Ontonix Launches a Black Swan Protection Tool.

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Como, 7-th March. Ontonix launches a novel Black Swan protection tool. The tool generates automatically a multitude of feasible future scenarios and identifies the most unfavourable ones from a resilience and sustainability point of view. Scenarios are generated based on user-defined probability of an unlikely event occurring in any of the variables that describe the system. The tool allows to generate Black Swan-type events and helps users to define strategies to mitigate risk in circumstances that are very unlikely and potentially catastrophic. Indispensable for governments and decision-makers in a Crisis Management context, the tool exposes worst-case scenarios and identifies the factors that cause them.

Event severity is defined by the probability of occurrence in terms of multiples of standard deviations. A three-sigma event, for example, occurs with a probability of 0.27% while a six-sigma event with a probability of 0.00000002%. With this information, the system generates multiple scenarios based on the current Complexity Map and without the need to resort to lengthy Monte Carlo Simulation. In addition to the worst-case scenario, the most likely one and the most favourable ones are determined.

 “The tool offers a unique Black Swan protection capability, by allowing users to perform Stress Tests of arbitrary degrees of severity” said Dr. J. Marczyk, the founder of Ontonix. “In today’s turbulent world, punctuated by destabilizing events of increasing intensity and frequency, it is vital to know what a worst-case scenario is and which factors are critical. What were considered low-probability events in the past must be countered today on an almost daily basis. However, in context of high complexity, when turbulence and thousands of interdependent factors combine, decision making and risk management become extremely difficult. Our system automatically identifies the worst cases out of thousands and hints the appropriate strategies”, he continued. “This novel tool is particularly useful in conditions of pressure, conflict or high market turbulence, answers the basic questions: “how bad can it get?” and “what can I do to protect myself?”, he concluded.

Below is an example of a small system, for which the worst-case scenario is determined with at 4sigma level event (probability of occurrence of 0.0063%).

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Dr. Jacek Marczyk

Visionary, ex rocket scientist, businessman and writer with over 35 years of experience in QUANTITATIVE large-scale Uncertainty and Complexity Management in diverse fields (manufacturing, finance, economics).

Author of ten books on simulation, uncertainty and complexity management, rating.

Developed in mid 90s the theory of eigenvalue orbits, a generalization of the concept of eigenvalue.

In 2000-2005 has developed the first Quantitative Complexity Theory (QCT), including a comprehensive measure of complexity.

Founded Ontonix Complexity Management in 2005 in the USA and launched in 2006 the first commercial system for MEASURING and managing complexity: OntoSpace.

www.ontonix.com

In 2009 developed real-time technology to measure the complexity and stability of patients during operation or permanence in Intensive Care Units.

http://www.ontomed.net

Developed a new theory of risk and rating published in 2009 in a book entitled "A New Theory of Risk and Rating".

Over last decade develops quantitative complexity management (QCM) technology and solutions for applications in economics, finance, Risk Rating and Management as well as in Asset Management and medicine. In the past five years works towards the democratization of ratings.