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姓 名: 张跃军
系 别: 金融工程系
职 称: 教授,博士生导师
办 公 室: 工商管理学院
办公电话: 86-731-88822899
移动电话:  
E-mail: zyjmis@126.com

个人简介

张跃军,湖南安仁人,博士、教授、博士生导师,长江学者奖励计划青年学者(2016年)、国家高层次人才特殊支持计划(即万人计划)青年拔尖人才(2014年)、国家自然基金委优秀青年基金获得者(2013年)、湖南省湖湘青年英才支持计划人选(2016年)、北京市中青年社科理论人才百人工程人选(2012年)、北京市优秀人才培养资助计划人选(2011年)。

2009年毕业于中国科学院科技政策与管理科学研究所(管理科学与工程专业),获管理学博士学位。博士毕业后,进入北京理工大学管理与经济学院工作,历任讲师、副教授、博士生导师。2014年加盟湖南大学工商管理学院,任教授、博士生导师。2015年获得湖南省首届我最喜爱的青年教师

张跃军博士主要从事石油金融、碳金融、能源经济复杂系统建模等领域的研究工作。现已主持国家自然科学基金(优秀青年基金项目、面上项目和青年项目)、万人计划项目、高等学校博士学科点专项科研基金、教育部人文社会科学研究基金等10余项;并作为子课题负责人参与承担国家973课题、国家科技支撑计划项目、国家自然基金委重大国际合作项目和重点项目等20余项。

截至2016年底,张跃军博士已以第一作者或通讯作者在国内外学术期刊发表论文70余篇,其中在Energy Economics、Applied Energy、Energy Policy、Annals of Operations Research等国际一流学术期刊发表SSCI/SCI论文40余篇,6篇论文入选Elsevier网站统计的引用最高/最热门论文(如 Most Cited Articles、Top25 Hottest Articles);7篇论文上榜ESI数据库的热点论文或高被引论文;论文被美国斯坦福大学研究生课程列为授课材料;论文单篇最高被引200余次。主编或参与完成专著 9 部(主编2部);撰写10余份政策咨询报告被中办、国办、国家能源局采用,多份报告得到国家领导人批示。

 近几年,研究成果获得湖南省社会科学优秀成果一等奖(排名第一)、高等学校科学研究优秀成果奖科技进步奖二等奖(排名第六)等荣誉。

兼任国际能源经济学会(IAEE)会员、中国双法研究会能源经济与管理研究分会副秘书长、中国系统工程学会能源资源系统工程分会常务理事、中国双法研究会青年工作委员会常务委员、中国管理科学与工程学会理事、中国能源研究会能源系统工程专业委员会委员等;8份国际学术期刊的客座主编、副主编或编委;30余份国际知名学术期刊审稿人。美国加州大学伯克利分校、美国加州大学劳伦斯伯克利国家实验室访问学者,新加坡国立大学能源研究所访问学者,东亚东盟经济研究中心(ERIA)项目专家。


招收博士生和硕士生的期望:
    诚邀志同道合、有理想、有追求、有探索精神的优秀青年相聚工商管理学院,共同探索、共同进步。期望报考学生:
        1. 人品厚道,与人为善,吃苦耐劳,诚实守信;
        2. 热爱研究,敬畏科研;
        3. 英语基础较好;
        4. 原专业为统计学、经济学、金融学、系统工程、自动化、计算科学或能源环境政策等。

 

课题组招聘博士后:

1. 研究方向
方向1:大数据环境下的石油金融研究
方向2:碳交易的社会经济影响研究

2.招聘要求
[1]已有博士学位,或近期能顺利完成答辩获得博士学位者,年龄35岁以下;
[2]管理科学、系统工程、能源环境、经济金融、计算机等相关专业背景;
[3]优秀的发表记录;
[4]热爱学术研究、工作积极、性格随和、善于合作。

3. 工作待遇
按照国家和湖南大学相关博士后管理办法执行,另加学院和课题组的科研补贴。

课题组详情请见:www.hnucrem.cn,有意申请者请将简历、代表性论文或成果发至zyjmis@126.com,并注明主题“应聘博士后”。

 

讲授课程

  能源经济学、金融监管理论与实务、定量风险管理、定量分析方法等。

研究领域

主要从事石油金融、碳金融、能源经济复杂系统建模等领域的研究工作。

 

研究成果

1. 部分国际期刊论文

[1]  Yue-Jun Zhang, Yan-Lin Jin, Julien Chevallier, Bo Shen. The effect of corruption on carbon dioxide emissions in APEC countries: a panel quantile regression analysis. Technological Forecasting and Social Change, 2016, 112: 220-227. (SSCI, IF=2.625)

Abstract: The relationship between corruption and CO2 emissions has been receiving increased attention in recent years, but little work has been conducted for the Asia-Pacific Economic Cooperation (APEC) countries even if they have determined to fight against corruption and address climate change. Using the quantile regression approach, this paper develops a panel data model for the effect of corruption on CO2 emissions in APEC countries. The empirical results show that, first of all, the effect of corruption on CO2 emissions is heterogeneous among APEC countries. Specifically, there is significant negative effect in lower emission countries, but insignificant in higher emission countries. Second, there exists an inverted U-shaped Environmental Kuznets Curve (EKC) between corruption and CO2 emissions, and the per capita GDP at the turning point of the EKC may increase when CO2 emissions increase. Finally, corruption may have not only a negative direct effect on CO2 emissions, but also a positive indirect effect through its effect on per capita GDP. The total effect appears positive, which indicates corruption may worsen environmental quality overall in APEC countries.

