Globalization has created an international financial network of countries linked by trade in goods and assets. These linkages allow for more efficient resource allocation across borders, but also create potentially hazardous financial interdependence, such as the great financial distress caused by the 2010 threat of Greece 's default or the 2008 collapse of Lehman Brothers. Increasingly, the tools of network science are being used as a means of articulating in a quantitative way measures of financial interdependence and stability . In this paper , we employ two networkanalysis methods on the international investment network derived from the IMF Coordinated Portfolio Investment Survey (CPIS) . Via the "error and attack" methodology [1], we show that the CPIS network is of the " robust- yet-fragile " type, similar to a wide variety of evolved networks 1, 2 . In particular, the network is robust to random shocks but very fragile when key financial centers (e. g., the United States and the Cayman Islands) are affected. Using loss-given-default dynamics [ 3 ], "extinction analysis" simulations show that interdependence increased from 2001 to 2007. Our simulations further indicate that default by a single relatively small country like Greece can be absorbed by the network, but that default in combination with defaults of other PIGS countries (Portugal, Ireland, and Spain) could lead to a massive extinction cascade in the global economy. Adaptations of this approach could form the basis for risk metrics designed to monitor and guide policy formulation for the stability of the global economy.
The recent financial crisis of 2008 and the 2011 indebtedness of Greece highlight the importance of understanding the structure of the global financial network . In this paper we set out to analyze and characterize this network, as captured by the IMF Coordinated Portfolio Investment Survey (CPIS) , in two ways. First, through an adaptation of the "error and attack" methodology [1], we show that the network is of the " robust-yet-fragile " type, a topology found in a wide variety of evolved networks . We compare these results against four common null-models, generated only from first-order statistics of the empirical data. In addition, we suggest a fifth, log-normal model, which generates networks that seem to match the empirical one more closely. Still, this model does not account for several higher order network statistics, which reenforces the added value of the higher-order analysis. Second, using loss-given-default dynamics [ 2 ], we model financial interdependence and potential cascading of financial distress through the network. Preliminary simulations indicate that default by a single relatively small country like Greece can be absorbed by the network, but that default in combination with defaults of other PIGS countries (Portugal, Ireland, and Spain) could lead to a massive extinction cascade in the global economy.
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Globalization has created an international financial network of countries linked by trade in goods and assets. These linkages allow for more efficient resource allocation across borders, but also create potentially hazardous financial interdependence, such as the great financial distress caused by the 2010 threat of Greece 's default or the 2008 collapse of Lehman Brothers. Increasingly, the tools of network science are being used as a means of articulating in a quantitative way measures of financial interdependence and stability
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