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We can notice that financial markets are subjected to the collective influences, to the psychology of the agents, to the diversity of the information following the role and the interests of each of the economic agents. This information constitutes partially the low(weak) signals of the market the impact of which on the Mark To Market varies according to other information which can be macroeconomic, stock-exchange and others. The fractal methodology uses a very few input data (date and Mark To Market) to identify the dominant low signals at the time of the calculation and to obtain relevant indicators which express the right price of the market. The methodology allows to understand better the breaks and the unexpected reversals. .

Data Science Platform
The Data Science technology (Parallel Computing, Hadoop, Mape Reduce) reinforces the ability to instantly compute a multitude of relevant indicators from a large volume of data sources. It also allows us to provide secure remote access to our customers in order to facilitate the internal communication of the operational staff involved in the calculation. The system is portable on various operating systems
The calculated indicators are those commonly used in financial management. But their calculation is refined by the fractal methodology, which gives them a realistic sense.

Mathematical Engineering
Functional and technical support
Control of the NAV

For example for the control of the NAV, we use the date and the Mark To Market to get the low signals of the market from which, we calculate fractal indicators to obtain a fractal Benchmarck of the Fund, the economic indicators of the Fund, the fractal predictive value of the following NAV and the tolerance threshold. An alert is sent when the NAV estimated exceed the threshold.

The quality of indicators increases with the contribution of new information. Here are the back tests we did on some Funds.


Impact of the Liabilities on the NAV
Impact of the low signals on the Asset liquidity
Modelisation of the seasonality and Assets allocation
Controle of the Collateral quality
Modelisation of the know-how of the operational
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