The world economy consists of highly interconnected and interdependent commercial and financial networks. Here, we develop temporal and structural network tools to analyze the state of the economy and the financial markets. Our analysis indicates that a strong clustering can be a warning sign. Reduction in diversity, which was an essential aspect of the dynamics surrounding the financial markets crisis of 2008, is seen as a key emergent feature arising naturally from the evolutionary and adaptive dynamics inherent to the financial markets. Similarly, collusion amongst construction firms in a number of regions in Japan in the 2000s can be identified with the formation of clusters of anomalous highly connected companies. V C 2013 Wiley Periodicals, Inc. Complexity 19: 22-36, 2013 Key Words: economics; evolutionary dynamics; network theory; quantitative finance.
ANALYSIS 1.Dynamics of Financial MarketsI n order to investigate the dynamics of financial markets we have developed a simple multi agent network model for a basic financial system, comprising of three fundamental types of agents: Banks, Investors and Borrowers (see section 2 for details). Our approach to modeling this system is inspired by the modeling of societies and ecosystems, in which a key role is played by the This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.virtual intra and interdependence of species [1][2][3][4]. This translates in our model into a focus on: (i) the dynamics of infection of business strategies within the banking sector and of culture dissemination within the investment and fund management community, and (ii) the topological aspects of the network of interactions. In order to focus more clearly on the influence of the collective action of agents, and their interaction amongst
FIGURE 1Crisis Mapping from Evolutionary Dynamics: Plot A shows the frequency of crisis and the relative number of times that each type of crisis scenario occurs. The front floor (dark blue) indicates the distributions when evolutionary dynamics are present, with realizations resulting in 1 or 2 crises being by far the most common. The back floor (green) showing the results without dynamics is entirely distributed into the first block (no crisis), indicating that evolutionary dynamics are an essential feature in order to see crises occur. Plot B illustrates the time line of crises as predicted by the model including the evolutionary dynamics for 1 crisis (light purple) and 2 crises (light yellow) simulations. Time is shown vertically, increasing downwards, while the horizontal axis denotes different realizations of the model. A crisis is defined when >2% of the Bank agents fail or require financial assistance over a year, which corresponds to the historical average registered in the first and second US banking crisis over the simulation period. 4 The fir...