Co-movement dynamics of US and Chinese stock market: evidence from COVID-19 crisis

Figures & data

Table 1. Summary statistics.

Period	Mean	Median	Max	Min	SD	Skewness	Kurtosis	Jarque–Bera
USA
Pre-Covid	0.001	0.050	5.732	–5.143	1.198	0.147	5.548	561.24***
During-Covid	0.082	0.052	3.782	–9.587	2.377	–0.089	7.361	371.79***
China
Pre-Covid	0.076	0.153	9.231	–10.372	1.420	0.684	8.127	2181.28***
During-Covid	0.003	0.078	5.990	–12.346	2.743	–0.363	9.873	872.64***

Note: The sample period is from 01/07/2010 to 31/04/2021.

*** Denotes significant at 1%.

Source: Author Estimation.

Table 2. Correlation matrix.

Period	USA	China
Pre-Covid period
USA	1.0000	0.0431
China	0.0431	1.0000
During-Covid
USA	1.0000	0.4698
China	0.4698	1.0000

Source: Author Estimation.

Table 3. Unit root tests.

Period	ADF test	PP test	ARCH effect
USA
Pre-Covid	–48.1631***	–48.3821***	62.6571***
During-Covid	–22.6531***	–29.3871***	135.6521***
China
Pre-Covid	–42.8137***	–49.6217***	54.01324***
During-Covid	–30.8342***	–33.6473***	125.8462***

*** Denotes significant at 1%.

Source: Author Estimation.

Table 4. Cointegration between the USA and China.

Period	Eigenvalue	Trace statistics	0.5 critical value	Max-Eigen statistics	0.5 critical value	Prob.
Pre-Covid
None*	0.2231	1012.461	51.6231	405.0264	27.58434	0.000
At most 1*	0.1932	820.652	37.3421	356.0068	21.13162	0.000
At most 2*	0.1721	621.4621	19.2371	306.7558	14.26460	0.000
At most 3*	0.1571	571.2310	8.9821	264.5378	3.841466	0.000
During Covid
None*	0.2062	1332.327	47.8561	321.1271	34.23790	0.000
At most 1*	0.1837	927.3004	29.7970	287.2011	29.32801	0.000
At most 2*	0.1605	571.2936	15.4947	256.3611	23.43091	0.000
At most 3*	0.1400	264.5378	3.8414	213.2310	15.78231	0.000

* Denotes significant at 10%.

Source: Author Estimation.

Table 5. Granger causality between the USA and China.

Null hypothesis	Pre-Covid period	During-Covid period
USA-China	3.8231***	13.6521***
China-USA	6.7821***	19.2351***

*** Denotes significant at 1%.

Source: Author Estimation.

Table 6. EGARCH model (pre-crisis period).

Pre-Covid period
Mean equation			Variance equation
Coefficients	USA	China	Coefficients	USA	China
${\beta }_0$	0.0002(0.0001)	0.0009(0.0003)	${\mathrm{\varnothing }}_0$	–0.3982***(0.0126)	–2.0361***(0.2251)
${\beta }_1$	–0.0732***(0.0342)	0.0532***(0.0220)	${\mathrm{\varnothing }}_1$	1.0432***(0.0172)	0.4351***(0.0361)
$\alpha \_\mathit{USA}$	–	0.0470**(0.172)	$\partial$	–0.0892***(0.0281)	–0.1762***(0.0271)
$\alpha \_\mathit{China}$	0.0372***(0.128)	–	${\mathrm{\varnothing }}_3$	0.3720*** (0.0034)	1.2315***(0.2781)
			$\gamma \_\mathit{USA}$	–	0.6532***(0.0910)
			$\gamma \_\mathit{China}$	1.3261***(1.2371)	–

*** Denotes significant at 1%.

** Denotes significant at 5%.

Source: Author Estimation.

Table 7. EGARCH model (during-crisis period).

During-Covid period
Mean equation			Variance equation
Coefficients	USA	China	Coefficients	USA	China
${\beta }_0$	0.0002(0.0001)	0.0009(0.0003)	${\mathrm{\varnothing }}_0$	–0.3982***(0.0126)	–2.0361***(0.2251)
${\beta }_1$	–0.0732***(0.0342)	0.0532***(0.0220)	${\mathrm{\varnothing }}_1$	1.0432***(0.0172)	0.4351***(0.0361)
$\alpha \_\mathit{USA}$	–	0.0470**(0.172)	$\partial$	–0.0892***(0.0281)	–0.1762***(0.0271)
$\alpha \_\mathit{China}$	0.0372***(0.128)	–	${\mathrm{\varnothing }}_3$	0.3720*** (0.0034)	1.2315***(0.2781)
			$\gamma \_\mathit{USA}$	–	0.6532***(0.0910)
			$\gamma \_\mathit{China}$	1.3261***(1.2371)	–

*** Denotes significant at 1%.

** Denotes significant at 5%.

Source: Author Estimation.