碳交易市场、能源市场与低碳股票市场的风险溢出效应——基于联合溢出指数模型的实证研究

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

摘要/Abstract

摘要：

随着全国统一的碳交易市场建设步伐的逐步加快，科学衡量不同市场之间的风险溢出效应对于有效应对复杂多变的市场情况尤为重要。文章运用联合溢出指数模型，实证发现碳交易市场、能源市场与低碳股票市场之间存在风险溢出效应，且不同市场间的方向性溢出效应和净溢出效应存在明显的时变特征；相较于我国，欧盟碳交易市场的抗风险能力更强。对此，应建立碳交易市场、能源市场与低碳股票市场之间的风险预警机制，完善我国碳交易市场的政策体系和相关金融机构的信息披露机制，从而有效防范跨市场间的金融风险。

关键词: 碳交易市场, 能源市场, 中国低碳指数, 联合溢出效应

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

中图分类号:

F832

龚振庭, 陈妍蓓. 碳交易市场、能源市场与低碳股票市场的风险溢出效应——基于联合溢出指数模型的实证研究[J]. 新疆财经, 2023, (5): 16-28.

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.

图/表 9

表1

表2

表3

静态溢出指数/%"

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

表3

图1

图2

图3

表4

不同预测期数的静态溢出指数/%"

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

表4

图4

图5

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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