Research Article of Journal of Theoretical and Applied Economics
Studying the Correlation of Stocks via Copula Function
Yishuai Tian1, Boying Lv1, Botao Liu1
1College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China.
Many factors affect the value of stocks, but there are few studies on the correlation between stocks and stock indexes. Therefore, this paper selects the closing prices of 4 industries related to Everbright Bank (601818) and 15 sectors related to the market index from 2017 to 2018, carries on the correlation analysis based on the Copula function, and compares the correlation coefficient by calculation. The stocks closely related to Everbright Bank are mainly bank stocks such as Bank of China and Ningbo Bank, while those greatly affected by the Shanghai Composite Index are Yunnan germanium industry, Tongji Technology, Futian Automobile and other technology and manufacturing stocks. Based on the Copula function to explore the correlation between stocks and the influencing factors, to provide a specific research basis for stock correlation analysis.
Keywords: Copula function; Correlation analysis; Stock market index
How to cite this article:
Yishuai Tian, Boying Lv, Botao Liu. Studying the Correlation of Stocks via Copula Function. Journal of Theoretical and Applied Economics, 2020; 4:5. DOI: 10.28933/jtae-2020-01-2005
1. Yuan Yao, Beibei Yao, Qi Zhong. A study on the influence of Investor sentiment on Stock return–an empirical Analysis based on Shanghai A-share data [J]. Price theory and practice,2019 (05):88-91.
2. Rongyu Deng. The impact of profitability of listed companies on stock prices [J]. The Chinese market,2019(25):42-44.
3. Yilun Qian. Analysis on the influencing factors of Vanke Stock Price– based on the empirical Analysis of listed companies in Real Estate Industry [J]. Paying taxes, 2019,13(05):166-167.
4. Huixian Zhang. Study on the relationship between Shanghai Composite Index and other Shanghai Classification Index [J]. Modern Marketing (Information Edition), 2019(01):12.
5. Hanlin Ji, Meng Xu. Research on the dynamic correlation between Financial sector and Shanghai Stock Index– based on VAR-DCC-GARCH Model [J]. Prices in China, 2020(01):83-85.
6. S&P Dow Jones Indices; NeoGenomics Set to Join S&P SmallCap 600[J]. Genetics & Environmental Business Week, 2019.
7. Jia Song. Product market competition, R & D investment and stock return [D]. Shanxi University, 2018.
8. Hao Ding. Empirical Analysis on the influencing factors of stock price change in Guizhou Moutai [J]. Modern economic information,2018(12):304.
9. Zongjing Liang, Yonghui Pang, Yun Kuan. Study on the influence of Food Safety incident Network on Food Stock Price [J]. Commercial economy 2019(10):177-180.
10. Van Ness B F, Van Ness R A, Yildiz S. The role of HFTs in order flow toxicity and stock price variance, and predicting changes in HFTs’ liquidity provisions[J]. Journal of Economics and Finance, 2017,41(4).
11. Blau B M. Religiosity and the Volatility of Stock Prices: A Cross-Country Analysis[J]. Journal of Business Ethics, 2017,144(3).
12. Gao H, Mei D. The correlation structure in the international stock markets during global financial crisis[J]. Physica A: Statistical Mechanics and its Applications, 2019,534.
13. Rubin D N, Bassett D S, Ready R. Uncovering dynamic stock return correlations with multilayer network analysis[J]. Applied Network Science, 2019,4(1).
14. Boako G, Tiwari A K, Ibrahim M, et al. Analysing dynamic dependence between gold and stock returns: Evidence using stochastic and full-range tail dependence copula models[J]. Finance Research Letters, 2019,31.
15. Xiaojun Dong. Macro-economy continues to decline and beware of systemic risk agglomeration– from the listing of China Cinda and Ever-bright Bank in Hong Kong [J]. Administrative management reform, 2014(04):33-37.
16. Weichen Xing. Prediction of Shanghai Stock Index based on BP neural network [J]. Enterprise Science and Technology and Development, 2019(12):124-125.
17. Bing Xu, Juan Chen. An empirical study on the tail of Index return Distribution in Shanghai and Shenzhen Stock Market [J]. The practice and understanding of mathematics, 2006(09):49-54.