 

[2]Yue-Jun Zhang, Jun-Fang Hao, Juan Song. The CO2 emission efficiency, reduction potential and spatial clustering in China's industry: evidence from the regional level. Applied Energy, 2016, 174: 213-223. (SCI&SSCI, IF=7.182)

Abstract: Given the key role of industrial sectors in energy conservation and CO2 emission reduction in China, this paper evaluates the industrial CO2 emission efficiency, emission reduction potential and profits brought by emission reduction for the 30 provinces in China during 2005–2012. Moreover, the spatial clustering among those provinces is detected in terms of industrial CO2 emission efficiency. The results indicate that, first, the 30 provinces are not completely efficient regarding their industrial CO2 emission efficiency, and they can be categorized into three groups, i.e., the high, middle and low efficiency regions. Second, the northwest region has the hugest industrial CO2 emission reduction potential among the eight regions in China, which shows the biggest opportunity for CO2 emission reduction. Therefore, the central government should provide more policy support for this region. Finally, the industrial sectors of the 30 provinces exist significant spatial clustering in light of CO2 emission efficiency, which provides important implications for government to formulate regional industrial policies.

 

 [3]Yue-Jun Zhang, Ting Yao. Interpreting the movement of oil prices: driven by fundamentals or bubbles?. Economic Modelling, 2016, 55: 226-240. (SSCI, IF=0.997)

Abstract: Based on the historical data of crude oil, diesel and gasoline markets during November 2001–December 2015, this paper employs the state-space model and log-periodic power law (LPPL) model to explore the dynamic bubbles of oil prices and predict their crash time. The results indicate that, first, oil price bubbles only exist during November 2001–July 2008, and crude oil and diesel prices are significantly driven by bubbles, whereas gasoline prices are mainly driven by fundamentals. Second, the state-space model captures the time-varying bubbles of crude oil and diesel prices. Finally, the LPPL model well predicts the crash time of bubbles.

 

[4]Tian-Jian Yang, Yue-Jun Zhang*, Su Tang, Jing Zhang. How to assess and manage energy performance of numerous telecommunication base stations: evidence in China. Applied Energy, 2016, 164: 436-445. (SCI&SSCI, IF=7.182) (*为通讯作者)

Abstract: Existing calculated benchmarking methods and main energy performance assessment schemes often lack the practical ability to manage the energy performance of a vast number of widespread telecommunication base stations (TBSs). Therefore, on the basis of a TBS survey, this paper puts forward the dynamic simulation and sensitivity analysis method to allow the new rule “one energy benchmark for a group of similar TBSs” rather than the traditional rule “one benchmark for one assessed building”. The new method reasonably limits the number of benchmarks and a feasible benchmark system is established for managing numerous TBSs. The results indicate that, first, more than one million TBSs distributed in a large area of China can be divided into 448 typical scenarios. Second, the benchmarks for reasonable energy use of these scenarios can be organized into four simple benchmarking charts. Third, the attempt to establish further challenging energy benchmarks shows that the most energy-saving measure in TBSs, i.e., ventilation cooling, can fully eliminate the negative impact of poor configurations of envelops and cooling coefficients of performance (COP). Finally, establishing telecom industrial standards for locating the reasonable TBS energy consumption level even in giant countries appears feasible.

 

[5] Yue-Jun Zhang, Ya-Fang Sun. The dynamic volatility spillover between European carbon trading market and fossil energy market. Journal of Cleaner Production, 2016, 112(4): 2654–2663. (SCI, IF=5.715)

Abstract: With the rapid spread of carbon trading in the world, the interaction of carbon prices and fossil energy prices has raised growing attention, but little research has discussed their time-varying correlation and dynamic volatility spillover. This paper employs the threshold dynamic conditional correlation (DCC) generalized autoregressive conditional heteroscedasticity (GARCH) model and the full Baba, Engle, Kraft and Kroner (BEKK) GARCH model to explore these issues, for the daily data of European carbon futures prices and the three fossil energy prices (coal, natural gas and Brent oil) from January 2 2008 to September 30 2014. The results indicate that, first, there is significant unidirectional volatility spillover from coal market to carbon market and from carbon market to natural gas market, whereas there exists no significant volatility spillover between carbon market and Brent oil market. Second, carbon market and fossil energy markets have significantly positive correlation across time. Specifically, among the three fossil fuels, coal market has the highest correlation with carbon market, followed by natural gas and Brent oil markets. Finally, as for the three fossil fuels, their price decrease may have stronger impact on carbon price volatility than their price increase with the same degree, while there is asymmetric impact of carbon price increase and decrease only on Brent oil price volatility. These results may help investors to well configure their portfolios and manage their investment risks, and help emission trading installations to join in carbon market in a cost-effective way.

