Imperial College London

Dr. Eduardo Viegas

Faculty of Natural SciencesDepartment of Mathematics








Electrical EngineeringSouth Kensington Campus





I am a researcher within the Centre for Complexity Science. I split my time between my academic activities and applied projects within the financial services industry, where I am focused on the development of quantitative methods for risk management and portfolio investment strategies.

My philosophical approach to Complexity Science is built upon a combination of dialogic reasoning and Whitehead’s Philosophic Relativity concept. This means that the scientific analysis is to be centred on identifying and explaining the structure and the dynamics of complex systems through different methods and approaches that can coexist, interact and evolve in a relative, time dependent, manner without the need for establishing a hierarchy of methods or single optimum units of measurement. Therefore, I tend to dispense with the necessity of reasoning by conflict as well as the need for synthesis to emerge into a single approach, preferring instead to draw conclusions about common and unifying themes.

My research is centred on the Financial Risk of Complex Systems, and it is fundamentally inspired by S. J. Gould’s structure of evolutionary theory and von Neumann’s automata theory. This effectively translates into constructing methods and frameworks centred on the development and implementation of evolutionary dynamic, nature inspired, quantitative methods to enhance the identification - and mitigation - of systemic, market, credit and liquidity risks within the financial markets and economic systems.

I continue to work on the developed of a Complexity Evolutionary Theory on Financial and Economic Crises (‘CETFEC’), which I regard to be at embryonic stage at present but with the core foundations already in place. CETFEC characterises financial markets and economies as complex systems, where the emergence of financial crises are only the natural consequence of fundamental evolutionary processes that lead relevant agents to adapt to different environmental conditions. Whereas some parallels can be draw to Minsky’s Financial Instability Hypothesis, the theory has a marked distinction that it does not pre-define, categorise or exercise a level of judgement about the behaviour of the agents within the system. CETFEC aims to identify the signals that lead the existence of the necessary conditions for the emergence of crises, rather than trying to predict the timing of crises. Fundamentally it holds that the understanding of the distribution and the diversity of the agents provide essential signals to the resilience of the system.

From a market practitioner’s perspective, I have nearly 30 years of experience within the global financial services industry in the development and implementation of mathematical finance models and stochastic analysis to enable valuation and pricing of cash and derivative financial instruments, risk quantification strategies, and trade structuring. Among past positions, I was the Head of Risk, Valuation and Governance of Lehman Brothers International Europe since its first day of administration, as well as the Head of Model Risk Methodologies for PwC’s Financial Services Risk and Regulation practice, and the Leader for the European Structured Finance Group for PwC’s Eurofirms.




Goto H, Viegas E, Takayasu H, et al., 2019, Dynamics of essential interaction between firms on financial reports, Plos One, Vol:14, ISSN:1932-6203, Pages:1-16

Viegas EM, Goto H, Takayasu H, et al., 2019, Assembling real networks from synthetic and unstructured subsets: the corporate reporting case, Scientific Reports, Vol:9, ISSN:2045-2322

Goto H, Viegas E, Jensen HJ, et al., 2018, Smoluchowski equation for networks: merger induced intermittent giant node formation and degree gap, Journal of Statistical Physics, Vol:172, ISSN:1572-9613, Pages:1086-1100

Goto H, Viegas E, Jensen HJ, et al., 2017, Appearance of unstable monopoly state caused by selective and concentrative mergers in business networks, Scientific Reports, Vol:7, ISSN:2045-2322

Broga KM, Viegas E, Jensen HJ, 2016, Model analysis of the link between interest rates and crashes, Physica a - Statistical Mechanics and Its Applications, Vol:457, ISSN:0378-4371, Pages:225-238

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