Optimisation under Organised Uncertainty

The model portfolio built by Fikula Capital Management is atomised. This means that it contains quite a large number of projects, so that the global risk of the portfolio is inferior to the sum of their individual risks, thanks to the law of large numbers. It is worth mentioning that there is no such thing as a major individual risk in our portfolio of projects. The relative weight of risk relating to every single project is kept low enough; the diversification effect can thus play to the fullest.


As a decision-making tool, Fikula has designed an Optimisation under Organised Uncertainty model that incorporates decision variables and constraints with the main objective of minimising the total portfolio risk. Our model is based on a standard optimisation under uncertainty model whose underlying projects have been subjected to the Organisation of Uncertainty, the Effective Strategy of Adjustment, and most importantly, to the Six Pillars of our proprietary model.  


Our optimisation model can be described by the following adjectives or adjectival phrases: Statistically Dependent, Formulaic, Econometric, Nonlinear, and Human-Centric.


Statistically Dependent


While their business models and customer bases are diverse, the underlying projects are still statistically dependent since they are subjected to the same specific environmental risk. There are thus correlation phenomena.


That is why Fikula Capital Management has carried out a thorough analysis of the risk factors that could systematically affect a high number of underlying projects to such an extent that the entire portfolio could potentially suffer a critical loss of capital.  


To tackle such adverse conditions, Fikula Capital Management has established a Dynamic Portfolio Insurance policy that will prevent our firm from facing a critical loss of capital.




While our margin of error is greater than the one of other types of investments, by saying “formulaic”, we mean that our decisions are the result of a quantitative decision-analysis process. We have reached our findings after an Optimisation under Organised Uncertainty modelling that led us from qualitative selection of the projects to our recursive risk management plan, having been through time-series forecasting, static financial modelling, dynamic Monte Carlo simulation, Real Options simulation, and portfolio optimisation.    




When it came to asset pricing, Fikula Capital Management has developed a multifactor model that called on the Arbitrage Pricing Theory. The Founder has relied on a structural approach that included in the same framework concepts coming both from financial theory and statistical methodology. 




Nonlinearity is an important feature of our optimisation model. From bottom to ceiling, we have resorted to nonlinearity to build, describe, and model the relationships between the relevant parameters and variables. Nonlinearity has been noticeably helpful in the following circumstances:


ü The whole theoretical platform introduced by Professor Defrenne rests on nonlinear thermodynamics


ü The Optimisation under Organised Uncertainty relies on a nonlinear optimisation approach and nonlinear constraints


ü Nonlinear extrapolation for time-series forecasts


ü Nonlinear transformations applied to the data before running a regression


ü A nonlinear rational expectations model to price assets


ü A nonlinear overall research process towards the Proprietary Model




As PhDs and holders of graduate degrees in psychology-related fields and as business consultants, Professors Delvaux and Defrenne have proposed a theoretical platform that is almost entirely built around human psychology, both at the level of the individual and at the level of the organisation.


Standing atop of that theoretical platform, the Founder has designed a comprehensive model whose Six Pillars are, for the most part, made from assumptions relating to behavioural psychology. 





Our private equity firm is built around human identity and behavioural psychology.