 

[6] Yue-Jun Zhang, Jun-Fang Hao. The evaluation of environmental capacity: evidence in Hunan province of China. Ecological Indicators, 2016, 60: 514–523. (SCI, IF=3.898)

Abstract: Environmental capacity paves the foundation for sustainable economic development. As the vital growth pole in the Rise Strategy of Central China, the environmental and economic construction of Hunan province proves to have enormous demonstration effect. In order to better understand the environmental condition in Hunan province, this study combines the information entropy theory and ecological comprehensive index to measure the environmental capacity of 14 administration divisions in Hunan province and 30 provinces across China in 2013. The results indicate that, first of all, the average environmental capacity of 14 administration divisions in Hunan province is relatively lower, i.e., 0.39. Second, Chang-Zhu-Tan city cluster in Hunan province exerts limited radiative and guiding effect on its surroundings; in particular, Xiangtan possesses a notably lower environmental capacity than other two cities, which hampers the integration process. Third, among the four types of environmental capacities concerned, i.e., population capacity, land capacity, resource capacity and waste assimilative capacity, waste assimilative capacity takes up the biggest weight, i.e., 0.31, indicating the most important role in environmental improvement. Finally, the environmental capacity of Hunan province ranks the 24th among the 30 provinces in China and the last in central China. Hunan should pay special attention to the expansion of waste assimilate capacity, so as to promote the overall environmental capacity.

 

[7] Yue-Jun Zhang, Hua-Rong Peng, Zhao Liu, Weiping Tan. Direct energy rebound effect for road passenger transport in China: A dynamic panel quantile regression approach. Energy Policy, 2015, 87: 303-313. (SCI&SSCI, IF=4.140) 

Abstract: The transport sector appears a main energy consumer in China and plays a significant role in energy conservation. Improving energy efficiency proves an effective way to reduce energy consumption in transport sector, whereas its effectiveness may be affected by the rebound effect. This paper proposes a dynamic panel quantile regression model to estimate the direct energy rebound effect for road passenger transport in the whole country, eastern, central and western China, respectively, based on the data of 30 provinces from 2003 to 2012. The empirical results reveal that, first of all, the direct rebound effect does exist for road passenger transport and on the whole country, the short-term and long-term direct rebound effects are 25.53% and 26.56% on average, respectively. Second, the direct rebound effect for road passenger transport in central and eastern China tends to decrease, increase and then decrease again, whereas that in western China decreases and then increases, with the increasing passenger kilometers. Finally, when implementing energy efficiency policy in road passenger transport sector, the effectiveness of energy conservation in western China proves much better than that in central China overall, while the effectiveness in central China is relatively better than that in eastern China.

 

[8] Yue-Jun Zhang, Jun-Fang Hao. The allocation of carbon emission intensity reduction target by 2020 among provinces in China. Natural Hazards, 2015, 79(2): 921–937. (SCI&SSCI, IF=1.833)

Abstract: According to the combined principles of fairness and efficiency, a comprehensive allocating indicator system is developed, and the TOPSIS approach is applied to allocate China’s 40–45 % carbon emission intensity (carbon emission per unit of GDP) reduction target by 2020. The results indicate that, first of all, the unequally weighted indicator system outperforms the equally weighted one according to regional developing situation in China; and the most important indicator affecting the allowance allocation is carbon reduction responsibility, followed by future development right and emission reduction efficiency. Second, China’s carbon emission intensity should be cut, but its absolute carbon emission volume may inevitably increase in the future due to the continuous economic growth, and we confirm that the western provinces may take the highest shares to increase carbon emissions, followed by the central, northeast and eastern provinces. Finally, in order to achieve the national target of carbon emission intensity reduction, the northeast and eastern provinces require reducing carbon emission intensity significantly from 2013 to 2020, while the central and western provinces should be given more developing room.

 

[9] Yue-Jun Zhang, Ao-Dong Wang, Weiping Tan. The impact of China's carbon allowance allocation rules on the product prices and emission reduction behaviors of ETS-covered enterprises. Energy Policy, 2015, 86: 176-185. (SCI&SSCI, IF=4.140) 

Abstract: It is an important task for China to allocate carbon emission allowance to realize its carbon reduction target and establish carbon trading market. China has designed several allocation rules within seven pilot regions. What influence those rules may cause is closely related with the enthusiasm of emission trading scheme (ETS) covered enterprises' participation in carbon market, and more importantly, with the mechanism design and sustainable development of carbon market. For this purpose, the multi-stage profit model is developed to analyze the ETS-covered enterprises' product prices and emission reduction behaviors under different allocation rules. The results show that, first, under the rules of grandfathering, self-declaration and auctioning, when deciding the optimal product price and optimal carbon emission reduction, those enterprises may focus on maximizing current stage profit; however, under the rule of benchmarking, those enterprises may care more about the impact of current decisions on the profit in next stage. Second, the optimal product price policy is positively correlated with the price of the same kind products, consumers' low-carbon awareness and government subsidy. Finally, along with the increase of carbon price, consumers' low-carbon awareness and government subsidy and the decrease of carbon emission cap, those enterprises tend to reduce carbon emissions.

 

[10] Yue-Jun Zhang, Yi-Song Huang. The multi-frequency correlation between EUA and sCER futures prices: evidence from the EMD approach. Fractals, 2015, 23(2): 1-18. (SCI&SSCI, IF=1.540)

Abstract: Currently European Union Allowances (EUA) and secondary Certified Emission Reduction (sCER) have become two dominant carbon trading assets for investors and their linkage attracts much attention from academia and practitioners in recent years. Under this circumstance, we use the empirical mode decomposition (EMD) approach to decompose the two carbon futures contract prices and discuss their correlation from the multi-frequency perspective. The empirical results indicate that, first, the EUA and sCER futures price movements can be divided into those triggered by the long-term, medium-term and short-term market impacts. Second, the price movements in the EUA and sCER futures markets are primarily caused by the long-term impact, while the short-term impact can only explain a small fraction. Finally, the long-term (short-term) effect on EUA prices is statistically uncorrelated with the short-term (long-term) effect of sCER prices, and there is a medium or strong lead-and-lag correlation between the EUA and sCER price components with the same time scales. These results may provide some important insights of price forecast and arbitraging activities for carbon futures market investors, analysts and regulators.

