Worthamence Platform
Artificial intelligence to support your financial decisions
Analyse more than 500 trading pairs in real time with Worthamence, a decision-support platform built to bring structure to complex markets and help identify opportunities.
Explore the methodologyReal-time predictive analysis
A clear summary of the volatility indicators and confidence scores produced by our proprietary models.
| Asset | Confidence score | AI trend | Calculated risk |
|---|---|---|---|
| BTC / USDT | 78,4 | +2,1 % | Moderate |
| ETH / USDT | 71,2 | +1,4 % | Moderate |
| SOL / USDT | 54,9 | +0,2 % | High |
| XRP / USDT | 62,7 | -0,8 % | Moderate |
| ADA / USDT | 48,3 | -1,6 % | High |
Figures are provided for illustrative purposes only to show the analysis engine’s output format. Actual scores may vary depending on market conditions at the time of calculation.
How the model organises the analysis
In three clear steps, raw data is converted into a practical recommendation, with the calculations handled automatically from start to finish.
Large-scale aggregation
Simultaneous data collection across 500+ trading pairs, covering price, volume and liquidity feeds.
Algorithmic filtering
Filtering out market noise and identifying weak signals in the collected time-series data.
Decision support
Personalised recommendations tailored to your risk profile and portfolio constraints.
Risk management built into the algorithm
Rather than relying on speculation, Worthamence applies advanced correlation models to assess your portfolio’s exposure to market-wide volatility before making any recommendation.
- Cross-correlation analysis across assets and asset classes
- Early identification of trend reversals
- Stress scenario modelling using historical data
A structured approach for considered investors
Worthamence develops predictive models designed to help reduce uncertainty, not guarantee returns. Its aim is to give a clear view of the trading pairs being monitored, with confidence scores updated continuously.
The platform is operated from outside Australia and is designed for investors who want to incorporate quantitative analysis into their decision-making while retaining their own judgement.
Questions about our methodology
Clear explanations of how the analysis engine works, rather than promises about performance.
How does the AI respond to unexpected market movements?
Our models adjust automatically, using liquidity data in milliseconds to reassess risk exposure.
Which data feeds are analysed?
We analyse order books, historical trading volumes and global macroeconomic indicators.