Scalping optimization
Latency-sensitive execution paths prioritise order routing speed, suited to positions held for seconds rather than full sessions.
Quantitative Edge / Automated Logic
Atom Finance filters live market data through predictive models built to separate signal from noise, so you review fewer charts and act on fewer, higher-conviction positions.
Predictive Precision
Atom Finance ingests high-velocity market data — tick-level pricing, order book depth and macro releases — and screens it for non-obvious correlations that are difficult to track manually across a full UK trading session.
| Data refresh interval | 250ms |
|---|---|
| Correlation lookback | Rolling 90 sessions |
| Asset coverage | Equities, FX (GBP pairs), Futures |
| Model retraining | Daily, post-close |
| Deployment time | Under 60 seconds |
One-click deployment
Link your brokerage through a secure, read-first API integration. Credentials are never stored in plain text.
Real-time risk modelling scans your existing exposure against live volatility and correlation data.
Orders are placed automatically once your custom threshold parameters are met, with manual confirmation available if you choose to require it.
Dynamic Risk Mitigation
Static stop-losses react to price after the fact. Atom Finance instead tracks volatility clusters as they form and reduces position sizing ahead of a confirmed regime shift, rather than waiting for a fixed threshold to be breached.
This does not remove market risk. It changes when the system responds to it, narrowing the gap between detection and action.
Adjusts position only after a price threshold is breached.
Adjusts exposure as volatility clustering is forming.
Applications
Latency-sensitive execution paths prioritise order routing speed, suited to positions held for seconds rather than full sessions.
Multi-vector analysis weighs macro data and sector rotation to propose rebalancing windows aligned with quarterly reporting cycles.
Cross-venue price discrepancies across LSE and connected liquidity pools are flagged within milliseconds of divergence.
Methodology
The core system runs an ensemble of gradient-boosted and sequence-based models, each specialised for a single data category rather than combined into one opaque model. Outputs are merged into a single confidence score before any threshold is evaluated.
Three primary categories feed the model: market sentiment drawn from public commentary and news wires, order flow data from connected venues, and macroeconomic releases covering UK and US indicators. No dataset is exclusive to a single client, and none includes non-public information.
Atom Finance does not hold client funds and does not provide personalised financial advice. Every automated action is bounded by parameters you set — position size limits, maximum drawdown, and asset restrictions — and can be paused at any time. Final decision authority remains with the account holder throughout.