Next generation ai in finance

COMPLEXITY-BASED INVESTMENT STRATEGIES

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.

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.

ASSET MANAGEMENT

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

CONSULTING SERVICES

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.