Systemic risk mapping
It is possible to study multivariate volatility using traditional methods such as the covariance matrix, graph-based techniques that rely on the identification of sinks, or even signal processing techniques such as the canonical time warping correspondence between two scalar sequences. But let us take advantage of the symbolic expressions generated via evolutionary computing to construct a graph representation of system dependencies.
Detection of (Anti) Fragility
Formally, fragility and antifragility are defined as negative or positive sensitivity to a semi-measure of dispersion and volatility \cite{Taleb_2013}. What is different in this case is that we are not concerned with exposure to price shocks only, but prices themselves can change abruptly in response to events from the environment. By constructing a graph using formulas selected from our genetic exploration of the model space, under a certain criterion (e.g. similar complexity or accuracy), we obtain a network as the one in Figure 5.