De onde vêm os dados utilizados pelos modelos?

Os modelos utilizam séries históricas de preços, indicadores macroeconômicos públicos e dados de mercado provenientes de fontes especializadas em informação financeira, organizados e auditados antes de alimentar qualquer análise.

Como a inteligência artificial reduz erro humano nas análises?

A IA aplica critérios estatísticos consistentes a cada execução, eliminando variações causadas por cansaço, pressão emocional ou viés de recência, comuns em análises manuais realizadas sob prazo.

O backtesting garante resultados futuros semelhantes?

Não. O backtesting demonstra como um modelo se comportou em condições passadas específicas. Ele reduz incertezas metodológicas, mas não elimina o risco inerente a qualquer investimento futuro.

É possível manter liquidez ao utilizar a plataforma?

A plataforma não custodia ativos nem restringe movimentações. As análises são complementares à gestão que o investidor já realiza junto às instituições financeiras de sua escolha.

Quem revisa as decisões finais de investimento?

A decisão final permanece sempre com o investidor ou seu assessor financeiro. A plataforma fornece dados e cenários estruturados, não ordens automáticas de operação.

Ancorézio Trade — AI Platform for Investment Decisions

Market Context

The volume of information has surpassed the human capacity for continuous analysis

Financial markets generate, on a daily basis, a volume of data that can hardly be interpreted consistently by a single analyst or by traditional spreadsheets. News, macroeconomic indicators, liquidity movements and correlations between assets change relevance in a matter of hours.

For investors who depend on capital preservation — and not just the search for maximum return — this environment requires methods that separate noise from signal with statistical rigor, not just market intuition.

Ancorézio Trade was structured to act exactly at this point: processing large volumes of historical and current data, applying predictive models tested before any recommendation is considered.

Average reduction in exposure to high volatility events* Continuously monitored

Frequency of reevaluation of models Daily

Integrated data sources Multiple, auditable

Methodological basis Historical backtesting

Methodology

How the analytical process is built, step by step

Each recommendation generated by the platform goes through a fixed verification sequence. No step is ignored, regardless of the urgency perceived in the market.

Step 01

Data Ingestion

Structured collection of historical series, macroeconomic indicators and real-time market data, organized on a consistent basis for analysis.

Step 02

Predictive Analytics

Application of statistical and machine learning models to identify relevant patterns and design risk and return scenarios.

Step 03

Validation by Backtesting

Each model is tested against different historical periods before being considered suitable, verifying its behavior in different market regimes.

Step 04

Delivery and Tracking

Conclusions are presented in objective reports, with stated premises and limitations, allowing continuous review by the investor.

Historical Performance Data

Proven historical returns and observed risk mitigation

The numbers below reflect the retrospective behavior of the models applied to simulated portfolios in different historical windows. Past performance is no guarantee of future results.

Analyzed Period	Strategy	Accumulated Return	Maximum Drawdown	Annualized Volatility
2013 – 2018	Conservative Model	+42.10%	-6.80%	7.90%
2015 – 2020	Conservative Model	+38.60%	-9.20%	8.40%
2018 – 2023	Balanced Model	+51.30%	-11.50%	10.10%
2020 – 2024	Balanced Model	+29.80%	-8.70%	9.60%

*Backtesting data on simulated portfolios based on historical market series. They do not represent actual account results or projections of future returns. Individual results vary depending on risk profile and investment horizon.

Platform Features

Tools designed as decision support, not autopilot

Each resource was designed to expand the investor's analysis capacity, keeping the final decision under human control.

Monitor

Real-Time Insights

Continuous monitoring of market and portfolio indicators, with objective alerts on relevant changes in risk or liquidity, without automatic buy or sell recommendations.

Validate

Predictive Modeling

Return and risk scenarios constructed from validated historical data, presented with confidence intervals and explicit assumptions for investor review.

Design

Automated Reports

Periodic consolidation of portfolio performance and historical comparisons into objective documents, reducing the time dedicated to manual data organization.

Transparency and Security

How the methodology treats data, liquidity and limits of analysis

The questions below bring together the most recurring points among investors who are considering adopting analysis assisted by artificial intelligence.

Ancorézio Trade — data analytics team reviewing predictive models

Ancorézio Trade operates with one guiding principle: no recommendations are generated without the underlying model being tested against sufficient historical data. This discipline reduces the influence of short-term speculative tendencies on long-term decisions.

The goal is not to eliminate human judgment, but to provide it with a more consistent evidence base, reducing the cognitive bias common in decisions made under short-term pressure.

Where does the data used by the models come from?

The models use historical price series, public macroeconomic indicators and market data from sources specialized in financial information, organized and audited before feeding into any analysis.

How does artificial intelligence reduce human error in analysis?

AI applies consistent statistical criteria to each run, eliminating variations caused by fatigue, emotional pressure or recency bias, common in manual analyzes performed under deadline.

Does backtesting guarantee similar future results?

No. Backtesting demonstrates how a model performed under specific past conditions. It reduces methodological uncertainties, but does not eliminate the risk inherent in any future investment.

Is it possible to maintain liquidity when using the platform?

The platform does not custody assets or restrict movements. The analyzes are complementary to the management that the investor already carries out with the financial institutions of their choice.

Who reviews final investment decisions?

The final decision always remains with the investor or his financial advisor. The platform provides structured data and scenarios, not automatic operation orders.

Security protocols: The portfolio data provided by the user is treated with restricted access controls and used exclusively to generate the requested reports, following practices aligned with Brazilian data protection legislation.

Analytical clarity and predictive security for your assets