Features of different asset types and extreme risk transmission during the COVID-19 crisis

Tsai, I-Chun

doi:10.1186/s40854-023-00510-5

Financial Innovation

Table 7 The Relationship between Asset Returns and Stringency Index: The VAR-MGARCH Model

From: Features of different asset types and extreme risk transmission during the COVID-19 crisis

	\(\Delta CCI\)		\(\Delta BTC\)		\(\Delta WSPI\)		\(\Delta WTI\)
Variable	Coefficient	t-Statistic	Coefficient	t-Statistic	Coefficient	t-Statistic	Coefficient	t-Statistic
Mean model:\(\Delta {y}_{t}\)
\({\psi }_{11}\)	− 0.0533	− 1.1621	− 0.0423	− 1.1576	0.0295	0.8131	0.0431	1.4585
\({\psi }_{21}\)	0.0163	0.2715	− 0.0921	− 1.9249	− 0.0087	− 1.1249	0.1501	5.4719
\({\phi }_{y,t}\)	0.2760	1.4423	0.2418	1.3526	0.0509	1.5514	0.2348	3.3055
Mean model:\(\Delta {SI}_{t}\)
\({\psi }_{12}\)	− 0.0296	− 1.2960	− 0.0072	− 0.3211	− 0.1757	− 2.2958	− 0.0307	− 1.2171
\({\psi }_{22}\)	− 0.3152	− 11.4994	− 0.2961	− 12.0099	0.3413	12.7230	0.0485	2.1521
\({\phi }_{x,t}\)	− 0.2489	− 2.3169	− 0.2068	− 2.1177	− 0.0041	− 0.0373	− 0.0244	− 0.3608
Variance model
\({c}_{11}\)	1.1679	5.1402	3.0346	8.8474	0.2352	6.4751	1.5404	15.7764
\({c}_{21}\)	− 1.0336	− 3.5236	0.0476	0.1526	1.0976	3.2526	0.0558	0.4194
\({c}_{22}\)	< 0.0000	< 0.0000	1.7892	6.4882	1.9747	9.4298	< 0.0000	< 0.0000
\({a}_{11}\)	0.2643	6.8182	0.0744	0.8680	0.2983	6.8604	1.0955	21.8817
\({a}_{12}\)	− 0.0432	− 2.3590	− 0.0118	− 0.5042	− 0.5038	− 2.1890	− 0.0058	− 0.1240
\({a}_{21}\)	− 0.0389	− 0.9888	0.2942	3.5497	0.0115	0.5505	0.6855	12.9573
\({a}_{22}\)	0.3554	6.5266	0.5825	5.7487	0.9085	8.1943	0.0708	1.7190
\({b}_{11}\)	0.9399	59.8402	0.6678	7.6453	0.9243	57.3504	− 0.0415	− 1.7054
\({b}_{12}\)	0.0625	6.3790	0.1372	1.7091	0.1141	1.0714	0.7209	25.5754
\({b}_{21}\)	0.0042	0.2552	− 0.3379	− 6.1058	− 0.0360	− 2.2198	− 0.4588	− 9.0735
\({b}_{22}\)	0.8858	19.7042	0.6750	10.1659	0.4313	8.1905	0.0294	0.6696

	\(\Delta WEPI\)		\(\Delta Gold\)		\(\Delta GSCI\)		\(\Delta REITs\)
Variable	Coefficient	t-Statistic	Coefficient	t-Statistic	Coefficient	t-Statistic	Coefficient	t-Statistic
Mean model:\(\Delta {y}_{t}\)
\({\psi }_{11}\)	0.0978	2.3561	− 0.0058	− 0.1429	− 0.0315	− 0.8400	− 0.0094	− 0.2601
\({\psi }_{21}\)	0.1455	9.8857	0.0248	3.4011	− 0.1217	− 8.7510	0.0007	0.0577
\({\phi }_{y,t}\)	0.2515	3.7029	0.0240	0.6404	0.2655	6.8881	0.0493	1.0572
Mean model:\(\Delta {SI}_{t}\)
\({\psi }_{12}\)	− 0.0107	− 0.1916	0.3073	3.7971	− 0.3613	− 5.8832	− 0.1672	− 3.2748
\({\psi }_{22}\)	0.0329	1.3041	− 0.3273	− 10.3493	− 0.2498	− 8.1015	0.3362	10.6693
\({\phi }_{x,t}\)	− 0.1742	− 1.8176	− 0.5541	− 5.5983	0.2382	3.8242	− 0.4191	− 3.8667
Variance model
\({c}_{11}\)	− 0.0099	− 0.0590	0.1952	3.2341	− 0.2776	− 6.4074	− 0.2321	− 4.8514
\({c}_{21}\)	0.7872	6.1823	2.0792	16.5220	− 0.7497	− 2.4348	0.0120	0.0258
\({c}_{22}\)	0.9233	18.2396	− 0.0928	− 1.5552	− 1.0116	− 4.1215	2.2139	20.6657
\({a}_{11}\)	− 0.1374	− 2.9882	0.2061	4.9505	0.1175	2.8674	0.2602	5.4771
\({a}_{12}\)	0.6948	11.6201	− 0.7285	− 3.8955	− 1.5536	− 15.7887	0.3813	3.2593
\({a}_{21}\)	− 0.1341	− 6.5489	− 0.0409	− 1.9071	− 0.2157	− 4.1920	− 0.0233	− 0.6120
\({a}_{22}\)	− 0.0514	− 2.2188	1.4240	7.0544	− 1.3989	− 9.1630	1.2935	7.0597
\({b}_{11}\)	0.9523	64.8906	0.9551	65.1453	0.9436	105.4076	0.9440	58.1046
\({b}_{12}\)	− 0.2183	− 8.1438	− 0.4643	− 2.8941	− 0.0285	− 0.4404	− 0.0056	− 0.0863
\({b}_{21}\)	0.1738	6.7792	0.0306	2.5923	− 0.0645	− 2.4734	− 0.0135	− 0.6474
\({b}_{22}\)	0.7626	27.6339	0.3100	7.2032	0.2372	7.9817	0.3437	7.3629

This table shows the relationships between risk factors and asset returns.\(\Delta CCI\),\(\Delta BTC\),\(\Delta WSPI\),\(\Delta WTI\),\(\Delta WEPI\),\(\Delta Gold\),\(\Delta GSCI\), and\(\Delta REITs\)respectively denote the return of cryptocurrency index, Bitcoin price, MSCI World SPI, WTI crude oil spot price, MSCI World Energy Price Index, gold spot price, S&P Goldman Sachs Commodity Index, and FTSE NAREIT All REITs index.\(\Delta TC\)denotes the rate of change of total infected cases. Number in bold stands for significance at 5%

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