  In this paper, making use of recent statistical physics techniques and
models, we address the specific role of randomness in financial markets, both
at the micro and the macro level. In particular, we review some recent results
obtained about the effectiveness of random strategies of investment, compared
with some of the most used trading strategies for forecasting the behavior of
real financial indexes. We also push forward our analysis by means of a
Self-Organized Criticality model, able to simulate financial avalanches in
trading communities with different network topologies, where a Pareto-like
power law behavior of wealth spontaneously emerges. In this context, we present
new findings and suggestions for policies based on the effects that random
strategies can have in terms of reduction of dangerous financial extreme
events, i.e. bubbles and crashes.
