Investigating the impact of Sino-US trade conflict on the co-movement of stock market between China, US and other East Asian Economies in the perspective of biomechanics and bioinformatics
Abstract
The Sino-U.S. trade conflict on 22 March 2018 the global system of trade and also the international stock market. This paper introduces the theories of biomechanics and bioinformatics to construct a dynamic analytical model based on Vector Auto-Regression (VAR) to investigate the impact of Sino-U.S. trade conflict on the stock markets of China, U.S. and other Asian economies. By employing concepts from biomechanics, the key variables in the co-movement of stock markets in China, the United States, and East Asia are analogized. The co-movement of stock is treated as a “state variable” and the “stress and strain” experienced by each country’s stock market under the influence of other markets are analyzed. This approach reveals the patterns of variation within these stock markets and provides a quantitative basis for understanding their dynamics. The granger causality and co-integration analysis are conducted on the empirical daily stock price data from 21 September 2016 to 22 September 2019. Benchmarking on Sino-US trade conflict on 22 March 2018, the data is divided into two phases, including 21 September 2016 to 21 March 2018, and 22 March 2018 to 22 September 2019. The results of this study show that the Asian stock markets seem to be more independent with the U.S. stock market after the Sino-U.S. trade conflict. And the results of the dynamic analysis model based on VAR also suggest that the tariff and the trade barriers not only hurt the relationship between China’s stock market and U.S.’s stock market, but also hurt the relationships of stock markets among U.S.’s and other Asian economies. The results of this empirical study can provide information for both investors and policy-makers to have a sound understanding of the stock market.
References
1. Vdovichena O, Tkachuk S, Zhuzhukina N, et al. The use of information in the world economy: globalization trends. Futurity Economics&Law. 2022; 2(4): 4-18. doi: 10.57125/FEL.2022.12.25.01
2. Karaduman C. The effects of economic globalization and productivity on environmental quality: evidence from newly industrialized countries. Environmental Science and Pollution Research. 2022; 29(1): 639-652. doi: 10.1007/s11356-021-15717-1
3. Ni J, Xu Y. Forecasting the dynamic correlation of stock indices based on deep learning method. Computational Economics. 2023; 61(1): 35-55. doi: 10.1007/s10614-021-10198-3
4. Dhingra B, Batra S, Aggarwal V, et al. Stock market volatility: a systematic review. Journal of Modelling in Management. 2024; 19(3): 925-952. doi: 10.1108/JM2-04-2023-0080
5. Behera DK, Karthiayani VP. Do globalization progress and sectoral growth shifts affect income inequality? An exploratory analysis from India. Regional Science Policy & Practice. 2022; 14(2): 352-376. doi: 10.1111/rsp3.12499
6. Ji X, Bu N, Zheng C, et al. Stock market reaction to the COVID-19 pandemic: an event study. Portuguese Economic Journal. 2024; 23(1): 167-186. doi: 10.1007/s10258-022-00227-w
7. Zhu S, Wu X, He Z, et al. Mixed frequency domain spillover effect of international economic policy uncertainty on stock market. Kybernetes. 2022; 51(2): 876-895. doi: 10.1108/K-11-2020-0755
8. Ahmed S, Hasan MM, Kamal MR. Russia–Ukraine crisis: The effects on the European stock market. European Financial Management. 2023; 29(4): 1078-1118. doi: 10.1111/eufm.12386
9. Rakshit B, Neog Y. Effects of the COVID-19 pandemic on stock market returns and volatilities: evidence from selected emerging economies. Studies in Economics and Finance. 2022; 39(4): 549-571. doi: 10.1108/SEF-09-2020-0389
10. Kundu S, Paul A. Effect of economic policy uncertainty on stock market return and volatility under heterogeneous market characteristics. International review of economics & finance. 2022; 80: 597-612. doi: 10.1016/j.iref.2022.02.047
11. Yang T, Zhou F, Du M, et al. Fluctuation in the global oil market, stock market volatility, and economic policy uncertainty: A study of the US and China. The quarterly review of economics and finance. 2023; 87: 377-387. doi: 10.1016/j.qref.2021.08.006