 

[11] Jin-Liang Zhang, Yue-Jun Zhang*, Lu Zhang. A novel hybrid method for crude oil price forecasting. Energy Economics, 2015, 49: 649-659. (SSCI, IF=3.199) *为通讯作者)

Abstract: Forecasting crude oil price is a challenging task. Given the nonlinear and time-varying characteristics of international crude oil prices, we propose a novel hybrid method to forecast crude oil prices. First, we use the ensemble empirical mode decomposition (EEMD) method to decompose international crude oil price into a series of independent intrinsic mode functions (IMFs) and the residual term. Then, the least square support vector machine together with the particle swarm optimization (LSSVM–PSO) method and the generalized autoregressive conditional heteroskedasticity (GARCH) model are developed to forecast the nonlinear and time-varying components of crude oil prices, respectively. Next, the forecasted crude oil prices of each component are summed as the final forecasted results of crude oil prices. The results show that, the newly proposed hybrid method has a strong forecasting capability for crude oil prices, due to its excellent performance in adaptation to the random sample selection, data frequency and structural breaks in samples. Furthermore, the comparison results also indicate that the new method proves superior in forecasting accuracy to those well-recognized methods for crude oil price forecasting.

 

[12] Yue-Jun Zhang, Ting Yao, Zi-Yi Wang. The bubble process of international crude oil futures prices: empirical evidence from the STAR model. International Journal of Global Energy Issues, 2015, 38(1/2/3): 109-125.  (EI)

Abstract: Since the 21st century, international crude oil price has continually reached the historical high with significant impact on the socio-economic development across the world. Whether there exists some bubbles in crude oil prices, how do the bubbles evolve over time and how much about the scale have become the focuses in academia and among practitioners. Under this circumstance, we employ the STAR model to analyse the WTI crude oil price bubbles from January 2003 to July 2013 and find that in the past decade, the bubbles always exist in the movement of WTI crude oil prices and with the crash of crude oil prices in the second half of 2008, the bubbles relieved significantly and the prices almost approached to the fundamental values, but with the following global economic recovery, the bubbles have emerged again in the wake of the upsurge of crude oil prices.

 

[13] Yue-Jun Zhang, Lu Zhang. Interpreting the crude oil price movements: evidence from the Markov regime switching model. Applied Energy, 2015, 143: 96-109. (SCI&SSCI, IF=7.182)

Abstract: Since 2009, global financial crisis has eased gradually and world economy has begun to recover slowly. Meanwhile, both Brent and WTI (West Texas Intermediate) crude oil prices have entered into a new round of increase and volatility, and the abnormal price spreads between them have been identified. Under this circumstance, this paper employs the Markov regime switching model with dynamic autoregressive coefficients to explore the price regimes of Brent and WTI after the financial crisis. Then it analyzes the causes of the abnormal spreads between the two benchmark crude oil prices based on the statistical observations of their typical regime differences. The results show that there are three main regimes in both Brent and WTI crude oil price returns, i.e., sharply downward, slightly downward and sharply upward regimes for Brent whilst sharply downward, relatively stable and sharply upward regimes for WTI. Meanwhile, the typical price regimes of Brent and WTI are the “sharply upward” and “relatively stable” regimes after the financial crisis, respectively. Besides, their different movement regimes in recent years are mainly attributed to their different market fundamental situations and the dynamics in crude oil markets, which also lead to the occurrence of their abnormal price spreads.

 

[14] Lan-Cui Liu, Gang Wu, Yue-Jun Zhang*. Investigating the residential energy consumption behaviors in Beijing: A survey study. Natural Hazards, 2015, 75(1): 243-263. (SCI&SSCI, IF=1.833) *为通讯作者)

Abstract: This paper investigates the residents’ direct and indirect energy consumption behaviors in Beijing, as well as the impact of age, educational background and income level on the behaviors. The results show that, first, there are a high proportion of residents who may support the policies and activities about consumption behaviors adjustment towards energy-saving and low-carbon pattern, but currently the residents’ awareness and behaviors are still not desirable. Second, the promotion of energy-saving appliance is effective to drive the energy conservation and emission reductions, and the current energy prices are higher but not effective to curb energy consumption and carbon emissions. Third, the direct energy consumption behaviors of older respondents and those with higher education background and income level generally tend to be more energy conservative than the younger respondents and other education and income level groups. The survey results may provide significant policy implications for the government and energy-saving product suppliers.

