Data Analysis
Combination of historical series of price, volume and derived indicators, processed by models that identify recurring patterns and divergences from the expected behavior of the asset.
PNAF Plataforma processes real-time market data, applies documented predictive models, and publishes performance records that can be consulted by verified users, rather than relying solely on internal projections.
No subscription commitment during the demo trial period.
Example of screen composition. The real data is available after account creation.
Each signal generated by the platform goes through three distinct layers before reaching the user: data processing, risk assessment and execution conditions.
Combination of historical series of price, volume and derived indicators, processed by models that identify recurring patterns and divergences from the expected behavior of the asset.
Each recommendation is accompanied by exposure metrics and estimated loss scenarios, calculated before any entry suggestion is presented to the user.
Signals are continually updated as new data enters the system, allowing you to adjust or cancel recommendations before the execution window closes.
The decision logic is divided into sequential steps, each documented internally, so that the analytical user can understand the origin of each signal.
Prices, volumes and technical indicators are collected from licensed market feeds and public data sources.
Data is cleaned, temporally aligned, and converted to a common format before entering models.
Several models evaluate the same set of data in parallel, each specialized in a type of pattern or time horizon.
The final recommendation is only issued after passing risk controls, with the result recorded in the public history.
The platform uses licensed market feeds for price and volume series, complemented by macroeconomic data from public sources. No third-party private data sources are used without authorization.
Each active model has an internal technical sheet with the variables used and the date of the last revision, available for consultation in the registered user's account area.
Instead of relying solely on projections, the platform maintains a consultable history of recommendations issued and the respective observed results.
Illustrative representation of the graph structure. The real values of each strategy are available after account activation, filtered by period and type of asset.
Each active strategy maintains its own record with date, signal issued and observed result, without selective aggregation of favorable results.
Records are visible for both signals that reached the defined objective and those that did not, allowing independent evaluation by the user community.
The same analysis infrastructure serves different purposes depending on the type of decision being made.
Users who trade with short horizons use real-time execution signals to evaluate entry and exit points, cross-referencing the model recommendation with their own technical reading of the market.
Public history allows you to compare the performance of different strategies before deciding which one to track most consistently.
Managers evaluating medium-term scenarios use data analysis modules to support capital allocation and planning decisions, with less dependence on short-term signals.
The risk mitigation layer is used to structure alternative scenarios before a decision is presented internally.
Direct answers to the most common questions from users with technical or financial backgrounds.
Processing time varies depending on system load and asset type, as some models require more validation steps than others. The platform indicates, for each signal, the exact time of the last reevaluation.
Connections between the user and the platform use encryption in transit. Data for each account is logically segregated and access to sensitive features is controlled by permissions associated with the user profile.
The models are trained with historical series and periodically reevaluated against new data. Relevant changes to a model's methodology are recorded in the respective technical sheet, with the date of the review.
Yes. The history of signals and results is accessible to users with a verified account, including cases in which the result did not correspond to the initial objective of the signal.
Access to the demo includes viewing historical performance and setting up a test strategy in a simulation environment.
Request Demo AccessAccess to the demo does not imply a subscription commitment.