12. Karanasos M, Yfanti S, Hunter J. Emerging stock market volatility and economic fundamentals: The importance of US uncertainty spillovers, financial and health crises. Annals of operations research. 2022; 313(2): 1077-1116. doi: 10.1007/s10479-021-04042-y
13. Ma Y, Wang Z, He F. How do economic policy uncertainties affect stock market volatility? Evidence from G7 countries. International Journal of Finance & Economics. 2022; 27(2): 2303-2325. doi: 10.1002/ijfe.2274
14. Bashir MF. Oil price shocks, stock market returns, and volatility spillovers: a bibliometric analysis and its implications. Environmental Science and Pollution Research. 2022; 29(16): 22809-22828. doi: 10.1007/s11356-021-18314-4
15. Lehnert T. The green stock market bubble. Circular Economy and Sustainability, 2023, 3(3): 1213-1222. doi: 10.1007/s43615-022-00223-4
16. Younis I, Gupta H, Shah W U, et al. The effects of economic uncertainty and trade policy uncertainty on industry-specific stock markets equity. Computational Economics. 2024; 64(5): 2909-2933. doi: 10.1007/s10614-024-10552-1
17. Iqbal BA, Rahman N, Elimimian J. The future of global trade in the presence of the Sino-US trade war. Economic and Political Studies. 2019; 7(2): 217-231. doi: 10.1080/20954816.2019.1595324
18. Su CW, Song Y, Tao R, et al. Does political conflict affect bilateral trade or vice versa? Evidence from Sino-U.S. relations. Economic Research-Ekonomska Istraživanja. 2019; 33(1): 3238-3257. doi: 10.1080/1331677x.2019.1694559
19. Yu M, Zhang R. Understanding the recent Sino-U.S. trade conflict. China Economic Journal. 2019; 12(2): 160-174. doi: 10.1080/17538963.2019.1605678
20. Kashyap U, Bothra N. Sino-US Trade and Trade War. Management and Economics Research Journal. 2019; 5: 1. doi: 10.18639/merj.2019.879180
21. Stanev D, Filip K, Bitzas D, et al. Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation. Sensors. 2021; 21(5): 1804. doi: 10.3390/s21051804
22. Zhang J. Biological analysis of trunk support strength training in sports training. Network Modeling Analysis in Health Informatics and Bioinformatics. 2021; 10(1). doi: 10.1007/s13721-021-00289-4
23. LeVeau B. Biomechanics of Human Motion. Routledge; 2024. doi: 10.4324/9781003522775
24. Fama EF. Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance. 1970; 25(2): 383. doi: 10.2307/2325486
25. Ross SA. The Current Status of the Capital Asset Pricing Model (CAPM). The Journal of Finance. 1978; 33(3): 885. doi: 10.2307/2326486
26. Chen NF, Roll R, Ross SA. Economic Forces and the Stock Market. The Journal of Business. 1986; 59(3): 383. doi: 10.1086/296344
27. Nelson CR. Inflation and Rates of Return on Common Stocks. The Journal of Finance. 1976; 31(2): 471-483. doi: 10.1111/j.1540-6261.1976.tb01900.x
28. Geweke J. Measurement of Linear Dependence and Feedback between Multiple Time Series. Journal of the American Statistical Association. 1982; 77(378): 304-313. doi: 10.1080/01621459.1982.10477803
29. ROLL R. Industrial Structure and the Comparative Behavior of International Stock Market Indices. The Journal of Finance. 1992; 47(1): 3-41. doi: 10.1111/j.1540-6261.1992.tb03977.x
30. Chen NF, Zhang F. Correlations, trades and stock returns of the Pacific-Basin markets. Pacific-Basin Finance Journal. 1997; 5(5): 559-577. doi: 10.1016/S0927-538X(97)00022-X
31. Maysami RC, Howe LC, Rahmat MA. Relationship between Macroeconomic Variables and Stock Market Indices: Cointegration Evidence from Stock Exchange of Singapore’s All-S Sector Indices. Jurnal Pengurusan. 2005; 24: 47-77. doi: 10.17576/pengurusan-2005-24-03
32. Claessens S, Klingebiel D, Schmukler SL. Stock market development and internationalization: Do economic fundamentals spur both similarly?. Journal of Empirical Finance. 2006; 13(3): 316-350. doi: 10.1016/j.jempfin.2006.03.002
33. Ratanapakorn O, Sharma SC. Dynamic analysis between the US stock returns and the macroeconomic variables. Applied Financial Economics. 2007; 17(5): 369-377. doi: 10.1080/09603100600638944
34. Rahman AA, Sidek NZM, Tafri FH. Macroeconomic determinants of Malaysian stock market. African Journal of Business Management. 2009.
