考虑多尺度多状态的原油市场与油轮市场动态相依性及风险传染研究

doi:10.16381/j.cnki.issn1003-207x.2022.2287

摘要/Abstract

摘要：

当下国际航运市场格局及需求出现巨大变化，国际原油价格和油轮运价波动剧烈，有效控制风险是油轮市场投资组合多样化和风险管理的重要手段。本文同时考虑到关注不同时间范围市场波动的市场参与者、油轮船型对相依结构的影响及可能存在发生结构变化的情况，通过构建基于MODWT分解的时变MRS Copula模型，刻画原油市场与油轮市场间的多尺度多状态动态相依关系，并运用尾部风险依赖系数度量多尺度多状态下两市场间的风险传染效应。结果表明：（1）相依结构。不同时间尺度下原油市场与油轮市场间的相依结构均存在两种状态，说明不同时间尺度下原油市场与油轮市场间的相依结构发生变化。（2）相依性特征。不同时间尺度下油轮市场内部及原油市场与油轮市场间的动态相依性存在显著差异性、时变性和非对称性。随时间尺度的增大，相依性波动区间越来越小，最后趋于稳定。（3）油轮市场内部风险传染效应。随着时间尺度的增大，两种状态下的油轮市场内部尾部风险波动程度越来越小，最后在长期下趋于稳定，而风险传染效应随时间尺度的增大而增大。（4）原油市场与油轮市场间的风险传染效应。不同时间尺度下，原油市场与油轮整体市场间的时变尾部风险均值大于原油市场与油轮细分市场间，即油轮整体市场更易受到原油市场的影响。此外，两种状态下的时变尾部风险呈现非对称性和高相依状态大于低相依状态的特点。其中，高相依状态下的风险传染效应随时间尺度的增大而减小。

关键词: 油轮市场, 原油市场, 风险传染, MODWT分解, 时变MRS Copula模型

Abstract:

In this paper， considering that market participants are concerned about market volatility in different time frames， the influence of tanker type on the dependence structure and the possibility of structural changes， a time-varying MRS copula model based on MODWT decomposition is constructed to describe the multi-state dynamic dependence relationship between crude oil market and tanker market， and the tail risk dependence coefficient is used to measure the contagion effect of multi-scale and multi-state tail risk. It reveals the risk contagion change rule between crude oil market and tanker market. Finally， the time-varying MRS copula model is compared with the traditional copula model in order to verify the validity of the time-varying MRS copula model in studying the dependence between crude oil price and tanker market. The results show that：（1） There are two states （high and low dependence states） of the dependence structure between crude oil market and tanker market at different scales， indicating structural changes in the dependence structure between crude oil market and tanker market at different scales. （2） As the time scale increases， the degree of tail risk volatility within the tanker market becomes less and less， and finally stabilizes at the long-term scale， while the risk contagion effect increases with the increase of the time scale. （3） The mean value of time-varying tail risk between the crude oil market and the overall tanker market at different time scales is greater than that between the crude oil market and the tanker segment， indicating that the overall tanker market is more vulnerable to the crude oil market. In addition， the time-varying tail risks in both states show asymmetry and the high-dependence state is larger than the low-dependence state. Among them， the risk contagion effect in the high-dependence state decreases with increasing time scale.

Key words: tanker market, crude oil market, risk contagion, MODWT decomposition, time-varying MRS copula model

中图分类号:

薛凯丽, 匡海波, 孟斌. 考虑多尺度多状态的原油市场与油轮市场动态相依性及风险传染研究[J]. 中国管理科学, 2025, 33(7): 54-67.

Kaili Xue, Haibo Kuang, Bin Meng. Study on Dynamic Dependence and Risk Contagion Effect of Crude Oil Market and Tanker Market Considering Multi-scale and Multi-state[J]. Chinese Journal of Management Science, 2025, 33(7): 54-67.

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市场类型		市场名称	指标	数据来源	类型
原油市场		Brent原油市场	Brent原油期货	Wind	月度
原油市场		WTI原油市场	WTI原油期货	Wind	月度
油轮市场	油轮整体市场	原油油轮市场	BDTI (波罗的海原油运价指数)	Clarksons	月度
	油轮整体市场	成品油油轮市场	BCTI (波罗的海成品油运价指数)	Clarksons	月度
	油轮细分市场	VLCC型油轮市场	VLCC Tanker (选取航线TD15: 260000t West Africa - China)	Clarksons	月度
		阿芙拉型油轮市场	Aframax Tanker (选取航线TD9: 70000mt, Caribbean to US Gulf)	Clarksons	月度
		巴拿马型油轮市场	Panamax Tanker (选取航线TC5:55000mt, CPP/UNL naphtha condensate, Middle East/Japan)	Clarksons	月度
		苏伊士型油轮市场	Suezmax Tanker (选取航线TD6:135000mt, Black Sea/Mediterranean)	Clarksons	月度

