Meritahorro processes large volumes of market information with machine learning models and delivers recommendations backed by historically tested strategies, before you make an investment decision.
Results based on historical backtesting. Past performance does not guarantee future results.
Investors and business owners in Chile today have access to more market information than ever: reports, indicators, historical series, news. The volume grew faster than the human ability to interpret it consistently.
The usual result is decision by intuition, confirmation bias or paralysis in the face of too many variables. Meritahorro was built to sort that information and turn it into a concrete recommendation.
The Meritahorro engine combines predictive models with systematic backtesting: each strategy is evaluated against real historical data before being converted into a user-visible recommendation.
Technical validation does not replace the user's criteria: it provides a quantitative basis to decide with more information and less exposure to errors of interpretation.
The benefits of Meritahorro are based on the discipline of systematic analysis, not optimistic projections about future market behavior.
The model applies risk criteria consistently in each evaluation, reducing the influence of impulsive or emotional decisions.
Before suggesting a strategy, the system contrasts it with the historical behavior of the corresponding asset or market.
The models are recalculated as new data comes in, allowing the recommendation to stay aligned with the current market.
Instead of testimonials, Meritahorro lays out the technical workings of the process so you can evaluate its logic before trusting it.
Each module of the system—ingestion, modeling, backtesting, and presentation—is documented so that the user can understand the origin of a recommendation, not just its final result.
This allows us to distinguish between a signal supported by consistent data and a short-term fluctuation without historical support.
The information used for analysis is processed under encryption in transit and at rest. It is not shared with third parties for commercial purposes unrelated to the operation of the platform.
Access to account panels requires individual authentication, and credentials are not stored in plain text.
Each recommendation includes the historical period evaluated, the observed volatility and the level of consistency of the strategy against different market scenarios.
These metrics describe past behavior and are intended to support analysis, not as a guarantee of future results.
Reliability depends on the quality of the historical data and the consistency of the backtesting applied. Meritahorro displays the metrics behind each recommendation so the user can evaluate its strength, rather than presenting it as an absolute truth.
No. Backtesting demonstrates how a strategy would have performed in the past under specific conditions. It is an indicator of historical consistency, not a guaranteed projection of future performance.
The system is designed to explain its results in clear language. Data science training is not required, although it is recommended that you understand basic risk and investment concepts before acting on recommendations.
The models are periodically recalculated as new data comes in. The update frequency depends on the type of asset and the volatility observed in each market.
The platform is intended to function as an independent analysis layer. The availability of specific integrations depends on the contracted plan and can be reviewed with the support team.
Do you have another technical question? Check the details of advantages or contact support from your account.
Create an account to access the Meritahorro analysis engine or first review a technical demo of the backtesting process before deciding.