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Table 6 DCC-GARCH model estimation results

From: Half-day trading and spillovers

  \( {R}_{m,t}^c \) \( {R}_{a,t}^c \) \( {R}_{d,t}^c \)
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)
  1. 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