How TradeClaw Scores Trading Signals: A Full Walkthrough
Most AI trading signal tools are black boxes — you get a "BUY" label and a confidence percentage, with no explanation of how it was computed. TradeClaw is different: the entire scoring engine is open source, and this post walks through exactly how every signal gets generated.
The Big Picture: A Points System
TradeClaw uses a simple, deterministic points system. Every signal is scored by running 5 technical indicators and awarding points based on what each indicator shows. The total is normalised to a confidence percentage.
| Indicator | Max Points | What It Measures |
|---|---|---|
| RSI (14) | 20 | Overbought / oversold momentum |
| MACD (12/26/9) | 25 | Trend direction & momentum change |
| EMA (20/50/200) | 20 | Price vs moving average alignment |
| Stochastic (14/3/3) | 15 | K/D position and crossover |
| Bollinger Bands (20, 2σ) | 10 | Price at extremes of volatility range |
| Total | 90 | → Scaled to 48–95% confidence |
Step 1: Compute Both Directions
For every asset and timeframe, TradeClaw computes a BUY score and a SELL score independently. Whichever score is higher and exceeds the minimum threshold (58% confidence) becomes the signal. Signals between 55–57% appear on the watchlist only. If neither exceeds 55%, no signal is emitted — "no opinion" is a valid output.
Step 2: Quality Gates (Filters)
Before a signal is emitted, it must pass 4 quality checks:
- ATR check: Average True Range must be > 0.3% of price. Signals in flat/dead markets are filtered out.
- Bollinger bandwidth: Must be > 1%. Consolidating markets produce false signals.
- EMA slope: At least one EMA must have non-zero slope. Zero-slope = no trend = noise.
- Stop distance: SL must be > 0.5% from entry. Tight stops get triggered by normal noise and produce misleading results.
Step 3: Confidence Normalisation
Raw score (0–90) → confidence (50–98%). The formula:
confidence = min(95, max(48, round(42 + rawScore × 0.62)))
Why cap at 95%? No deterministic indicator combination can justify 100% certainty. The floor of 48% prevents meaninglessly low scores from cluttering the output.
Is It Actually Calibrated?
Good calibration means: signals at 80% confidence should win ~80% of the time. We track this on the calibration page using Expected Calibration Error (ECE). The honest answer: with synthetic seed data, calibration is not yet validated. As live signals accumulate, that page will reflect real performance.
Multi-Timeframe Confluence
TradeClaw also generates signals across H1, H4, and D1 timeframes and checks for confluence. When all three timeframes agree, confidence gets a +15% boost. When they disagree, confidence is reduced and the signal is flagged as "conflicted."
Limitations We're Honest About
- All indicators are lagging — they react to price, they don't predict it
- Crypto and forex have different characteristics — RSI(14) behaves differently on 1-hour BTC vs daily EUR/USD
- The scoring weights are manually tuned, not machine-learned from backtested data (yet)
- No fundamental analysis, news, or macro factors are considered
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