Cipheron Fund analyses market data continuously so you don't have to. Built for remote professionals who want their capital working while they focus elsewhere, it pairs predictive modelling with a stop-loss system designed to limit drawdowns before they compound.
Transparent methodology, published risk parameters, no performance guarantees. Capital is at risk, as with any market-linked strategy.
Freelancers and remote professionals who manage their own capital often find that the market does not respect time zones, deadlines, or client calls.
Cipheron Fund replaces continuous manual oversight with automated data ingestion and predictive analysis. The platform processes real-time inputs around the clock and applies a consistent, rules-based framework, so decisions are not shaped by fatigue or a single bad night's sleep.
At the centre of Cipheron Fund is a dynamic stop-loss mechanism. Rather than relying on a single fixed percentage, the system continuously recalculates an acceptable drawdown threshold based on current volatility, position size, and recent market behaviour.
When conditions move outside that threshold, the system reduces exposure automatically, before losses have a chance to compound. The goal is not to avoid every downturn, which no system can promise, but to keep any single drawdown within a range that preserves capital for the next opportunity.
This is designed to appeal to professionals who are comfortable with measured growth and uncomfortable with open-ended risk.
The process is designed to be explainable at every stage, so you always understand why a recommendation has been made.
Real-time feeds from market, volatility, and liquidity sources are aggregated continuously, giving the system an up-to-date picture rather than a stale snapshot.
Pattern-recognition models assess current conditions against historical behaviour to estimate probable near-term movement and associated risk.
Tailored recommendations, including position sizing and stop-loss placement, are generated and applied according to the parameters you set.
Every model used by Cipheron Fund is backtested against historical data before it is deployed, and performance is reviewed on a rolling basis rather than assumed to remain valid indefinitely. Backtesting results are indicative of past conditions only and are not a projection of future returns.
Strategies are adjusted when live market behaviour diverges meaningfully from the patterns a model was trained on. This keeps the logic grounded in current conditions, rather than locked to assumptions that may no longer hold.
| Parameter | What it controls | How it is determined |
|---|---|---|
| Drawdown threshold | Point at which exposure is automatically reduced | Recalculated continuously based on volatility |
| Position sizing | Proportion of capital allocated to a given position | Scaled to the user's stated risk tolerance |
| Signal confidence | Minimum predictive confidence required to act | Set by model performance during backtesting |
| Rebalancing frequency | How often allocations are reviewed and adjusted | Varies with market conditions and data flow |
Cipheron Fund was built around a simple observation: remote professionals who have accumulated capital rarely have the time, or the inclination, to monitor markets manually. The platform is designed to operate quietly in the background, applying the same disciplined framework whether you're online or not.
The team is based in Belfast and works with a straightforward principle: capital preservation comes first, and growth is pursued within clearly defined risk boundaries, not chased at any cost.
Request access to see the methodology in detail, review current risk parameters, and decide whether a data-led, drawdown-aware approach fits how you work.