Vivo Capitecto – Algorithmic Execution Analytical Dashboard on Financial Market Background

Artificial intelligence for investment

Algorithmic optimization. Impeccable execution.

Vivo Capitecto analyzes the market in real time to identify local lows and execute your DCA strategy at the right time, rather than at fixed time intervals. The result: a more efficient average entry price, calculated by a predictive engine designed for demanding traders.

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Smart tickets

A DCA that responds to the market, not the calendar

The traditional DCA purchases on predetermined dates, without considering the price structure. The Vivo Capitecto engine replaces the calendar with a local minimum detection model: it evaluates volume, volatility and momentum before deciding when to execute each leg of the purchase.

Each entry is calculated based on the current condition of the asset, not a fixed schedule. This allows capital to be distributed with greater sensitivity to short-term fluctuations, without manual intervention.

Entry criteria Data-driven
Frequency Adaptive
Supervision Automated

DCA by calendar vs. DCA by signal

By calendar

Make purchases on fixed dates, without considering the current price.

By signal (AI)

Executes purchases when the model detects favorable entry conditions.

Sensitivity

Void against intraday movements.

Sensitivity

Continuous, based on real-time market data.

Adjustment

Manual, requires periodic review of the inverter.

Adjustment

Automatic, managed by the predictive engine.

Predictive engine

The technical advantage behind each execution

The system processes high volumes of market data and adjusts its risk parameters continuously, without relying on manual reviews.

Analyze

Real-time market data

Processes price, volume and volatility streams from multiple sources simultaneously, identifying entry patterns before they run out.

Mitigate

Exposure and execution risk

Adjusts the size of each purchase tranche based on current volatility, limiting exposure in adverse market conditions.

Scale

Multi-asset operation

Manages multiple DCA strategies in parallel without degrading the response speed of the decision engine.

Methodology

From raw data to executed order

The model follows a fixed sequence of four phases. Each phase produces a verifiable result before moving on to the next.

1

Data ingestion

Price, order book and volume data is collected from connected markets, normalized for immediate analysis.

2

Pattern recognition

The model identifies recurring structures associated with local minima, comparing them with the historical behavior of the asset.

3

Decision optimization

The optimal size and timing of the next entry is calculated, considering the available capital and the defined risk limits.

4

Automated execution

The order is sent to the connected broker or exchange without manual intervention, with confirmation recorded in the account history.

Use cases

The same engine, different investment profiles

The system configuration is adapted to the time horizon and operating volume of each profile.

Institutional investor

Distribute high-volume orders into tranches to reduce price impact, executing each tranche when liquidity conditions are favorable.

Active trader

Receives high-frequency adjustments on the size and frequency of entries, tailored to the intraday volatility of the asset.

Portfolio manager

Configure a long-term accumulation with fixed risk limits, delegating to the engine the selection of the exact moment of each purchase.

Infrastructure

Designed to operate alongside your broker

Vivo Capitecto connects via API to common execution platforms. The decision engine works independently of the broker, so the input logic remains constant when changing providers or assets.

Vivo Capitecto: analysis team working on market data panels
Frequently asked questions

Infrastructure, security and reach

How is access via API protected?

The keys are generated with permissions restricted to trading operations, without authorization to withdraw funds. Traffic is encrypted end-to-end and credentials are stored separately per account.

What is the latency of the execution engine?

The time between the signal generated by the model and the sending of the order remains in the range of milliseconds, subject to the latency of the connected broker or exchange.

What assets are compatible with the system?

The engine operates with crypto assets and currency pairs available on connected exchanges. The list of supported assets depends on the integration enabled on each account.

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