统计量	r_Brent	r_WTI	r_BDTI	r_BCTI	r_VLCC	r_Aframax	r_Panamax	r_Suezmax
均值	0.3303	0.3094	-0.0226	0.2188	-0.1477	-0.0327	0.2524	-0.0784
中值	1.2798	1.7945	-0.5129	-1.0773	0.3306	-1.5025	0.3863	1.2144
最大值	35.6977	63.3269	56.9910	50.1292	90.6575	70.9432	68.5807	92.3002
最小值	-63.3933	-78.1866	-57.8084	-70.1012	-91.4878	-87.7757	-113.6044	-77.0168
标准差	10.2021	11.8259	16.4442	15.5255	20.3595	25.5776	20.8838	24.5681
偏度	-1.4549	-1.0037	0.1349	0.0152	0.2674	-0.1471	-0.4852	0.0439
峰度	11.0151	15.3572	4.9196	5.5277	7.6859	3.6109	7.2853	4.7488
J-B检验	618.0228	1332.2060	31.9401	54.3161	189.0685	3.9079	164.0962	26.0603
ADF	-11.0802^***	-11.5743^***	-11.3384^***	-11.6977^***	-14.4317^***	-13.3355^***	-12.8128^***	-12.3066^***
ARCH	8.0660	26.1399	5.8752	13.1681	5.4215	12.5833	11.4763	3.1792
	[0.0004]	[0.0000]	[0.0162]	[0.0004]	[0.0209]	[0.0005]	[0.0000]	[0.0437]
样本量	204	204	204	204	204	204	204	204

参数	r_Brent	r_WTI	r_BDTI	r_BCTI	r_VLCC	r_Aframax	r_Panamax	r_Suezmax
a	-0.2359	-0.3240	-0.5798	-0.5680	-0.6887	-0.5162	0.6657	0.6654
a	(0. 3705)	(0.5273)	(0.1824)	(0.1829)	(0.1779)	(0.1897)	(0.0737)	(0.0599)
b	0.4124	0.4324	0.7557	0.7326	0.7899	0.3899	-0.9310	-0.9288
b	(0.3468)	(0.5076)	(0.1336)	(0.1399)	(0.1561)	(0.2392)	(0.0370)	(0.0314)
α	0.6751	0.5756	0.2462	0.3579	0.6065	0.8157	0.6857	0.6432
α	(0.1309)	(0.1754)	(0.1634)	(0.1941)	(0.2342)	(0.1710)	(0.1722)	(0.1952)
β	0.1980	0.2018	0.6028	0.4969	0.1625	0.1092	0.2112	0.2055
β	(0.1087)	(0.1157)	(0.2031)	(0.2420)	(0.1108)	(0.0920)	(0.1071)	(0.1253)
Dof	5.8101	5.3430	5.5581	4.9535	3.6322	15.5380	5.1129	4.7100
ARCH	1.7865	1.0988	0.5673	0.4544	0.2249	2.3687	1.1265	0.1958
ARCH	[0.1092]	[0.3679]	[0.6653]	[0.7115]	[0.5083]	[0.0871]	[0.1479]	[0.6096]

时间尺度	收益对	最优模型	时变参数	最小值	最大值	均值	标准差	时变参数	最小值	最大值	均值	标准差
d₁时间尺度(短期)	(u_Brent, v_Aframax)	时变MRS Clayton	θ⁰	0.0046	6.1223	1.9650	1.1090	θ¹	0.0001	0.6303	0.0796	0.1041
	(u_Brent, v_Panamax)	时变MRS Clayton	θ⁰	0.0001	36.8231	12.3186	10.5259	θ¹	0.0001	1.1028	0.1690	0.2193
	(u_Brent, v_Suezmax)	时变MRS Clayton	θ⁰	0.0001	10.0100	4.5858	4.5921	θ¹	0.0001	0.0296	0.0039	0.0046
	(u_Brent, v_VLCC)	时变MRS Clayton	θ⁰	0.0001	37.1588	12.8850	10.6466	θ¹	0.0001	2.4148	1.1209	0.5045
d₂时间尺度(中期)	(u_Brent, v_Aframax)	时变MRS SJC Copula	τ⁰_L	0.0000	0.8781	0.2572	0.2356	τ¹_L	0.0000	0.0010	0.0010	0.0001
	(u_Brent, v_Aframax)	时变MRS SJC Copula	τ⁰_U	0.0000	0.9858	0.6024	0.3275	τ¹_U	0.0000	0.0010	0.0010	0.0001
	(u_Brent, v_Panamax)	时变MRS SJC Copula	τ⁰_L	0.0000	0.9493	0.7944	0.1079	τ¹_L	0.0000	0.0010	0.0010	0.0001
	(u_Brent, v_Panamax)	时变MRS SJC Copula	τ⁰_U	0.0002	0.0012	0.0010	0.0001	τ¹_U	0.0002	0.0010	0.0010	0.0001
	(u_Brent, v_Suezmax)	时变MRS Clayton	θ⁰	0.0001	55.9061	17.2179	15.6236	θ¹	0.0001	1.8828	0.1193	0.1937
	(u_Brent, v_VLCC)	时变MRS Clayton	θ⁰	0.0001	45.1563	12.9884	11.2706	θ¹	0.0001	2.3159	0.2912	0.3899
d₄时间尺度(长期)	(u_Brent, v_Aframax)	时变MRS SJC Copula	τ⁰_L	0.0005	0.9867	0.6066	0.3562	τ¹_L	0.0005	0.0011	0.0010	0.0000
	(u_Brent, v_Aframax)	时变MRS SJC Copula	τ⁰_U	0.0000	0.2897	0.1186	0.0640	τ¹_U	0.0000	0.0010	0.0010	0.0001
	(u_Brent, v_Panamax)	时变MRS Clayton	θ⁰	0.0001	49.4121	14.2155	12.9225	θ¹	0.0001	4.2503	1.5005	0.9502
	(u_Brent, v_Suezmax)	时变MRS SJC Copula	τ⁰_L	0.0000	0.9758	0.9090	0.0735	τ¹_L	0.0000	0.0010	0.0010	0.0001
	(u_Brent, v_Suezmax)	时变MRS SJC Copula	τ⁰_U	0.0009	0.0010	0.0010	0.0000	τ¹_U	0.0009	0.0010	0.0010	0.0000
	(u_Brent, v_VLCC)	时变MRS SJC Copula	τ⁰_L	0.0010	0.9047	0.1204	0.2116	τ¹_L	0.0010	0.0654	0.0013	0.0045
	(u_Brent, v_VLCC)	时变MRS SJC Copula	τ⁰_U	0.0032	0.3824	0.1296	0.0967	τ¹_U	0.0010	0.0912	0.0014	0.0063

