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The structure and resilience of financial market networks
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10.1063/1.3683467
/content/aip/journal/chaos/22/1/10.1063/1.3683467
http://aip.metastore.ingenta.com/content/aip/journal/chaos/22/1/10.1063/1.3683467
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Figures

Image of FIG. 1.
FIG. 1.

(Color online) Illustration of the method to construct financial market networks. The return of each stock (i, j, and k) is obtained and a network is constructed by taking into account a time interval . This time window is moved to the right by an amount of and a new network is obtained. This process is repeated until the window reaches the end of the time scale, which results in the set of networks .

Image of FIG. 2.
FIG. 2.

Time evolution of the dynamical entropy. The higher the dynamic entropy, the higher is the level of network resilience. Values below correspond to important crises: (i) Black Monday in 1987, (ii) the United States savings and loan crisis in 1989, (iii) the collapse of the Japanese asset price bubble, (iv) the collapse of hedge fund Long-Term Capital Market in 1998, (v) the Argentine crises and 9/11 attacks in 2001, (vi) the last global crisis which started 2008. Evolution of entropy in random data is also presented (in gray).

Image of FIG. 3.
FIG. 3.

Evolution of the average shortest path length in the obtained financial market networks. Evolution of this measurement in random data is also presented.

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/content/aip/journal/chaos/22/1/10.1063/1.3683467
2012-02-14
2014-04-17
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: The structure and resilience of financial market networks
http://aip.metastore.ingenta.com/content/aip/journal/chaos/22/1/10.1063/1.3683467
10.1063/1.3683467
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