How it works
Active machine-learning factor models are organized into a directional view for selected currencies and horizons.
- Each point represents an active factor model: horizontal position is effective timeframe and vertical position is expected return impact.
- Point color identifies the currency; positive values sit in the bullish zone and negative values in the bearish zone.
- Currency scores aggregate active factor outputs into Bullish, Bearish or Neutral asset bias.
- Macro Pair Divergence subtracts the quote score from the base score and ranks currencies moving in opposite directions first.
Model Reliability describes historical model support and consistency. It is not a probability that a trade will win.