Reducing financial avalanches by random investments.
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.
Dipartimento di Economia e Impresa, Universitá di Catania, Corso Italia 55, 95129 Catania, Italy.
Alessio Emanuele
AE
Biondo
Dipartimento di Fisica e Astronomia, Universitá di Catania and INFN sezione di Catania, Via S. Sofia 64, 95123 Catania, Italy.
Alessandro
A
Pluchino
Dipartimento di Fisica e Astronomia, Universitá di Catania and INFN sezione di Catania, Via S. Sofia 64, 95123 Catania, Italy.
Andrea
A
Rapisarda
ETH Zurich, Clausiustrasse 50, 8092 Zurich, Switzerland.
Dirk
D
Helbing