Quantlux monitors markets continuously and applies risk-adjusted models in the background, giving parents and professionals a clear view of their options without hours spent at a screen.
Quantlux runs the analysis in the background, applying the same evaluation criteria every hour of every day. You set the parameters once — risk tolerance, time horizon, contribution pattern — and review the output when it suits your schedule, not the market's.
The model does not get tired or distracted. Each pair is re-scored on a fixed schedule using identical statistical criteria, which removes the inconsistency that comes with ad-hoc manual review.
*Indicative figure based on internal processing benchmarks; actual intervals vary by data provider latency.
The predictive layer combines historical volatility, correlation across related pairs, and recent momentum to produce a confidence score rather than a binary buy-or-sell instruction. A lower confidence score simply means the model recommends monitoring rather than acting — this is a deliberate design choice to avoid false certainty.
Risk management is not a one-off setting. The workflow below repeats continuously so that your exposure stays aligned with the parameters you set, even as markets move.
Price, volume and volatility data is pulled across 500+ pairs on a fixed schedule.
Each pair is scored for confidence based on historical patterns and current conditions.
Exposure is checked against your stated risk tolerance before any recommendation is surfaced.
You see a plain-language summary and the underlying figures, on your own schedule.
Position sizing is capped according to the risk profile set at onboarding, and real-time risk adjustment reduces exposure automatically when volatility rises beyond your stated threshold. Nothing is actioned outside those boundaries.
The system flags statistically significant shifts in correlated pairs and surfaces them for your attention. It does not attempt to predict short-term price movements with certainty — it narrows the range of options worth reviewing.
These are illustrative scenarios based on typical parameter settings, not guaranteed outcomes.
Monthly contribution amount, a 15-year time horizon, and a moderate risk tolerance setting.
The model weights longer-dated, lower-volatility pairs more heavily and reduces exposure automatically as the target date approaches, rather than holding a fixed allocation throughout.
No fixed contribution schedule, a longer 20-year horizon, and preference for minimal manual intervention.
The dashboard surfaces a monthly summary rather than daily alerts, reflecting the longer horizon and reducing the temptation to react to short-term noise.
A capital-preservation priority flag, a 3-year horizon, and a low risk tolerance setting.
The model limits recommendations to lower-volatility pairs and prioritises stability over growth, in line with the shorter horizon stated at onboarding.
We have kept this section free of testimonials. These are direct answers to the questions most often raised during onboarding.
Account access uses encrypted connections and two-factor authentication at login. Funds are held with regulated custody partners rather than within Quantlux's own infrastructure, and our platform only has permission to analyse and recommend — not to move funds without your explicit confirmation.
Data used for analysis is pseudonymised wherever possible and retained only for as long as needed to generate recommendations. Quantlux does not sell personal data to third parties. Full details are set out in our privacy policy, available from the footer of every page.
Initial setup — risk profile, time horizon and contribution preferences — typically takes under fifteen minutes. The dashboard begins populating with analysis on the first full scanning cycle after setup is confirmed.
No. Quantlux provides statistically significant analysis and risk-adjusted recommendations, not guarantees. All investment carries risk, and past patterns in the data do not assure future performance.
There is no obligation to commit funds before reviewing the analysis. Set up a risk profile, and see what the model surfaces for your own time horizon before deciding whether it's a fit.