35. Granger CWJ, Morgenstern O. Predictability of stock market prices. Lexington, MA: Heath Lexington Books; 1970.
36. King MA, Wadhwani S. Transmission of Volatility between Stock Markets. Review of Financial Studies. 1990; 3(1): 5-33. doi: 10.1093/rfs/3.1.5
37. Karolyi GA, Stulz RM. Why Do Markets Move Together? An Investigation of U.S.‐Japan Stock Return Comovements. The Journal of Finance. 1996; 51(3): 951-986. doi: 10.1111/j.1540-6261.1996.tb02713.x
38. Connolly RA, Wang FA. International equity market comovements: Economic fundamentals or contagion?. Pacific-Basin Finance Journal. 2003; 11(1): 23-43. doi: 10.1016/S0927-538X(02)00060-4
39. Forbes KJ, Rigobon R. No Contagion, Only Interdependence: Measuring Stock Market Comovements. The Journal of Finance. 2002; 57(5): 2223-2261. doi: 10.1111/0022-1082.00494
40. Bekaert G, Ehrmann M, Fratzscher M, et al. The Global Crisis and Equity Market Contagion. The Journal of Finance. 2014; 69(6): 2597-2649. doi: 10.1111/jofi.12203
41. Huyghebaert N, Wang L. The co-movement of stock markets in East Asia. China Economic Review. 2010; 21(1): 98-112. doi: 10.1016/j.chieco.2009.11.001
42. Graham M, Kiviaho J, Nikkinen J. Integration of 22 emerging stock markets: A three-dimensional analysis. Global Finance Journal. 2012; 23(1): 34-47. doi: 10.1016/j.gfj.2012.01.003
43. De Jong F, De Roon F. Time-varying market integration and expected returns in emerging markets. Journal of Financial Economics. 2005; 78(3): 583-613. doi: 10.1016/j.jfineco.2004.10.010
44. Jang H, Sul W. The Asian financial crisis and the co-movement of Asian stock markets. Journal of Asian Economics, 2002; 13(1): 94-104. doi: 10.1016/S1049-0078(01)00115-4
45. Jiang Y, Yu M, Hashmi S. The Financial Crisis and Co-Movement of Global Stock Markets—A Case of Six Major Economies. Sustainability. 2017; 9(2): 260. doi: 10.3390/su9020260
46. Didier T, Love I, Martínez Pería MS. What explains comovement in stock market returns during the 2007–2008 crisis?. International Journal of Finance & Economics. 2011; 17(2): 182-202. doi: 10.1002/ijfe.442
47. Hwang E, Min HG, Kim BH, et al. Determinants of stock market comovements among US and emerging economies during the US financial crisis. Economic Modelling. 2013; 35: 338-348. doi: 10.1016/j.econmod.2013.07.021
48. Trihadmini N, Falianty TA. Stock market contagion and spillover effects of the global financial crisis on five ASEAN countries. Institutions and Economies; 2020.
49. Lee HS, Kim TY. A new analytical approach for identifying market contagion. Financial Innovation. 2022; 8(1). doi: 10.1186/s40854-022-00339-4
50. Iwanicz-Drozdowska M, Rogowicz K, Kurowski Ł, et al. Two decades of contagion effect on stock markets: Which events are more contagious?. Journal of Financial Stability. 2021; 55: 100907. doi: 10.1016/j.jfs.2021.100907
51. Ji X, Wang S, Xiao H, et al. Contagion Effect of Financial Markets in Crisis: An Analysis Based on the DCC–MGARCH Model. Mathematics. 2022; 10(11): 1819. doi: 10.3390/math10111819
52. Bayona A, Peia O. Financial contagion and the wealth effect: An experimental study. Journal of Economic Behavior & Organization. 2022; 200: 1184-1202. doi: 10.1016/j.jebo.2020.08.001
53. Burfisher ME. Introduction to Computable General Equilibrium Models. Cambridge University Press; 2021. doi: 10.1017/9781108780063
54. Nair BB, Mohandas VP, Sakthivel NR. A genetic algorithm optimized decision tree-SVM based stock market trend prediction system. International journal on computer science and engineering. 2010.
55. Kurani A, Doshi P, Vakharia A, et al. A Comprehensive Comparative Study of Artificial Neural Network (ANN) and Support Vector Machines (SVM) on Stock Forecasting. Annals of Data Science. 2021; 10(1): 183-208. doi: 10.1007/s40745-021-00344-x
56. Tang Y, Xiong JJ, Luo Y, et al. How Do the Global Stock Markets Influence One Another? Evidence from Finance Big Data and Granger Causality Directed Network. International Journal of Electronic Commerce. 2019; 23(1): 85-109. doi: 10.1080/10864415.2018.1512283
Copyright (c) 2025 Author(s)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright on all articles published in this journal is retained by the author(s), while the author(s) grant the publisher as the original publisher to publish the article.
Articles published in this journal are licensed under a Creative Commons Attribution 4.0 International, which means they can be shared, adapted and distributed provided that the original published version is cited.
Submit a Paper
