Optimize Decisions

Data intelligence at the service of your capital

Mintarvek analyzes large volumes of financial information and applies proven predictive models through backtesting – the verification of a strategy against historical data – to provide you with clear recommendations about your capital, without the need to program or interpret spreadsheets.

Explore Strategies

The image schematically represents the type of market time series that our models continuously process to identify relevant patterns.

The problem

Too much information, too little signal

Every day thousands of reports, quotes and news related to financial markets are generated. Most individual investors and small business owners do not have the time or the tools necessary to distinguish which data is relevant to their portfolio and which is simply statistical noise.

Our predictive models—systems trained with historical data to estimate the probability of different future scenarios—filter that information and translate it into understandable indicators, explained in plain language and without unnecessary jargon.

Mintarvek: visual representation of a predictive model analyzing market data
Methodology

How we build and verify each strategy

Before suggesting any adjustments to a portfolio, we put the corresponding strategy through a four-phase validation process, designed to reduce reliance on intuition.

  1. 01

    Data collection

    We bring together historical series of prices, volumes and macroeconomic indicators from different markets, homogenizing the formats so that they are comparable to each other.

  2. 02

    Predictive modeling

    We apply machine learning algorithms that identify recurring patterns and estimate probabilities of future behavior, without guaranteeing results, but offering a verifiable statistical basis.

  3. 03

    Backtesting

    We simulate each strategy over past periods that the model did not use during its training, checking how it would have behaved in different market cycles, including those with greater volatility.

  4. 04

    Continuous monitoring

    Once in production, we periodically compare actual versus simulated performance and recalibrate the model when market conditions change significantly.

Simulated performance (backtesting) Observed performance after launch

Schematic and illustrative representation, without actual numerical values, showing how we compare the simulated behavior of a strategy with its subsequent behavior. It is not a projection of future returns.

Capabilities

Three pillars on which the platform rests

Real time analysis

Mintarvek's systems process market data continuously, updating their estimates as new information arrives, rather than relying on one-off reports that become out of date within hours.

The monitoring panel shows the evolution of each indicator along with the date of its last update, so you always know how recent the information consulted is.

Risk mitigation

Each recommendation includes an estimate of the associated risk, calculated from historical volatility and correlation between assets, so you can assess the balance between potential return and exposure before deciding.

The alert thresholds adjust to the profile declared by each user, avoiding generic recommendations that do not take into account their risk tolerance.

Scalability

The same infrastructure that analyzes a single portfolio can be expanded to manage multiple portfolios or lines of business, without compromising system response time.

This allows both an individual investor and a small company with several business units to use the same analysis engine.

Transparency

Risk and AI FAQs

Do predictive models guarantee profitability?

No. No statistical model can guarantee future results. What we offer is a decision basis based on historical data and the observed behavior of similar strategies throughout different market cycles.

Do I need technical knowledge to use the platform?

There's no need. The conclusions of the analysis are presented in plain language, including the corresponding technical term in parentheses when relevant, so that you can go deeper if you wish without this being essential to make a decision.

How is my data protected?

The financial information you provide us is stored encrypted and is used exclusively to generate your own analysis. It is not shared with third parties for commercial purposes.

What happens if the market changes unexpectedly?

Our models are recalibrated periodically. When significant deviations are detected between simulated and real behavior, the system flags the incident so that the team can review the corresponding strategy.

Can I stop using the platform at any time?

Yes. You maintain control over your data and the continuity of the service at all times, without mandatory retention periods.

The technical terms used in this section—backtesting, predictive model, historical volatility—are explained within the text itself, so that it is not necessary to consult a separate glossary to understand how the platform works.