Table 6.

DCC-GARCH model estimation results

	$R_{m,t}^c$	$R_{a,t}^c$	$R_{d,t}^c$
Mean equation
γi, 11	0.017 (0.700)	− 0.165*** (− 7.071)	1.063 × 10− 3 (0.044)
γi, 12	0.280*** (10.620)	− 0.044** (− 2.443)	0.238*** (7.130)
γi, 21	− 0.026 (− 1.103)	9.005 × 10− 3 (0.371)	− 0.010 (− 0.602)
γi, 22	−0.042* (− 1.814)	−0.048** (− 2.098)	−0.044* (− 1.931)
Variance equation
α1	0.044*** (2.693)	0.077*** (5.202)	0.062*** (4.145)
α2	0.186*** (6.794)	0.182*** (6.872)	0.183*** (6.829)
β1	0.949*** (48.420)	0.923*** (67.550)	0.938*** (69.440)
β2	0.776*** (30.100)	0.778*** (31.160)	0.777*** (30.700)
θ1	4.783 × 10− 5 (0.005)	0.042* (1.928)	2.829 × 10− 3 (0.242)
θ2	0.842 (0.304)	0.499** (2.478)	0.848*** (16.810)

Notes. This table shows the estimation results of the DCC-GARCH model. The maximum likelihood estimation is applied, and the estimation method is the two-step approach. The results are converged within 100 iterations. The sample period spans from January 1, 2010, to March 31, 2020. $R_{m,t}^c$, $R_{a,t}^c$, and $R_{d,t}^c$ denote different $R_{i,t}^c$ in the mean equation of the DCC-GARCH model. The estimations of the constants in the mean and variance equations are omitted. The t-statistics of the elements are shown in parenthesis. One, two and three asterisks (*), respectively, indicate that the t-values are significant at the 0.1, 0.05, and 0.01 level. Some less relevant parameter estimates are omitted