 

[15] Yue-Jun Zhang, Ya-Bin Da. The decomposition of energy-related carbon emission and its decoupling with economic growth in China. Renewable & Sustainable Energy Reviews, 2015, 41: 1255-1266. (SCI&SSCI, IF=8.050)

Abstract: In order to find the efficient ways to reduce carbon emission intensity in China, we utilize the LMDI method to decompose the changes of China׳s carbon emissions and carbon emission intensity from 1996 to 2010, from the perspectives of energy sources and industrial structure respectively. Then we introduce the decoupling index to analyze the decoupling relationship between carbon emissions and economic growth in China. The results indicate that, on the one hand, economic growth appeared as the main driver of carbon emissions increase in the past decades, while the decrease of energy intensity and the cleaning of final energy consumption structure played significant roles in curbing carbon emissions; meanwhile, the secondary industry proved the principal source of carbon emissions reduction among the three industries and had relatively higher potential. On the other hand, when the decoupling relationship is considered, most years during the study period saw the relative decoupling effect between carbon emissions and economic growth, which indicated that the reduction effect of inhibiting factors of carbon emissions was less than the driving effect of economic growth, and the economy grew with increased carbon emissions; there appeared the absolute decoupling effect in 1997, 2000 and 2001, which implied that the economy grew while carbon emissions decreased; whereas no decoupling effect was identified in 2003 and 2004.

 

[16] Yue-Jun Zhang, Ao-Dong Wang, Ya-Bin Da. Regional allocation of carbon emission quotas in China: evidence from the Shapley value method. Energy Policy, 2014, 74: 454-464. (SCI&SSCI, IF=4.140) 

Abstract: It is an important task for China to allocate carbon emission quotas among regions so as to realize its carbon reduction targets and establish the national cap-and-trade carbon market. Meanwhile, it is supposed to be cost-effective to jointly reduce China׳s carbon emissions through some collaborative activities among regions. Then a natural question is how to allocate the quotas among regions in light of the collaboration. For this purpose, the Shapley value method is adopted and the results show that, first, the regions with higher GDP, higher carbon outflow and higher carbon reduction connection should be allocated more carbon quotas. Moreover, when the collaboration is considered, the optimal allocation of carbon quotas among regions will change significantly compared to the basic quotas by the entropy method; and the Central region is allocated the largest proportion of carbon quota among regions, which indicates its largest radiation effect. Besides, the collaboration between the Central region and Northern coast region, and that between the Central region and the Eastern region should be paid close attention. These results may provide insightful support for decision makers to promote collaborative carbon reduction and allocate carbon quotas in China.

 

[17] Gang Wu, Yue-Jun Zhang*. Does China factor matter? An econometric analysis of international crude oil prices. Energy Policy, 2014, 72: 78-86. (SCI&SSCI, IF=4.140) *为通讯作者)

Abstract: Whether China’s crude oil imports are the culprit of oil price volatility these years has not been quantitatively confirmed. Therefore, this paper empirically investigates the role of China’s crude oil net imports in Brent price changes from October 2005 to November 2013 based on an econometric analysis. The results indicate that, during the sample period, China’s crude oil imports do not significantly affect Brent price changes, no matter in the long run or short run. Therefore, the blame for China’s crude oil imports to cause the dramatic fluctuations of international oil price has no solid evidence. Also, there exists significant uni-directional causality running from the Brent price to China׳s crude oil imports at the 5% level. Besides, the response of the Brent price to China׳s crude oil imports is found positive but slight, and the Brent price responds more significantly to US dollar exchange rate and OECD commercial inventory than to China’s crude oil imports in the short run. Finally, the contribution of China׳s crude oil imports to Brent price movement is about 10%, which is less than that of US dollar exchange rate but larger than that of Indian crude oil imports or OECD commercial inventory.

 

[18] Yue-Jun Zhang, Zhao Liu, Huan Zhang, Tai-De Tan. The impact of economic growth, industrial structure and urbanization on carbon emission intensity in China. Natural Hazards, 2014, 73(2): 579-595. (SCI&SSCI, IF=1.833) 

Abstract: China’s macroeconomic policy framework has been determined to ensure steady growth, adjust the industrial structure and advance the socioeconomic reforms in recent years. And urbanization is supposed to be one of the most important socioeconomic reform directions. Meanwhile, China also committed to reduce carbon emissions intensity by 2020, then it should be noted that what kind of impact of these policy orientations on carbon emission intensity. Therefore, based on the historical data from 1978 to 2011, this paper quantitatively studies the impact of China’s economic growth, industrial structure and urbanization on carbon emission intensity. The results indicate that, first, there is long-term cointegrating relationship between carbon emission intensity and other factors. And the increase in the share of tertiary industry [i.e., the ratio of tertiary industry value added to gross domestic product (GDP)] and economic growth (here we use the real GDP per capita) play significant roles in curbing carbon emission intensity, while the promotion of population urbanization (i.e., the share of population living in the urban regions of total population) may lead to carbon emission intensity growth. Second, there exists significant one-way causality running from the urbanization rate and economic growth to carbon emission intensity, respectively. Third, among the three drivers, economic growth proves the main influencing factor of carbon emission intensity changes during the sample period.

 

[19] Yue-Jun Zhang. Speculative trading and WTI crude oil futures price movement: an empirical analysis. Applied Energy, 2013, 107: 394-402. (SCI&SSCI, IF=7.182)

Abstract: Based on the historical data of CFTC’s Commitments of Traders (COT) reports from 2007 to 2010, this paper empirically studies the influence of speculators’ positions on WTI crude oil futures returns. The results indicate that, first, the instantaneous feedback of speculators’ position change on crude oil price return proves statistically significant and dominates the linear feedback relationship between them during the sample period although speculation does not appear a significant driver of crude oil price movement in the lead-and-lag sense. Second, the contemporaneous influence of speculators’ positions on oil price takes evident linearity but weak nonlinearity. Third, when oil price has high (low) volatility, non-commercials’ position change may exert a significant (insignificant) linear shock on oil price returns. And whether crude oil price stays in high or low volatility, the nonlinear influence does not appear significant. Finally, the linear influence appears symmetric when crude oil price goes up and down, but the nonlinear influence takes asymmetric feature; and neither of linear and nonlinear influence is symmetric when crude oil price experiences high and low volatility.

