Juste Capitholm — predictive analytics interface displaying real-time financial data feeds
AI decision support platform

Artificial intelligence at the service of your strategic decisions.

Harness the power of predictive models to turn your data into growth opportunities and minimize your financial risks.

The dashboard aggregates market feeds, calculates a risk score per position and publishes each recommendation in a searchable log, before and after execution.

Total transparency

Verified performance logs

Each recommendation issued by the predictive engine is time-stamped and archived. Real-time data remains viewable, regardless of the result obtained.

Performance report

Continuous publication

Each recommendation is archived as soon as it is issued, before any confirmation of results.

Recommendation History

Open consultation

All market cycles covered by the platform remain accessible to registered users.

Tracked data streams

Multi-market

Stocks, currencies, commodities and indices are ingested in parallel by the analysis engine.

Methodology

Documented

The operation of the model is described before registration, without exposing the proprietary parameters.

View the full methodology →
Technical stack

Analytical capabilities

Three pillars structure the engine: data ingestion, risk assessment and execution at scale.

01

Real-time multi-source analysis

The engine crosses order books, economic news and sentiment indicators to produce a consolidated reading of the market, updated continuously rather than at fixed intervals.

02

Predictive risk modeling

Each position is associated with a risk score calculated on historical scenarios and inter-market correlations, making it possible to anticipate sensitive arbitrage points.

03

Scalability of automated decisions

The infrastructure applies the same decision rules to an increasing volume of positions, without degradation of processing time or repeated manual intervention.

Juste Capitholm — technical team working on financial data analysis models
About

A platform designed for quantitative analysis

Juste Capitholm develops predictive models applied to financial markets. The objective remains constant: to reduce the time between the appearance of a signal in the data and the resulting decision.

The technical team combines data engineering and human supervision on risk parameters, in order to limit biases linked to new market configurations.

Learn more about the platform
Operation

From raw data to decision

The process takes place in three steps, without exposing the internal parameters of the model.

1

Ingestion

Market flows, macroeconomic data and news sources are collected and normalized continuously, before any analytical processing.

2

Treatment

The engine applies its risk classification and scoring models, eliminating anomalies that would distort the reading of the market.

3

Optimization

Recommendations are prioritized according to the risk-return pair, then transmitted to the user or to automated execution, reducing the weight of human bias.

Concrete applications

Three profiles, three uses

The recommendations adapt to the decision horizon of each user, from the long term to the very short term.

Institutional investors

Capital Allocation

Distribution of positions according to an aggregated risk score, revised with each significant change in the data flows monitored.

Strategic planners

Market entry timing

Identification of favorable windows for deployment, by combining macroeconomic conditions and technical indicators.

Day traders

Arbitrage and hedging

Alerts on intraday valuation gaps, with a risk level calculated before any position is taken.

Technical questions

Security, integration and latency

Direct answers to the most frequent points of vigilance before integration.

How is the data secured?

Flows pass through encrypted connections and personal data is processed in accordance with the GDPR. No account data is shared with third parties for commercial purposes.

Can the platform integrate with my existing tools?

A documented API allows the platform to be connected to existing execution or reporting systems, without dependence on a single interface.

What is the latency of the predictive engine?

The calculation time is optimized for intraday uses. The exact latency depends on the selected data stream volume and is shown in the performance report.

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