Analyze models
golatest predictive analytics dashboard showing financial data series
Predictive analysis Backtesting Risk management

Investment decisions backed by backtested models, not intuition

golatest processes market data in real time and contrasts it against historical series to generate quantified recommendations. Each signal is accompanied by its statistical evidence of origin.

Analyze models See technical documentation
Continuous backtesting About verifiable historical series
Real-time processing Optimized latency for LATAM
The problem

Manual analysis does not scale when the decision depends on location

For a remote professional managing positions from different time zones, manually reviewing indicators, news and market correlations consumes hours that are not always available between meetings or commutes.

The gap is not one of information—there is more data available than ever—but of consistent processing capacity. A human analyst cannot evaluate thousands of variables simultaneously or repeat the same decision criteria without fatigue or bias.

Predictive advantage begins where manual review ends

A model that has already been tested against historical data does not eliminate risk, but it allows it to be compared with concrete evidence before assuming it.

golatest data analysis interface used by a remote professional
The solution

A backtesting engine with real-time processing

The system combines three components that work in a coordinated manner: historical validation, continuous data ingestion and risk mitigation models applied before issuing any recommendation.

Backtesting engine

Validation against historical series before each recommendation

Each strategy is first run on past data to measure its performance in different market regimes. No signal is displayed without this contrast register.

  • Simulation over multiple time windows
  • Comparison between high and low volatility conditions
  • Documented record of each test run
Real-time processing

Continuous market data ingestion

The feeds are constantly updated and normalized before entering the model, reducing the lag between the market event and the generated signal.

Risk mitigation

Quantified limits per position

Each recommendation includes maximum exposure parameters calculated from the historical volatility of the asset, not an arbitrary fixed value.

Methodology

From raw data to a verifiable recommendation

The workflow is divided into three sequential phases, each independently auditable.

Data ingestion

Series of prices, volume and macro variables are collected from structured market sources, with normalization and quality control before processing.

AI modeling

The models apply pattern recognition to the normalized data and contrast it against their historical performance documented in backtesting.

Output recommendation

The result is delivered with its level of statistical confidence, the time horizon considered and the suggested risk limits.

Transparency

The logic behind each signal is documented

Instead of showing testimonials, golatest exposes the structure of its backtesting reports so that each user can evaluate the criteria before trusting it.

Illustrative panel — backtesting reporting structure

Reference data, not guaranteed results

Backtest windows evaluatedMultiple cycles
Retraining frequencyPeriodic
Data originPublic market series
Reported confidence levelBy signal

This panel represents the structure of the report, not a screenshot of the live product. The historical performance of a model is not a guarantee of future results.

Access

Access levels depending on the depth of analysis required

Current values are shared during the account verification process, prior to first access to the panel.

Base Analysis

To evaluate the system with real data

  • Access to signals with reported confidence level
  • Backtesting history by strategy
  • Data update at standard intervals
Request access

Advanced Analysis

For active portfolio management

  • Everything included in Base Analysis
  • Real-time processing with lower latency
  • Configurable risk parameters per asset
  • Exportable backtesting reports
Request access

Institutional Use

For larger equipment and volumes

  • Everything included in Advanced Analysis
  • Integration via dedicated technical documentation
  • Joint review of risk criteria
Coordinate technical conversation
Frequently asked questions

Technical and regional aspects relevant to Argentina

How is account data protected?

Access credentials are stored encrypted and communication with the panel is carried out via a secure connection. No account data is shared with third parties outside the service.

What latency can I expect operating from Argentina or other countries in the region?

The processing infrastructure is distributed to reduce response time in connections from Latin America. The final latency also depends on the quality of the user's local connection.

How often are the models updated?

The models are periodically retrained based on new market data. Each update is documented along with its performance comparison with the previous version.

Does the system guarantee investment results?

No. The recommendations are based on statistical evidence and historical models. Past performance does not guarantee future results and the final investment decision is always the user's.

Review the logic of the model before deciding

Access the technical documentation of golatest and evaluate the backtesting criteria with which each recommendation is built.

Analyze models See technical documentation