  The dynamics of many socioeconomic systems is determined by the decision
making process of agents. The decision process depends on agent's
characteristics, such as preferences, risk aversion, behavioral biases, etc..
In addition, in some systems the size of agents can be highly heterogeneous
leading to very different impacts of agents on the system dynamics. The large
size of some agents poses challenging problems to agents who want to control
their impact, either by forcing the system in a given direction or by hiding
their intentionality. Here we consider the financial market as a model system,
and we study empirically how agents strategically adjust the properties of
large orders in order to meet their preference and minimize their impact. We
quantify this strategic behavior by detecting scaling relations of allometric
nature between the variables characterizing the trading activity of different
institutions. We observe power law distributions in the investment time
horizon, in the number of transactions needed to execute a large order and in
the traded value exchanged by large institutions and we show that heterogeneity
of agents is a key ingredient for the emergence of some aggregate properties
characterizing this complex system.
