Evolution & limitations
How Agents Contribute to the Final Score Over Time
Each agent follows a structured lifecycle:
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Starts with an initial rule set
Based on research, backtests, and expert assumptions. -
Observes reality over time
Signals are continuously evaluated against real market behavior to understand how they correlate with performance and which indicators consistently matter versus those that prove irrelevant. -
Is iteratively improved
Thresholds and weights are adjusted over time, new features can be introduced, and ineffective components are removed as evidence accumulates.
As this process unfolds, the contribution of each agent to the final score becomes progressively more calibrated, and the system learns which signals are truly predictive and which are primarily noise. QQ Omega is designed as a living system that evolves continuously as new data is absorbed and models adapt.
Known Limitations of the System
QQ Omega is powerful, but not magic. Its outputs depend on data quality, model assumptions, and the broader market environment. Accuracy can be constrained by limited or immature data, particularly for new or opaque projects, and by assumptions that reflect current market structure and may require revision as conditions change. In addition, extreme events such as regulatory interventions, exploits, bans, or macroeconomic shocks can temporarily push markets outside the scope of any systematic model.
QQ Omega is a decision-support system, not an oracle, and it is not a substitute for sound risk management or capital discipline.