Complexity in Finance
How can complexity science reshape investment thinking?
In this section, I introduce Complexity Arbitrage — the idea that asset managers can achieve better outcomes by applying concepts from complexity science, such as non-ergodicity, systemic risk, price emergence, and adaptive strategy.
Current Research Themes
My research at the Institute of Economics at Scuola Superiore Sant’Anna focuses on strengthening the bridge between academic thinking in complexity economics and the lived realities of investment practice. The work develops a clearer understanding of how capital is allocated in evolving, uncertain environments, and how complexity science can help investors make better decisions.
• Understanding how asset managers actually make decisions under uncertainty
A central strand of the research is a programme of interviews with practising asset managers to uncover how they navigate uncertainty, feedback, shifting narratives, and imperfect models in real investment settings. The aim is to surface tacit knowledge, heuristics, and challenges that are poorly captured in existing theory. Insights from this work will inform academic articles and a practitioner-focused report.
• Engaging deeply with the academic literature on capital allocation
This theme examines the literatures most relevant to how financial capital is allocated in complex, evolving economic systems — including behavioural finance, evolutionary economics, and theories linked to stock selection and portfolio management. This work directly supports the interview project by shaping the conceptual framing, informing the design of qualitative methods, and attempting to position findings within established debates.
The Five Themes of Complexity Arbitrage
Emergent Market Prices
Emergent Market Prices
Emergent Market Prices
Markets in process.
Prices are shaped by countless interactions, feedback loops, and shifting conditions. Seeing prices as emergent — not fixed reflections of “true value” — reveals the underlying processes driving market movements
Narratives
Emergent Market Prices
Emergent Market Prices
The stories we think in. Stories, mental models, and beliefs shape expectations and decisions. Tracking them helps identify sentiment shifts and the potential for self-fulfilling or self-defeating outcomes.
Modelling
Emergent Market Prices
Modelling
Guides, not crystal balls.
Models are crude maps of a patterned reality rather than fixed predictors. Using them adaptively — updating them as conditions change — keeps strategies adaptive and assumptions fresh.
Uncertainty
Non-Ergodicity
Non-Ergodicity
Beyond risk.
Not all unknowns can be measured. Building flexibility into strategies, preparing for varied scenarios, and avoiding overconfidence in forecasts greatly strengthens long-term resilience and strategic adaptability.
Non-Ergodicity
Non-Ergodicity
Non-Ergodicity
The journey matters.
In non-ergodic systems, the sequence of returns — not just the average — shapes results. Interim losses, volatility, and compounding can leave lasting marks on performance that conventional thinking often overlooks.