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BEGIN:VEVENT
DTSTAMP:20260828T000552Z
LAST-MODIFIED:20140328T183109Z
DTSTART:20140409T150000Z
DTEND:20140409T160000Z
UID:event1266@bu.edu
URL:http://physics.bu.edu/internal/events/show/1266
SUMMARY:Interdependent Networks - Topological Percolation Research and Appl
	ication in Finance
DESCRIPTION:Featuring Di Zhou\n\nPart of the PhD Final Oral Exams.\n\nExami
	ning Committee:  H.E. Stanley\, Anders Sandvik\, Robert Carey\, William Sko
	cpol\, William Klein\n\nAbstract\nThis dissertation covers the two major pa
	rts of my Ph.D. research: i) developing a theoretical\nframework of complex
	 networks and applying simulation and numerical methods to study the\nrobus
	tness of the network system\, and ii) applying statistical physics concepts
	 and methods to\nquantitatively analyze complex systems and applying the th
	eoretical framework to study real-world\nsystems.\n\nIn part I\, we focus o
	n developing theories of interdependent networks as well as building comput
	er\nsimulation models\, which includes three parts: 1) We report on the eff
	ects of topology on failure\npropagation for a model system consisting of t
	wo interdependent networks. We find that the\ninternal node correlations in
	 each of the networks significantly changes the critical density of\nfailur
	es\, which can trigger the total disruption of the two-network system. Spec
	ifically\, we find\nthat the assortativity within a single network decrease
	s the robustness of the entire system. 2)\nWe study the percolation behavio
	r of two interdependent scale-free (SF) networks under random\nfailure of 1
	-p fraction of nodes. We find that as the coupling strength q between the t
	wo networks\nreduces from 1 (fully coupled) to 0 (no coupling)\, there exis
	t two critical coupling strengths q1\nand q2\, which separate the behaviors
	 of the giant component as a function of p into three different\nregions\, 
	and for q2 < q < q1\, we observe a hybrid order phase transition phenomenon
	. 3) We study\nthe robustness of n interdependent networks with partially s
	upport-dependent relationship both\nanalytically and numerically. We study 
	a starlike network of n Erdos-Renyi (ER)\, SF networks\nand a looplike netw
	ork of n ER networks\, and we find for starlike networks\, their phase tran
	sition\nregions change with n\, but for looplike networks the phase regions
	 change with average degree .\n\nIn part II\, we apply concepts and methods
	 developed in statistical physics to study economic\nsystems. We analyze st
	ock market indices and foreign exchange daily returns for 60 countries\nove
	r the period of 1999-2012. We build a multi-layer network model based on di
	fferent correlation\nmeasures\, and introduce a dynamic network model to si
	mulate and analyze the initializing and\nspreading of financial crisis. Usi
	ng different computational approaches and econometric tests\, we\nfind atyp
	ical behavior of the cross correlations and community formations in the fin
	ancial networks\nthat we study during the financial crisis of 2008. For exa
	mple\, the overall correlation of stock\nmarket increases during crisis whi
	le the correlation between stock market and foreign exchange\nmarket decrea
	ses. The dramatic increase in correlations between a specific nation and ot
	her nations\nmay indicate that this nation could trigger a global financial
	 crisis. Specifically\, core countries that have higher correlations with o
	ther countries and larger Gross Domestic Product (GDP) values\nspread finan
	cial crisis quite effectively\, yet some countries with small GDPs like Gre
	ece and Cyprus\nare also effective in propagating systemic risk and spreadi
	ng global financial crisis.
LOCATION:PRB 595\, 3 Cummington Mall\, 02215
STATUS:CONFIRMED
CLASS:PUBLIC
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