Green and Sustainable Finance

Graph-Massivizer aims to remove the limitations of financial market data providers (limited volume, reduced accessibility, very high costs, limited historic relevance) by enabling fast semi-automated creation of realistic and affordable synthetic extreme financial data sets, unlimited in size and accessibility. Peracton Ltd. uses the financial multiverse for improved AI-enhanced green investment and trading simulations, free of critical biases such as prior knowledge, over-fitting, and indirect contamination due to historic financial data scarcity and limitations. There are two major objectives to be achieved:

Objective 1

Generate an energy-efficient synthetic financial data (multiverse), validated using standard (green) financial investment and trading algorithms against real historical financial data sets.


Green Financial Data Multiverse sustainable extreme data archive.

Objective 2

Use Financial Data Multiverse for improved green AI-enhanced financial algorithms with reduced bias, risk, and higher performance.


Improved green financial algorithm portfolio for better investment returns and lower risk.