 

[20] Yue-Jun Zhang, Zi-Yi Wang. Investigating the price discovery and risk transfer functions in the crude oil and gasoline futures markets: some empirical evidence. Applied Energy, 2013, 104: 220-228. (SCI&SSCI, IF=7.182)

Abstract: This paper empirically investigates the functions of price discovery and risk transfer in crude oil and gasoline futures markets using some econometric models. And the results indicate that, first, 95.71% and 59.41% of the price discovery function is performed by futures in crude oil and gasoline markets respectively during the sample period, implying the greater contribution of the futures markets compared with that of the spot markets. Meanwhile, the gasoline futures price makes 85.71% contribution to price discovery in its interaction with crude oil futures price. Second, crude oil futures price performs the risk transfer function much better than gasoline futures price in interactions with their respective spot prices. And the risk transfer function between crude oil and gasoline futures markets is not well performed. Finally, the recent financial crisis has not significantly influenced the price discovery and risk transfer functions between crude oil and gasoline futures markets.

 

[21] Yue-Jun Zhang, Ya-Bin Da. Decomposing the changes of energy-related carbon emissions in China: evidence from the PDA approach. Natural Hazards, 2013, 69(1): 1109-1122. (SCI, IF=1.833)

Abstract: In order to investigate the main drivers of CO2 emissions changes in China during the 11th Five-Year Plan period (2006–2010) and seek the main ways to reduce CO2 emissions, we decompose the changes of energy-related CO2 emissions using the production-theoretical decomposition analysis approach. The results indicate that, first, economic growth and energy consumption are the two main drivers of CO2 emissions increase during the sample period; particularly in the northern coastal, northwest and central regions, where tremendous coal resources are consumed, the driving effect of their energy consumption on CO2 emissions appears fairly evident. Second, the improvement of carbon abatement technology and the reduction in energy intensity play significant roles in curbing carbon emissions, and comparatively the effect of carbon abatement technology proves more significant. Third, energy use technical efficiency, energy use technology and carbon abatement technical efficiency have only slight influence on CO2 emissions overall. In the end, we put forward some policy recommendations for China’s government to reduce CO2 emissions intensity in the future.

 

[22] Tian-Jian Yang, Yue-Jun Zhang*, Jin Huang, Ruo-Hong Peng. Estimating the energy saving potential of telecom operators in China. Energy Policy, 2013, 61: 448-459. (SCI&SSCI, IF=4.140) *为通讯作者)

Abstract: A set of models are employed to estimate the potential of total energy saved of productions and segmented energy saving for telecom operators in China. During the estimation, the total energy saving is divided into that by technology and management, which are derived from technical reform and progress, and management control measures and even marketing respectively, and the estimating methodologies for energy saving potential of each segment are elaborated. Empirical results from China Mobile indicate that, first, the technical advance in communications technology accounts for the largest proportion (70%–80%) of the total energy saved of productions in telecom sector of China. Second, technical reform brings about 20%–30% of the total energy saving. Third, the proportions of energy saving brought by marketing and control measures appear relatively smaller, just less than 3%. Therefore, China's telecom operators should seize the opportunity of the revolution of communications network techniques in recent years to create an advanced network with lower energy consumption.

 

[23] Yue-Jun Zhang. Interpreting the dynamic nexus between energy consumption and economic growth: empirical evidence from Russia. Energy Policy, 2011, 39(5): 2265-2272. (SCI&SSCI, IF=4.140)

Abstract: Research on the nexus between energy consumption and economic growth is a fundamental topic for energy policy making and low-carbon economic development. Russia proves the third largest energy consumption country in the world in recent years, while little research has shed light upon its energy consumption issue till now, especially its energy–growth nexus. Therefore, this paper empirically investigates the dynamic nexus of the two variables in Russia based on the state space model. The results indicate that, first of all, Russia's energy consumption is cointegrated with its economic growth in a time-varying way though they do not have static or average cointegration relationship. Hence it is unsuitable to merely portrait the nexus in an average manner. Second, ever since the year of 2000, Russia's energy efficiency has achieved much more promotion compared with that in previous decades, mainly due to the industrial structure adjustment and technology progress. Third, among BRIC countries, the consistency of Russia's energy consumption and economic growth appears the worst, which suggests the complexity of energy–growth nexus in Russia. Finally, there exists bi-directional causality between Russia's energy consumption and economic growth, though their quantitative proportional relation does not have solid foundation according to the cointegration theory.

