Next generation ai in finance


Optimum utilizes the Quantitative Complexity Theory adopted in various industries since 2005. A proven technology.

Optimum is the first and only company to launch complexity-based investment strategies.

Our proprietary measure of correlation enables us to better manage risk and volatility.

Complexity metrics provide superior market early-warning signals in high volatility and turbulence.

“Realise that everything connects to everything.”

— Leonardo da Vinci, 1484


The Technology


Next Generation AI in Data Analysis

Conventional linear correlation measures, often used in association with designing a portfolio and managing risk, may provide misleading results.

Optimum adopts a more relevant measure of correlation - generalized correlation - which accounts for non-linear aspects of data. The method is based on proprietary model-free cognitive AI technology which transforms data scatter plots into images, emulating an expert actually looking at data. This is AI 2.0.

The huge advantage of generalized correlations are numerous. First of all, they capture correlations that classical techniques can miss. Secondly, they discard correlations that are identified mistakenly by conventional means. Finally, they provide realistic values of correlation unlike, for example, Pearson correlations, which can often be excessively high.

However, the biggest advantage of generalized correlations is that they don’t require a cut-off value in order to differentiate between significant and negligible values thereof. The method of computation naturally establishes which correlations are significant and which are not.

The method for the computation of generalized correlations has its roots in quantum physics and nonlinear mechanics. For more than a decade, our technology is being used in numerous sectors, such as defense, manufacturing and medicine.

What We Do With Data

Data is analyzed by emulating the brain as it ‘sees it’ in the form of an image, without the need to build math models. This allows us to determine the true structure and nature of data.

Our measure of correlation enables us to better reflect the level of risk associated with an individual company, portfolio of companies or other financial instruments or asset classes.

Visual Analytics - Cognitive Artificial Intelligence

Visual Analytics - Cognitive Artificial Intelligence

A popular and conventional correlation is the linear correlation by Pearson. Pearson’s correlations function properly when applied to data which is linear in character. In cases which include data concentrations, clustering, bifurcations or other forms of discontinuity, applying linear correlations is outright wrong. The results of linear correlation analysis may in fact provide outcomes which can induce unjustified optimism and distort significantly any risk-type calculations.

The surprising fact is that this shortcoming of linear correlations is widely known and yet neglected by the mainstream of fund managers and analysts. Traditional models which are used to compute risk or degree of asset diversification in investment portfolios may be easily proved to be incorrect. 

The new information and insight which complexity quantification brings makes it possible to radically rethink asset selection risk management and therefore portfolio design.

The Bottom Line

1. Each portfolio can only reach a specific maximum value of Complexity called “Critical Complexity”.
2. Close to its Critical Complexity, a portfolio becomes fragile and should be restructured to remove its Complexity Drivers.
3. Prior to a crisis portfolio complexity tends to fluctuate rapidly. Complexity spikes are formidable early-warning signals.



Optimum has launched specific complexity-based Investment strategies together with Institutional partners. In particular, Optimum is trading complexity-based Long/Short equity portfolios.

Our Long Strategy is based on the so-called Optimum Complexity region which exists for every stock universe.

The Short Strategy is based on early-warning signals deriving from complexity analysis of macroeconomic indicators.

Market-specific early warning indicators factsheet


Measuring Systemic Risk

Optimum offers a futuristic risk-assessment methodology which goes beyond traditional models used by most risk managers. A typical application is drawdown early-warnings in Trading Desks. Systemic risks are determined taking into account very large amounts of information such as Balance Sheets of thousands of companies, market indices, macr-economic indicators. Processing this informatio, reveals new broad-scope and broad-scale insight into the structure and dynamics of risk.

market-specific early-warning signals

Complexity analysis of macroeconomic indicators offers an efficient early-warning signal as it produces sharp spikes prior to major market drops. Such information is key in establishing efficient shorting strategies.

Systemic Portfolio Analysis

Integrated Systemic Portfolio Analysis includes external factors (macro-economic parameters, interest rates, unemployment, GDP growth, currency exchange rates, etc.) when it comes to determining the real exposure of complex portfolios or funds. In essence, a portfolio or a fund is analyzed together with its ‘ecosystem’ in an integrated fashion, so that its interaction with the economy is taken into account.


Optimum’s compact team, with the core members working together for almost a decade, operates out of London.

We have extensive expertise in quantitative investing, unconventional risk and complexity management, radically innovative data treatment and passion for science.

daniele cosulich


Daniele brings and extensive experience of fund raising and fund management with managerial and entrepreneurial skills in different cultures and environments. Former Senior Advisor to Method Investments & Advisory, a boutique investment bank based in London.  He was part of the team who created a Eur 5.5bn Private Equity coffe fund to support the strategy of JAB Holdings. Former  CFO of Green Comm Racing, the Nautico de Valencia’s challenger of the 34th America’s Cup. Former Executive Director for Octant Capital.

Mr. Cosulich  graduated from European Business School in London with a first class honours degree in International Business Administration. He also held various specialisation courses such as the AIAF Training Course for Financial Analysts  (certified by EFFAS). Member of the “Leader del Futuro” Ambrosetti Club.

Jacek Marczyk Ph.D.


Ex rocket scientist and author of ten books on uncertainty, complexity management and rating, Dr. Marczyk has developed the Quantitative Complexity Theory (QCT) and a new complexity-based theory of risk and rating. With over 30 years experience in data analysis, In 2005 he founded Ontonix, the first company to develop Quantitative Complexity Management tools. In 2015 he founded Singapore-based Universal Ratings.

Dr. Marczyk he has held various executive positions and has worked for companies such as EADS, BMW AG, Centric Engineering Systems, ESI, Silicon Graphics and MSC Software. He holds MA degrees in Aeronautical and Aerospace Engineering from the Polytechnics of Milan and Turin, and a Ph.D. in Civil Engineering from the Polytechnic University of Catalonia.

Andrea calandruccio


Mr. Calandruccio began his career in Investment Banking, advising on a number of private equity acquisitions and financing transactions in Europe and US and serves as Strategic Advisor to Icon’s Investment Committee. He later joined Marex Spectron proprietary trading team as a senior derivatives trader, developing and implementing several successful statistical arbitrage models. Andrea holds a MSc in Investment Management from Cass Business School and is currently pursuing a PhD in Applied Mathematics in the Complexity and Networks Group at Imperial College London.

Rayane Bensafia


Prior to joining Optimum Complexity Rayane has worked at Meeschaert Asset Management in Paris as Portfolio Manager Assistant, performing credit and convertible bonds analysis and operating daily cash and liquidities of funds. Subsequently, he worked at Leonteq Securities AG in Monaco, managing full client relationship and client requests for primary market trades. With background in mathematics and physics, Rayane focuses on complexity-based portfolio design strategies.

Mr. Bensafia graduated from the EDHEC Business Schoo, majoring in Equity Derivatives, Asset Pricing, Fixed Income, Portfolio Theory and Risk Management.

patrick hofmanN


Mr. Hofmann is an accomplished entrepreneur with interests in a range of sectors.  He is a founder and partner in Sundance Partners Ltd, which is regarded as London’s largest premium fruit juice manufacturing and distribution company.  He is European Operating Partner at Blue Cloud Ventures, a New York based software-focused venture capital firm. Patrick is also a partner at Clarius Capital Partners, a London-based investment advisory firm.

Previously, Patrick was an investment banker in the debt capital markets group at Bear Stearns covering the European technology, media and telecom sectors as well as being responsible for the European automotive sector.  Prior to Bear Stearns, he worked in debt capital markets at Banque Paribas and UBS. Mr. Hofmann graduated from the European Business School