Table 3.

VAR-ADCC-GARCH analysis of climate bond and gold markets.

Variables $\downarrow$	Climate bond	Gold
$r_{t-1}^b$	0.0947 (.00)***	0.1053 (.00)***
$r_{t-1}^g$	−0.0082 (.11)	0.0074 (.73)
${\epsilon }_{b,t-1}^2$	0.0402 (.00)***	1.4286 (.00)***
${\epsilon }_{g,t-1}^2$	0.0015 (.00)***	0.0527 (.00)***
$h_{t-1}^b$	0.9389 (.00)***	−2.0853 (.00)***
$h_{t-1}^g$	−0.0024 (.00)***	0.9225 (.00)***
${\theta }_1$	0.0091 (.00)***
${\theta }_2$	0.2464 (.00)***
${\theta }_3$	0.0037 (.00)***
Log Likelihood	−286.15
ARCH-LM	0.88 (.59)

Notes: This table reports the outcomes for the VAR-ADCC-GARCH model for the bond-gold combination. $r_{t-1}^g$ refers to the return on the gold index at time t-1 and $r_{t-1}^b$ denotes the same for the climate bond index. In addition, $h_{t-1}^b$ measures the conditional variance of the bond price returns at time t-1 and $h_{t-1}^g$ indicates the conditional variance of gold market returns at time t-1. The squared error terms ${\epsilon }_{g,t-1}^2$ and ${\epsilon }_{b,t-1}^2$ measure the effects of unexpected news or shocks in gold and bond markets, respectively. ARCH-LM statistics are used to test the null hypothesis that the return series exhibit heteroscedasticity at lag 10. ***, ** and * indicate statistical significance at 1 %, 5 % and 10 % levels, respectively. Values in parentheses indicate p-values.