Quali protocolli di sicurezza proteggono i dati dell'utente

Tutti i dati in transito e a riposo sono protetti tramite crittografia AES-256. L'accesso alla dashboard avviene attraverso autenticazione a più fattori e ogni sessione viene registrata in un log consultabile dall'utente.

Qual è il livello di liquidità del capitale allocato

Il capitale allocato a ciascun modello può essere ritirato secondo i tempi tecnici previsti dal ciclo di liquidazione della strategia in corso, che variano in funzione della posizione aperta al momento della richiesta.

Con quale frequenza vengono aggiornati i modelli IA

I modelli ricevono aggiornamenti in tempo reale sulla base dei nuovi dati di mercato elaborati. Le revisioni strutturali dei parametri di backtesting vengono invece effettuate su base periodica e documentate internamente.

Come viene calcolato l'indice di precisione predittiva

L'indice confronta le previsioni generate dal modello con l'esito effettivo delle posizioni chiuse in un dato intervallo temporale, esprimendo il risultato come percentuale di previsioni coerenti con il movimento di mercato osservato.

È possibile selezionare più modelli contemporaneamente

Sì. L'allocazione dinamica consente di distribuire il capitale su più strategie in parallelo, rispettando i limiti di esposizione complessiva definiti nel profilo di rischio dell'utente.

Immediate Connect It, data analysis interface and AI predictive models

Predictive analytics platform

AI-Driven Decision Optimization

We transform high volumes of market data into concrete operational guidance. Our models monitor historical best-performing strategies in real time and replicate their allocations via copy-trading, with risk mitigation built into every step of the process.

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Models monitored

128

Data update

< 400 ms

Asset classes covered

Data Engine

Technical density, not promises

The numbers below describe the operational behavior of the analysis engine in the last 24 hours. They are updated every calculation cycle and do not represent performance projections.

EUR/USD vol. +0.34%

S&P 500 corr. 0.61

Strategy M-07 active

Nasdaq vol. +0.19%

Rebalance cycle #4821

BTC/USD drawdown -1.2%

Engine performance metrics
Indicator	Current value	Average 30 days
Analysis Latency	0.38 s	0.41 s
Predictive Accuracy Index	71.4%	69.8%
Processed Data Volume	4.2TB	3.9TB
Active strategies in replication	54	49

Accuracy model M-07

74.2%

Accuracy model M-12

68.9%

Accuracy model M-21

70.5%

Methodology

How the copy-trading mechanism works

The system selects the strategies with the most solid historical performances, replicates their allocation through models called "Specular Strategies" and redistributes the exposure to contain portfolio volatility.

01 — Predictive modeling

Analysis of high-performance strategies

Each candidate strategy is subjected to rigorous backtesting on multi-year historical series, isolating recurring patterns and discarding those with drawdowns inconsistent with the declared risk profile.

02 — Automated execution

Mirror strategies in real time

Once selected, the strategy is replicated proportionally on the capital allocated by the user, with synchronized execution to minimize slippage compared to the original model.

03 — Risk diversification

Dynamic allocation between models

Capital is not concentrated in a single model: dynamic allocation distributes exposure across multiple inversely correlated strategies, reducing the impact of a single market event.

Operational path

Three steps to passive optimization

The activation process has been reduced to the essentials: data connection, model selection and continuous monitoring without the need for daily manual intervention.

01

Data connection

You connect your account or data source via encrypted protocol, giving the analytics engine access to the information needed to calculate allocations.
02

AI model selection

You choose from the available models based on the desired risk profile, consulting historical backtesting and predictive precision index of each strategy.
03

Passive optimization

The system independently manages the rebalancing of positions, while the user consults the dashboard to check the progress and updates of the model.

Use cases

Versatility in different market conditions

The same analytics engine serves different profiles: from the professional looking for a lateral income stream, to the manager needing large-scale algorithmic hedging tools.

Professionals

A secondary activity with limited management

For those who have a full-time job, automated copy-trading allows you to allocate a portion of your savings to a perimeter return, without requiring daily monitoring of the financial markets.

15 minAverage weekly time

3-5Recommended models at startup

Allocation example

Model M-07	40%
Model M-12	35%
Reserve liquidity	25%

Institutional analysis

Analytical depth for high volumes

The models apply the same rigorous backtesting logic used for private capital even on larger portfolios, maintaining the same dynamic allocation and volatility control parameters.

4.2TBData processed per day

07Asset classes analyzed

Risk coverage

Algorithmic risk management automatically reduces gross exposure when the correlation between active strategies exceeds the threshold set in the user profile.

Retail optimization

Access to logic historically reserved for professional operators

Through the dashboard interface, even small capitals can benefit from the same dynamic allocation logic normally applied to institutional portfolios, maintaining a return within the limits of the accepted risk.

54Active strategies in replication

AES-256Encryption standards

Operational note

Past performance of monitored strategies is no guarantee of future results. Each allocation carries a level of risk proportional to the chosen exposure.

Immediate Connect It, data analysis team working on predictive models

Who we are

An analytics infrastructure, not a promise of revenue

Immediate Connect It was created to provide a level of quantitative analysis normally reserved for professional structures, making it accessible through a single interface for monitoring and replicating strategies.

The daily work of the engine consists in continuously comparing the performance of the available models, updating the predictive accuracy indices and reporting relevant changes in the risk profile of each strategy.

Find out more

Technical questions

Security, liquidity and model updating

The following answers are formulated in technical and factual terms, without promotional purposes.

What security protocols protect your data

All data in transit and at rest is protected using AES-256 encryption. Access to the dashboard occurs through multi-factor authentication and each session is recorded in a log that can be consulted by the user.

What is the level of liquidity of the allocated capital

The capital allocated to each model can be withdrawn according to the technical times foreseen by the liquidation cycle of the current strategy, which vary depending on the position open at the time of the request.

How often are AI models updated

The models receive real-time updates based on newly processed market data. Structural reviews of backtesting parameters are instead carried out on a periodic basis and documented internally.

How the Predictive Accuracy Index is calculated

The index compares the forecasts generated by the model with the actual outcome of the positions closed in a given time interval, expressing the result as a percentage of forecasts consistent with the observed market movement.

You can select multiple templates at once

Yes. Dynamic allocation allows you to distribute capital across multiple strategies in parallel, respecting the overall exposure limits defined in the user's risk profile.