The Spillover of Carbon Trading Market， Energy Market and Low Carbon Stock Market—An Empirical Study Based on the Joint Spillover Index Model

doi:10.16716/j.cnki.65-1030/f.2023.05.002

Abstract

Abstract:

With the gradual acceleration of the construction of a unified carbon trading market across China, scientifically measuring the risk spillover effects between different markets is particularly important for effectively responding to complex and ever-changing market conditions. The paper uses a joint spillover index model to empirically find that there is a risk spillover effect between the carbon trading market, energy market, and low-carbon stock market, and the directional spillover effect and net spillover effect between different markets have obvious time-varying characteristics. Compared with China, the EU carbon trading market has a stronger ability to resist risks. In this regard, a risk warning mechanism should be established between the carbon trading market, energy market, and low-carbon stock market, and the policy system construction of China’s carbon trading market and the information disclosure mechanism of relevant financial institutions should be improved to effectively prevent cross market financial risks.

Key words: carbon trading market, energy market, China Low Carbon Index, joint spillover effects

CLC Number:

F832

GONG Zhenting, CHEN Yanbei. The Spillover of Carbon Trading Market， Energy Market and Low Carbon Stock Market—An Empirical Study Based on the Joint Spillover Index Model[J]. Finance & Economics of Xinjiang, 2023, (5): 16-28.

Figures/Tables 9

指标	LCI	EUA	COAL	OIL	SZA	SHEA	GDEA	HBEA	$S • → i j n t$
LCI	99.02	0.18	0.01	0.23	0.36	0.04	0.07	0.10	1.03
EUA	0.38	98.70	0.03	0.34	0.04	0.23	0.14	0.13	1.28
COAL	0.71	0.02	98.14	0.70	0.12	0.07	0.20	0.05	1.86
OIL	1.22	6.35	0.30	90.70	0.09	0.64	0.34	0.36	9.24
SZA	0.36	0.09	0.12	0.17	98.37	0.37	0.15	0.38	1.65
SHEA	0.43	0.13	0.05	0.80	0.38	97.44	0.69	0.08	2.55
GDEA	0.06	0.16	0.13	0.42	0.01	0.70	98.40	0.12	1.59
HBEA	0.11	0.18	0.22	0.40	0.74	0.08	0.18	98.09	1.92
$S • ← i j n t$	3.27	7.11	0.86	3.06	1.73	2.13	1.77	1.22	jSOI=2.64
$S n e t, i j n t$	2.23	5.83	-1.00	-6.19	0.08	-0.42	0.18	-0.70

预测期	变量	LCI	EUA	COAL	OIL	SZA	SHEA	GDEA	HBEA
H=25	$S • ← i j n t$	1.03	1.28	1.86	9.24	1.65	2.55	1.59	1.92
	$S • ← i j n t$	3.27	7.11	0.86	3.06	1.73	2.13	1.77	1.22
	$S n e t, i j n t$	2.23	5.83	-1.00	-6.19	0.08	-0.42	0.18	-0.70
H=50	$S • ← i j n t$	1.03	1.28	1.86	9.24	1.65	2.55	1.59	1.92
	$S • → i j n t$	3.27	7.11	0.86	3.06	1.73	2.13	1.77	1.22
	$S n e t, i j n t$	2.23	5.83	-1.00	-6.19	0.08	-0.42	0.18	-0.7

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变量	均值	中位数	标准差	偏度	峰度	JB检验	观察值
LCI	-0.000525	-0.000435	0.010165	0.387307	8.443529	2128.839	1690
EUA	-0.001729	-0.001441	0.021936	0.688489	11.480250	5197.499	1690
COAL	0.000626	0.000437	0.013578	-1.561218	22.763070	28189.790	1690
OIL	0.000215	0.000798	0.020045	0.031162	28.197980	44710.510	1690
SZA	-0.000922	0.000000	0.328548	0.384144	22.733410	27462.350	1690
SHEA	0.000077	0.000000	0.027245	-0.298728	20.088610	20588.260	1690
GDEA	0.000797	0.000264	0.022756	-0.272974	10.188700	3659.936	1690
HBEA	0.000412	0.000000	0.022840	-0.165766	9.319908	2820.269	1690