True Accrumance runs predictive models against live market data and records every recommendation. The outcome of each one — win or loss — is written to a log that registered users can review in full.
True Accrumance ingests price, volume and volatility data across major crypto markets and runs it through a set of predictive models. The output is a risk-adjusted recommendation, not an instruction.
You keep control of execution. The system is built to reduce the volume of low-quality decisions an investor has to filter through manually, using data rather than intuition as the starting point.
Every recommendation the model produces is timestamped and logged before its outcome is known, which is the basis of the verification process described below.
A performance claim is only useful if it can be checked. This is the process we use to make that possible.
Every recommendation and its outcome is timestamped and written to an append-only log the moment it occurs. Entries cannot be edited after the fact, only appended to.
A daily snapshot of the log is stored outside True Accrumance's own infrastructure. This separates the record of what happened from the system that generated it.
Snapshots are made available to registered users for download. Any historical entry can be checked against the published record at the time it was logged.
A daily reconciliation compares the live log against the previous day's snapshot. Discrepancies are flagged before the next trading session and disclosed, not silently corrected.
The log includes losing positions alongside winning ones. A performance log that only shows favourable outcomes is not a verification log — it is marketing.
No single component of this platform makes a decision on its own. Each stage below checks the output of the one before it.
The model reviews historical price movement, volume and volatility across several time frames. It outputs a probability-weighted range for short-term movement, not a single fixed prediction. Where the data does not support a confident range, the model returns no recommendation.
Before any recommendation is surfaced, a separate process checks position size against account-level volatility limits. Recommendations that breach a preset risk threshold are suppressed at source. They are not shown as an optional, riskier alternative.
Market data feeds refresh continuously. Recommendations carry a fixed validity window and expire automatically rather than remaining on screen once the underlying conditions have changed.
This table mirrors the structure of the log made available to registered users. It does not display live figures — access to the current log is granted on request.
| Date | Asset pair | Model signal | Logged outcome | Verification status |
|---|---|---|---|---|
| — | — | — | — | Available on request |
| — | — | — | — | Available on request |
| — | — | — | — | Available on request |
Direct answers to the questions we are asked most often, without qualifying language.
Yes. Crypto markets are volatile and the model's recommendations are statistically probable outcomes, not guaranteed ones. The system is designed to reduce exposure to low-quality decisions, not to remove market risk.
Fee structure is disclosed in full before you commit any capital, and it is available on request through the contact page. We do not vary disclosed fees based on account size after the fact.
Model output is reviewed against the independent log snapshot on a fixed schedule. Any deviation between what the model recommended and what was logged is investigated and disclosed, not adjusted quietly.
Yes, regularly. The model returns a probability-weighted range, not a certainty. Losing positions are recorded in the same log as winning ones, and both count toward the published accuracy figures.
The model produces a recommendation and a risk assessment. Execution requires a separate, deliberate action from the account holder — the system does not place trades without that step.
Request access to the full performance log, or read the methodology paper first. There is no obligation attached to either.