 2012. "Anti-correlation and subsector structure in financial systems," Papers 1201.6418, arXiv.org.
    4. Wang, Gang-Jin & Jiang, Zhi-Qiang & Lin, Min & Xie, Chi & Stanley, H. Eugene, 2018. "Interconnectedness and systemic risk of China's financial institutions," Emerging Markets Review, Elsevier, vol. 35(C), pages 1-18.
    5. Marcel van den Berg & Charles van Marrewijk & Saara Tamminen, 2018. "Trade, productivity and profitability: On profit levels and profit margins," The World Economy, Wiley Blackwell, vol. 41(8), pages 2149-2174, August.
    6. Hao Meng & Wen-Jie Xie & Wei-Xing Zhou, 2015. "Club Convergence of House Prices: Evidence from China's Ten Key Cities," Papers 1503.05550, arXiv.org.
    7. S. De Schoenmaker & P. Van Cauwenberge & H. Vander Bauwhede, 2013. "The influence of agglomerations on firm profitability," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/853, Ghent University, Faculty of Economics and Business Administration.
    8. Uechi, Lisa & Akutsu, Tatsuya & Stanley, H. Eugene & Marcus, Alan J. & Kenett, Dror Y., 2015. "Sector dominance ratio analysis of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 488-509.
    9. Machin, Stephen & Van Reenen, John, 1993. "Profit Margins and the Business Cycle: Evidence from UK Manufacturing Firms," Journal of Industrial Economics, Wiley Blackwell, vol. 41(1), pages 29-50, March.
    10. X. F. Jiang & T. T. Chen & B. Zheng, 2014. "Structure of local interactions in complex financial dynamics," Papers 1406.0070, arXiv.org.
    11. Laurent Laloux & Pierre Cizeau & Marc Potters & Jean-Philippe Bouchaud, 2000. "Random Matrix Theory And Financial Correlations," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 391-397.
    12. Fei Ren & Wei-Xing Zhou, 2014. "Dynamic Evolution of Cross-Correlations in the Chinese Stock Market," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-15, May.
    13. Spyridon Stavropoulos & Dimitris Skuras, 2016. "Firm Profitability and Agglomeration Economies: An Elusive Relationship," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 107(1), pages 66-80, February.
    14. Yue-Hua Dai & Wen-Jie Xie & Zhi-Qiang Jiang & George J. Jiang & Wei-Xing Zhou, 2016. "Correlation structure and principal components in the global crude oil market," Empirical Economics, Springer, vol. 51(4), pages 1501-1519, December.
    15. Tumminello, Michele & Lillo, Fabrizio & Mantegna, Rosario N., 2010. "Correlation, hierarchies, and networks in financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 75(1), pages 40-58, July.
    16. Yue-Hua Dai & Wei-Xing Zhou, 2017. "Temporal and spatial correlation patterns of air pollutants in Chinese cities," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-24, August.
    17. Wang, Gang-Jin & Xie, Chi, 2015. "Correlation structure and dynamics of international real estate securities markets: A network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 176-193.
    18. Fenghua Wen & Xin Yang & Xu Gong & Kin Keung Lai, 2017. "Multi-Scale Volatility Feature Analysis and Prediction of Gold Price," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 205-223, January.
    19. Vasiliki Plerou & Parameswaran Gopikrishnan & Bernd Rosenow & Luis A. Nunes Amaral & H. Eugene Stanley, 1999. "Universal and non-universal properties of cross-correlations in financial time series," Papers cond-mat/9902283, arXiv.org.
    20. Li, Xing & Qiu, Tian & Chen, Guang & Zhong, Li-Xin & Wu, Xiao-Run, 2017. "Market impact and structure dynamics of the Chinese stock market based on partial correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 106-113.
    21. Lin, Min & Wang, Gang-Jin & Xie, Chi & Stanley, H. Eugene, 2018. "Cross-correlations and influence in world gold markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 504-512.
    22. Wang, Gang-Jin & Xie, Chi & Chen, Shou & Yang, Jiao-Jiao & Yang, Ming-Yan, 2013. "Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3715-3730.
    23. Dong-Ming Song & Michele Tumminello & Wei-Xing Zhou & Rosario N. Mantegna, 2011. "Evolution of worldwide stock markets, correlation structure and correlation based graphs," Papers 1103.5555, arXiv.org.
    24. Gang-Jin Wang & Chi Xie & H. Eugene Stanley, 2018. "Correlation Structure and Evolution of World Stock Markets: Evidence from Pearson and Partial Correlation-Based Networks," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 607-635, March.
    25. Shen, Dehua & Liu, Lanbiao & Zhang, Yongjie, 2018. "Quantifying the cross-sectional relationship between online sentiment and the skewness of stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 928-934.
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    Cited by:

    1. Mei Yang & Hongling Zhou & Yali Li & Jinyu Zhang, 2023. "Efficiency Evaluation and Influencing Factors of Sports Industry and Tourism Industry Convergence Based on China’s Provincial Data," Sustainability, MDPI, vol. 15(6), pages 1-23, March.

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