时间尺度	收益对	尾部风险(S₀)	最小值	最大值	均值	标准差	尾部风险(S₁)	最小值	最大值	均值	标准差
d₁ 时间尺度 (短期)	(u_BTI, v_Aframax)	λ⁰_L	0.1474	0.5381	0.2767	0.0842	λ¹_L	0.4801	0.9148	0.6878	0.0737
	(u_BTI, v_Aframax)	λ⁰_U	0.0479	0.4080	0.0603	0.0266	λ¹_U	0.4080	0.8226	0.7124	0.0872
	(u_BTI,v_Panamax)	λ⁰_L	0.1588	0.4048	0.1829	0.0209	λ¹_L	0.4048	0.8643	0.8415	0.0340
	(u_BTI,v_Panamax)	λ⁰_U	0.0614	0.7607	0.3006	0.1766	λ¹_U	0.3134	0.9475	0.7595	0.1572
	(u_BTI,v_Suezmax)	λ⁰_L	0.4355	0.7290	0.6310	0.0421	λ¹_L	0.1646	0.5118	0.2971	0.0383
	(u_BTI,v_Suezmax)	λ⁰_U	0.0650	0.9313	0.6428	0.2026	λ¹_U	0.0103	0.6882	0.2644	0.1613
d₂ 时间尺度 (中期)	(u_BTI, v_Aframax)	λ⁰_L	0.0612	0.8925	0.5219	0.1613	λ¹_L	0.0010	0.3657	0.0028	0.0255
	(u_BTI, v_Aframax)	λ⁰_U	0.0800	0.9283	0.5947	0.1572	λ¹_U	0.0049	0.4725	0.0906	0.0631
	(u_BTI,v_Panamax)	λ⁰_L	0.2187	0.8101	0.7138	0.0483	λ¹_L	0.0010	0.2187	0.0021	0.0152
	(u_BTI,v_Panamax)	λ⁰_U	0.0257	0.8695	0.5679	0.1731	λ¹_U	0.0010	0.0257	0.0011	0.0017
	(u_BTI,v_Suezmax)	λ⁰_L	0.0677	0.9567	0.7401	0.1414	λ¹_L	0.0294	0.8354	0.3636	0.2219
	(u_BTI,v_Suezmax)	λ⁰_U	0.5389	0.9549	0.8411	0.0544	λ¹_U	0.1897	0.6584	0.4050	0.0645
d₄ 时间尺度 (长期)	(u_BTI, v_Aframax)	λ⁰_L	0.3616	0.8997	0.8823	0.0376	λ¹_L	0.1416	0.3616	0.1728	0.0181
	(u_BTI, v_Aframax)	λ⁰_U	0.5455	0.8834	0.8632	0.0248	λ¹_U	0.2161	0.5455	0.2641	0.0274
	(u_BTI,v_Panamax)	λ⁰_L	0.4798	0.6927	0.5931	0.0366	λ¹_L	0.6927	0.9345	0.8935	0.0226
	(u_BTI,v_Panamax)	λ⁰_U	0.3181	0.9064	0.8049	0.1199	λ¹_U	0.0385	0.7510	0.1136	0.0667
	(u_BTI,v_Suezmax)	λ⁰_L	0.6304	0.8601	0.8306	0.0313	λ¹_L	0.0010	0.7937	0.0050	0.0555
	(u_BTI,v_Suezmax)	λ⁰_U	0.1206	0.8839	0.7892	0.1146	λ¹_U	0.0010	0.7112	0.0047	0.0497