Market simulation & strategy
Stress-test pricing, launch strategy, or trading rules against synthetic populations of heterogeneous agents before committing capital. Finds the failure modes averages can't see.
Equilibrium economics answers the wrong question. It asks what price clears the market when everyone is rational, identical, and finished adjusting. That is a useful cartoon for a seminar, and a dangerous one for a trading floor or a supply chain.
The alternative is not to abandon rigor — it is to model behavior that is genuinely adaptive. Traders who learn. Firms that imitate. Shocks that propagate through network topology rather than dissipating smoothly across representative agents. The methods are now mature: agent-based models, calibrated networks, non-linear stochastic dynamics. The bottleneck is practitioners who can translate between the research and a real business problem.
That is the practice.
Stress-test pricing, launch strategy, or trading rules against synthetic populations of heterogeneous agents before committing capital. Finds the failure modes averages can't see.
Map the graph — who actually depends on whom, two and three hops deep. Identify nodes whose failure triggers cascades disproportionate to their size or spend.
Conventional VaR underestimates regime change. Complexity-based indicators — correlation structure, critical slowing-down — give early warning of phase transitions conventional models miss by construction.
Apply network theory to deal sourcing, synergy modeling, and post-merger integration risk. Synergies live in the graph of who-talks-to-whom; so do the integration failures.
If you have an interesting question — inside a firm, a research group, or a hiring pipeline — the fastest path is a direct note.