 

[24] Yue-Jun Zhang. The impact of financial development on carbon emissions: an empirical analysis in China. Energy Policy, 2011, 39(4): 2197-2203. (SCI&SSCI, IF=4.140)

Abstract: Given the complexity between China's financial development and carbon emissions, this paper uses some econometric techniques, including cointegration theory, Granger causality test, variance decomposition, etc., to explore the influence of financial development on carbon emissions. Results indicate that, first, China's financial development acts as an important driver for carbon emissions increase, which should be taken into account when carbon emissions demand is projected. Second, the influence of financial intermediation scale on carbon emissions outweighs that of other financial development indicators but its efficiency's influence appears by far weaker although it may cause the change of carbon emissions statistically. Third, China's stock market scale has relatively larger influence on carbon emissions but the influence of its efficiency is very limited. This to some extent reflects the relatively lower liquidity in China's stock markets. Finally, among financial development indicators, China's FDI exerts the least influence on the change of carbon emissions, due to its relatively smaller volume compared with GDP; but it is mainly utilized in carbon intensive sectors now, therefore, with the increase of China's FDI in the future, many efforts should be made to adapt its utilizing directions and play its positive role in promoting low-carbon development.

 

[25] Yue-Jun Zhang, Yi-Ming Wei. The dynamic influence of advanced stock market risk on international crude oil return: an empirical analysis. Quantitative Finance, 2011, 11(7): 967-978. (SCI&SSCI, IF=0.960) 

Abstract: During the new round of oil price upsurge in the very beginning of 21st century, stock market risk proves one of the key factors to influence international oil market volatility. Based on the historic data from 1997 to 2007 and using the state-space model estimated with Kalman filtering approach, factor models are developed to obtain the time-varying risk of dominant advanced and emerging stock markets on international crude oil market, respectively. And then the influence of those stock market risks on oil market returns is investigated and compared. Empirical study results indicate that, firstly, the influence of stock market risk on oil market shows more non-linear features than linear ones, and the influence of advanced stock markets seems stronger than that of the emerging. Secondly, there can be seen negative linear influence of stock market risks on oil market in down stock markets while not all up markets can witness positive linear shock on the oil market. Finally, Japanese stock market risk has a symmetric performance in both its linear and non-linear influence on oil market, whereas all other stock market risks exert asymmetric influence. All the abovementioned results imply the diversity and complexity of the influence of stock market risks on oil market, which are supposed to be helpful for related investors and decision makers.

 

[26] Yue-Jun Zhang, Yi-Ming Wei. The crude oil market and the gold market: evidence for cointegration, causality and price discovery. Resources Policy, 2010, 35(3): 168-177. (SSCI, IF=2.618)

Abstract: Given that the gold market and the crude oil market are the main representatives of the large commodity markets, it is of crucial practical significance to analyze their cointegration relationship and causality, and investigate their respective contribution, from the perspective of price discovery, to the common price trend so as to interpret the dynamics of the whole large commodity market and forecast the fluctuation of crude oil and gold prices. Empirical analysis indicates that, first, there are consistent trends between the crude oil price and the gold price with significant positive correlation coefficient 0.9295 during the sampling period, from January of 2000 to March of 2008. Second, there can be seen a long-term equilibrium between the two markets, and the crude oil price change linearly Granger causes the volatility of gold price, but not vice versa; moreover, the two market prices do not face a significant nonlinear Granger causality, which overall suggests their fairly direct interactive mechanism. Finally, with regard to the common effective price between the two markets, the contribution of the crude oil price seems larger than that of the gold price, whether with the permanent transitory (PT) model (86.50% versus 13.50%) or the information share (IS) model (50.28% versus 49.72%), which implies that the influence of crude oil on global economic development proves more far-reaching and extensive, and its role in the large commodity markets has attracted more attention in recent years.

 

[27] Yue-Jun Zhang, Yi-Ming Wei. An overview of current research on EU ETS: evidence from its operating mechanism and economic effect. Applied Energy, 2010, 87(6): 1804-1814. (SCI&SSCI, IF=7.182

Abstract: The European Union Emissions Trading Scheme (EU ETS) is supposed to be an important mechanism for addressing climate change. Up to now, the theoretical foundation of EU ETS has been widely acknowledged, but empirical research on its current situation has only been published recently or is forthcoming. Therefore, this paper is aimed to summarize the main arguments of empirical studies on the EU ETS, in terms of two aspects, i.e., the operating mechanism and economic effect of the EU ETS, which are two crucial topics and have been attached much attention. Based on the shortcomings of current research and future requirements of the EU ETS evolution, finally, we also present some further directions of the EU ETS research. Overall, the research overview here may be helpful to recognize the features of the EU ETS and its effect on others.

 

[28] Yue-Jun Zhang, Ying Fan, Hsien-Tang Tsai, Yi-Ming Wei. Spillover effect of US dollar exchange rate on oil price. Journal of Policy Modeling, 2008, 30(6): 973-991. (SSCI, IF=0.993)

Abstract: The US dollar is frequently used as the invoicing currency of international crude oil trading. Hence, the fluctuation in US dollar exchange rate is believed to underlie the volatility of crude oil price and especially its forecasting accuracy. Using econometric techniques including cointegration, VAR model, ARCH type models and a newly proposed approach to test Granger causality in risk, three spillover effects are explored, i.e., mean spillover, volatility spillover and risk spillover. Using rigorous appraisal, analysis is made of the influence of US dollar exchange rate on the international crude oil price from the perspective of market trading and several findings have been obtained. Firstly, a significant long-term equilibrium cointegrating relationship can be identified between the two markets. This suggests a crucial reason for the fluctuation in crude oil price. But interestingly, the reverse does not work. Specifically, the influence of a standard deviation disturbance of US dollar exchange rate on oil price is increased quite slowly, and reaches its highest point, 1.0088 US dollars per barrel, after 1 year or so with a slightly and steadily diminishing process afterward. This implies that the US dollar depreciation for the years under investigation was a key factor in driving up the international crude oil price. Secondly, there is apparent volatility and clustering for the two market prices, whereas their volatility spillover effect is insignificant, which reveals that their price volatility take relatively independent paths and the instant fluctuation in US dollar exchange rate will not cause significant change in the oil market. Finally, their risk spillover effect appears quite limited, hence price risk influence of US dollar exchange rate on the oil market is not necessarily emphasized too much. Put it another way, compared with the powerful oil market, the impact of US dollar exchange rate is confirmed to be relatively partial. These results indicate that the influence of US dollar exchange rate on the international crude oil market proves quite significant in the long term; however, its short-term and instant influence turns out to be quite limited, which is noteworthy to be taken into account for oil market researchers, market trading analysts and traders.

