Table 2.

Descriptive statistics of VaR and detected changes (τ = 5%).

	Average	Median	S.D.	Min	Max	Hitwhole	Hittraining	Hitcovid	Change date
MSCIUS	−0.0296	−0.0145	0.0359	−0.2099	−0.0082	5.17%	2.30%	8.05%	09-Mar
MSCIEU	−0.0231	−0.0145	0.0226	−0.1462	−0.0092	4.60%	4.60%	4.60%	24-Mar
MSCICN	−0.0241	−0.0206	0.0092	−0.0590	−0.0158	4.60%	1.15%	8.05%	23-Mar
Bitcoin	−0.0566	−0.0501	0.0190	−0.1750	−0.0441	5.75%	5.75%	5.75%	–
Gold	−0.0155	−0.0126	0.0090	−0.0504	−0.0074	5.75%	4.60%	6.90%	–
EUR-USD	−0.0058	−0.0049	0.0026	−0.0180	−0.0035	5.75%	6.90%	4.60%	25-Mar
CNY-USD	−0.0042	−0.0040	0.0008	−0.0087	−0.0038	5.17%	3.45%	6.90%	–
Oil	−0.0485	−0.0324	0.0463	−0.2806	−0.0217	5.75%	3.45%	8.05%	18-Mar
Soybean	−0.0162	−0.0154	0.0024	−0.0253	−0.0132	5.17%	3.45%	6.90%	–
T-Bill	0.0041	0.0042	0.0013	0.0001	0.0055	5.75%	0	11.49%	23-Mar

Note: VaR estimators for asset i at quantile τ are calculated through ${\mathrm{VaR}}_{i,t}^{\tau }={\widehat{\sigma }}_{i,t}{\epsilon }_i^{\tau }$. The conditional volatility ${\widehat{\sigma }}_{i,t}$ is obtained by fitting a GARCH(1,1) model given a general presence of the conditional heteroscedasticity. The unconditional quantile for the error ε_i^τ is obtained from a bootstrapped distribution by re-sampling the historical residuals for 1000 times. The violations/hits are identified by the indicator function $\mathbb{I}\left(r_{i,t}<{\mathrm{VaR}}_{i,t}^{\tau }\right)$. All change dates are in the year 2020.