Physica A415(2014)43-53 Contents lists available at ScienceDirect Physica A ELSEVIER journal homepage:www.elsevier.com/locate/physa Systemic risk and causality dynamics of the world CrossMark international shipping market Xin Zhanga*,Boris Podobnik b.c.de,Dror Y.Kenettb,H.Eugene Stanleyb College of Transport and Communication,Shanghai Maritime University.Shanghai 201306.China bCenter for Polymer Studies and Department of Physics,Boston University.Boston,MA02215,United States Faculty of Civil Engineering.University of Rijeka,51000 Rijeka,Croatia d Zagreb School of Economics and Management,10000 Zagreb.Croatia e Faculty of Economics,1000 Ljubljana,Slovenia HIGHLIGHTS We study the temporal correlation networks of the world shipping market over time. We model the systemic risk level of the shipping market based on the Dynamic Causality Index. We explore directional connections between the shipping market and the financial market. Different market sectors tend to link and comove closely during financial crisis. The Dynamic Causality Index can provide efficient warning before market downturn. ARTICLE INFO ABSTRACT Article history: Various studies have reported that many economic systems have been exhibiting an Received 10 July 2014 increase in the correlation between different market sectors,a factor that exacerbates Received in revised form 22 July 2014 the level of systemic risk.We measure this systemic risk of three major world shipping Available online 2 August 2014 markets,(i)the new ship market,(ii)the second-hand ship market,and (iii)the freight market,as well as the shipping stock market.Based on correlation networks during three Keywords: time periods,that prior to the financial crisis,during the crisis,and after the crisis,minimal Complex networks Systemic risk spanning trees(MSTs)and hierarchical trees(HTs)both exhibit complex dynamics,i.e.. Correlation networks different market sectors tend to be more closely linked during financial crisis.Brownian Brownian distance distance correlation and Granger causality test both can be used to explore the directional Granger causality test interconnectedness of market sectors,while Brownian distance correlation captures more dependent relationships,which are not observed in the Granger causality test.These two measures can also identify and quantify market regression periods,implying that they contain predictive power for the current crisis. 2014 Elsevier B.V.All rights reserved. 1.Introduction It is widely acknowledged that economic systems are highly complex.In recent years they have become a subject of much interest among both economists and physicists[1-12].Because the international shipping industry facilitates 90%of world trade and is a key factor in global economic development[13 it is a major topic for economic theory.The shipping industry Corresponding author. E-mail addresses:zhangxin@shmtu.edu.cn,sivaxin@bu.edu (X.Zhang). http://dx.doi.org/10.1016/j.physa.2014.07.068 0378-4371/2014 Elsevier B.V.All rights reserved.Physica A 415 (2014) 43–53 Contents lists available at ScienceDirect Physica A journal homepage: www.elsevier.com/locate/physa Systemic risk and causality dynamics of the world international shipping market Xin Zhang a,∗ , Boris Podobnik b,c,d,e , Dror Y. Kenett b , H. Eugene Stanley b a College of Transport and Communication, Shanghai Maritime University, Shanghai 201306, China b Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, United States c Faculty of Civil Engineering, University of Rijeka, 51000 Rijeka, Croatia d Zagreb School of Economics and Management, 10000 Zagreb, Croatia e Faculty of Economics, 1000 Ljubljana, Slovenia h i g h l i g h t s • We study the temporal correlation networks of the world shipping market over time. • We model the systemic risk level of the shipping market based on the Dynamic Causality Index. • We explore directional connections between the shipping market and the financial market. • Different market sectors tend to link and comove closely during financial crisis. • The Dynamic Causality Index can provide efficient warning before market downturn. a r t i c l e i n f o Article history: Received 10 July 2014 Received in revised form 22 July 2014 Available online 2 August 2014 Keywords: Complex networks Systemic risk Correlation networks Brownian distance Granger causality test a b s t r a c t Various studies have reported that many economic systems have been exhibiting an increase in the correlation between different market sectors, a factor that exacerbates the level of systemic risk. We measure this systemic risk of three major world shipping markets, (i) the new ship market, (ii) the second-hand ship market, and (iii) the freight market, as well as the shipping stock market. Based on correlation networks during three time periods, that prior to the financial crisis, during the crisis, and after the crisis, minimal spanning trees (MSTs) and hierarchical trees (HTs) both exhibit complex dynamics, i.e., different market sectors tend to be more closely linked during financial crisis. Brownian distance correlation and Granger causality test both can be used to explore the directional interconnectedness of market sectors, while Brownian distance correlation captures more dependent relationships, which are not observed in the Granger causality test. These two measures can also identify and quantify market regression periods, implying that they contain predictive power for the current crisis. © 2014 Elsevier B.V. All rights reserved. 1. Introduction It is widely acknowledged that economic systems are highly complex. In recent years they have become a subject of much interest among both economists and physicists [1–12]. Because the international shipping industry facilitates 90% of world trade and is a key factor in global economic development [13] it is a major topic for economic theory. The shipping industry ∗ Corresponding author. E-mail addresses: zhangxin@shmtu.edu.cn, sivaxin@bu.edu (X. Zhang). http://dx.doi.org/10.1016/j.physa.2014.07.068 0378-4371/© 2014 Elsevier B.V. All rights reserved