Complexity Insights
Network analysis
Mapping contagion & connectivity.
Correlation graphs, counterparty networks, community detection, centrality-based systemic-risk scoring. Identifying the institutions that are "too connected to fail" — not just too big.
A research-house for complex systems.
Complexity Insights is a one-person practice applying network science, agent-based modeling, and quantitative data work to economic and financial questions that don't sit still long enough for a textbook answer.
Traditional models assume equilibrium. Real markets are adaptive, networked, and reflexive — small changes cascade, stable periods end abruptly, and the same number means different things across regimes. The practice takes that seriously, with code you can run.
Areas of work
What the practice actually does.
Agent-based modeling
Simulating emergence in synthetic markets.
Testing strategies, policy shifts, and microstructure changes in risk-free synthetic environments. When closed-form analysis breaks, a well-specified ABM still produces usable answers.
Data science
Where linearity breaks down.
Non-linear dynamics, regime-dependent behavior, feedback loops. Reproducible pipelines in Python; versioned data; everything that makes a finding hold up under re-running it next quarter.
Systemic risk
Quantifying the tails that VaR misses.
Network-aware risk metrics, stress propagation, regime-change early warning. Standard VaR assumes independence. Real crises don't.
M&A & strategy
Network theory for deal work.
Deal sourcing, synergy modeling, post-merger integration risk. What's the topology of the combined entity, and where are the fragile bridges?
Corporate finance
Complexity & valuation.
Capital allocation and FP&A that takes non-stationarity seriously. Traditional DCF meets regime-dependent discounting and scenario trees that actually resolve.
Nicholas Thomas
Research Lead & FounderI am an economics graduate and researcher focused on the intersection of complexity science and financial markets. My work extends traditional economics with computational methods applied to real-world data.
During my studies, I became frustrated with the gap between textbook models and market reality. The 2008 financial crisis wasn't just a "black swan" — it was a failure of models that assumed independence in a deeply interconnected system.
I founded Complexity Insights to bridge that gap. The firm serves as both a consultancy and a research laboratory, applying agent-based modeling and network theory to strategic problems in finance and risk management.
I am currently available for full-time roles in economic research, data analysis, and financial modeling — anywhere careful quantitative work changes a real decision.
Next
See the work, or start a conversation.
The projects page holds the current pipeline; the front door is always open for a direct note.
All projects →"The map is never finished. Only ever less wrong."