Journal
PHYSICAL REVIEW E
Volume 88, Issue 6, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.88.062814
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Funding
- FET Flagship Pilot Project FuturICT [284709]
- ETH project Systemic Risks, Systemic Solutions (CHIRP II Project) [ETH 4812-1]
- ERC Advanced Investigator Grant Momentum [324247]
- European Research Council (ERC) [324247] Funding Source: European Research Council (ERC)
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Building on similarities between earthquakes and extreme financial events, we use a self-organized criticality-generating model to study herding and avalanche dynamics in financial markets. We consider a community of interacting investors, distributed in a small-world network, who bet on the bullish (increasing) or bearish (decreasing) behavior of the market which has been specified according to the S&P 500 historical time series. Remarkably, we find that the size of herding-related avalanches in the community can be strongly reduced by the presence of a relatively small percentage of traders, randomly distributed inside the network, who adopt a random investment strategy. Our findings suggest a promising strategy to limit the size of financial bubbles and crashes. We also obtain that the resulting wealth distribution of all traders corresponds to the well-known Pareto power law, while that of random traders is exponential. In other words, for technical traders, the risk of losses is much greater than the probability of gains compared to those of random traders.
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