Abstract
AbstractThe Graph-Massivizer project, funded by the Horizon Europe research and innovation program, aims to create a high-performance and sustainable platform for extreme data processing. This paper focuses on one use case that addresses the limitations of financial market data for green and sustainable investments. The project allows for the fast, semi-automated creation of realistic and affordable synthetic (extreme) financial datasets of any size for testing and improving AI-enhanced financial algorithms for green investment and trading. Synthetic data usage removes biases, ensures data affordability and completeness, consolidates financial algorithms, and provides a statistically relevant sample size for advanced back-testing.
Publisher
Springer Nature Switzerland
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