Prumo Quinhena uses predictive models to automate your crypto strategy, minimizing risk and optimizing each entry point without complications.
The system identifies price floors within a defined time window, instead of buying on fixed dates without market context.
Market volatility stops 70% of new investors before their first trade. For a university student, the problem is not just the risk: it is the time available to manage it.
Reviewing charts between classes, term papers, and coursework is not a sustainable method of portfolio management. Manual tracking requires constant attention that competes directly with the academic agenda.
Each ad hoc review of the market consumes time that does not translate into better entries: the frequency of attention does not replace a consistent decision criterion.
Prumo Quinhena combines series of historical prices, market volume and volatility variables in the same decision model. The goal is not to predict the future with absolute certainty, but rather to reduce the variance of input decisions using quantifiable and repeatable rules.
The model rules are documented and can be reviewed before activating them: there are no black box signals or recommendations without explainable criteria behind them.
The model does not buy on fixed dates by default. Analyze data in real time to locate the best entry point within a limited time window.
The system collects price, volume and volatility from multiple exchanges in short intervals, building a continuous basis on the behavior of the asset.
Regression models estimate the probability of a local price floor within the defined window, instead of executing purchases on fixed dates without market context.
When the model conditions are met within the window, the system executes the corresponding partial purchase, without manual intervention or delays due to indecision.
The decision engine is supported by regression models trained with historical price and volume series. Each potential entry is evaluated against a drawdown mitigation threshold, designed to limit exposure in steep downside scenarios.
This platform is aimed at low-risk entry into volatile assets, not short-term speculative trading. The system does not run leverage or intraday trading strategies.
The connection keys with the exchange are stored encrypted and are not shared with third parties. System access is limited to operations necessary to run the model.
Before being applied in real time, each setup is backtested over previous market cycles, comparing the model's output against a simple periodic buying strategy.
A student allocates a fixed portion of his monthly payment or income from odd jobs to Prumo Quinhena. The system splits that amount into smaller entries, executed only when the model detects favorable conditions within the monthly period, instead of purchasing on an arbitrary date.
With a scholarship fund or one-time savings, the logic shifts from frequency to scale: the same model distributes capital into several spaced inflows, prioritizing reducing exposure to a single price point over investment speed. The initial amount does not determine the result of the model: the same input logic works with small amounts and scales without strategy changes when the available capital grows.
Funds remain in your connected exchange account at all times. Prumo Quinhena only sends purchase orders based on the model; Withdrawal and liquidity depend on the rules of the exchange, not the platform.
The model does not automatically stop purchases in the event of a drop: it evaluates whether that drop represents a price floor within the defined window. If the drawdown mitigation threshold is not met, the next entry is deferred until the next analysis cycle.
Platform costs are detailed in the technical documentation before connecting an account. The fees charged by the exchange for each trade are independent of Prumo Quinhena and are displayed in each strategy configuration.
The model processes public market data, such as price and volume, and does not require personal information beyond exchange connection credentials, stored encrypted. This data is not sold or shared with third parties.