Skip to main content

Refonte Infini Launches Its Latest AI Innovation, an Advanced Scientific Trading Robot

Newsfile - Tue Oct 3, 5:02PM CDT

Paris, France--(Newsfile Corp. - October 3, 2023) - Refonte Infini, an innovative company at the intersection of the financial and AI sectors, has announced it is now making its newest scientific trading robot available to the public. The innovative tool simplifies crypto trading by leveraging the power of science, math, and AI, going beyond traditional models on the market.

While traditional trading models use only programming to initiate trades, Refonte Infini's Scientific Trading Robot combines scientific methodology such as mathematics, statistics, science computing, programming coding, and finance technics. Refonte Infini's founder Yvan Jorel Ngaleu Ngoyi, Ph.D., co-authored a paper with professor Elie Ngongang outlining this methodology in detail in its globally renowned and referenced paper "Forex Daytrading Strategy: An Application of the Gaussian Mixture Model to Marginalized Currency Pairs".

Cannot view this image? Visit:

Figure 1

To view an enhanced version of this graphic, please visit:

Cannot view this image? Visit:

Figure 2

Cannot view this image? Visit:

The paper and Refonte Infini's model have been gaining international attention for this revolutionary model decentralizing the financial world. It leverages the Gaussian Mixture Model to determine clusters in the crypto market, the Hidden Markov Model to determine regime changes in the crypto market, Jonhson Su's model for the entry point, the Trailing Stop Loss for the exit point, and more than 100,000 explanatory variables (or features) significantly reducible by using stepwise regression.

"We are thrilled to be able to offer our Scientific Trading Robot to the general public after refining it for years," said Yvan Jorel Ngaleu Ngoyi, Refonte Infini founder.

To learn more about and register to use Refonte Infini's Scientific Trading Robot, visit

CONTACT: Yvan Jorel Ngaleu Ngoyi
PHONE: 00 33 769546557

To view the source version of this press release, please visit