 

[29] Ying Fan, Yue-Jun Zhang, Hsien-Tang Tsai, Yi-Ming Wei. Estimating ‘Value at Risk’ of crude oil price and its spillover effect using GED approach. Energy Economics, 2008, 30(6): 3156-3171. (SSCI, IF=3.199)

Abstract: Estimation has been carried out using GARCH-type models, based on the Generalized Error Distribution (GED), for both the extreme downside and upside Value-at-Risks (VaR) of returns in the WTI and Brent crude oil spot markets. Furthermore, according to a new concept of Granger causality in risk, a kernel-based test is proposed to detect extreme risk spillover effect between the two oil markets. Results of an empirical study indicate that the GED-GARCH-based VaR approach appears more effective than the well-recognized HSAF (i.e. historical simulation with ARMA forecasts). Moreover, this approach is also more realistic and comprehensive than the standard normal distribution-based VaR model that is commonly used. Results reveal that there is significant two-way risk spillover effect between WTI and Brent markets. Supplementary study indicates that at the 99% confidence level, when negative market news arises that brings about a slump in oil price return, historical information on risk in the WTI market helps to forecast the Brent market. Conversely, it is not the case when positive news occurs and returns rise. Historical information on risk in the two markets can facilitate forecasts of future extreme market risks for each other. These results are valuable for anyone who needs evaluation and forecasts of the risk situation in international crude oil markets.

 

[30] Zhi-Fu Mi, Yue-Jun Zhang*. Estimating the 'Value at Risk' of EUA futures prices based on the Extreme Value Theory. International Journal of Global Energy Issues, 2011, 35(2/3/4): 145-157. (EI) *为通讯作者)

Abstract: This paper employs the Extreme Value Theory (EVT) to measure the 'Value at Risk' (VaR) of EUA futures prices. The results show that during the sample period: first, the EVT approach can be used to reliably measure the extreme risk of carbon futures markets of the European Union Emissions Trading Scheme, both for Phase I and Phase II. Second, the downside extreme risk of carbon futures market outweighs the upside risk, with evident asymmetric features. Moreover, the average VaR of carbon futures contract DEC10 proves much less than that of contract DEC07 during the sample period.

 

2. 主要科研项目

 

主持

[1]中国碳排放配额交易对碳减排的影响机制建模及优化策略研究. 国家自然科学基金面上项目. 2018-2021.

[2]国际石油价格复杂系统建模及应用研究. 国家万人计划青年拔尖人才项目. 2015-2017. 

[3]石油金融与碳金融系统建模. 国家自然科学基金优秀青年项目. 2014-2016.  

[4]碳排放配额交易的市场机制与政策研究. 国家自然科学基金面上项目. 2013-2016.  

[5]国际石油市场复杂系统投机泡沫机制及其实证研究. 国家自然科学基金青年项目. 2011-2013.  

[6]国际石油市场投机泡沫复杂机制及其对油价波动的影响研究. 高等学校博士学科点专项科研基金. 2011-2013.  

[7]应对气候变化的碳交易市场机制与模型研究. 教育部人文社会科学研究基金项目. 2010-2012.  

[8]石油市场风险管理:模型与应用. 国家科学技术学术著作出版基金资助项目. 2012.  

[9]北京市金融发展对碳排放的复杂影响机制建模及实证研究. 北京市优秀人才培养资助计划. 2012-2013.  

[10]世界主要城市煤炭清洁化管理经验借鉴. 北京市节能环保中心. 2011-2012.  

 

参与

[1]高维度、非线性、非平稳及时变金融数据建模和应用. 国家自然科学基金重点项目. 2015-2019.

[2]气候变化对社会经济系统易损性影响分析方法及其应用研究. 国家自然科学基金重大国际合作项目. 2011-2013.  

[3]建立以中国为主的气候变化国际/区域研究中心可行性研究. 国家973课题. 2010-2011.  

[4]资源与环境复杂系统管理中的理论方法与应用研究. 国家杰出青年科学基金项目. 2004-2008.   

[5]能源安全与能源政策的基础研究. 国家自然科学基金重点项目. 2008-2011. 

[6]应对气候变化的碳市场研究. 中国科学院知识创新工程重要方向项目群项目. 2009-2011.  

[7]原油价格波动规律及其对我国经济的影响分析. 国家自然科学基金项目. 2006-2008.  

[8]矿产资源开发利用决策支持系统开发. 科技部十一五国家科技支撑计划项目. 2006-2009.  

[9]国外矿产资源开发利用风险评价技术研究. 科技部十一五国家科技支撑计划项目. 2006-2009.  

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