XAU/USD, spot gold priced in US dollars per troy ounce, is the most macro-sensitive instrument in the Eaglics model. Gold's daily range is driven by a confluence of US real interest rates, dollar strength, geopolitical risk, and inflationary expectations that no single model architecture handles reliably in isolation.
The Eaglics XAU/USD ensemble applies 14-plus signal inputs, the most of any instrument in coverage. The system cross-conditions on US 10-year real yields, TIPS breakeven rates, DXY positioning, and geopolitical risk scores alongside the standard price-history and volatility regime inputs.
XAU/USD's average daily range of $20 to $40 per troy ounce makes its absolute pip movement comparable to EUR/USD in dollar terms, but its non-linear relationship with macroeconomic variables means the regime classification step is the single most important component of the model for this instrument.
How the Eaglics 5-Model Ensemble Forecasts XAU/USD
The structural drivers of XAU/USD are common knowledge. What is not public is the correct weighting of those drivers against one another on any given morning, and which model architecture is most relevant for the coming session's regime.
The Eaglics ensemble does not apply a fixed formula. All inputs are compiled into an orthogonalized signal library where redundant information is removed before any model processes the data. Regime classification, classifying the prior session's close as low, normal, or elevated volatility, then determines which of the five architectures receives the highest weight in the final high-low band output.
Signal Library Construction
Macro calendar events, cross-asset correlation inputs, realized volatility measures, and inter-session price behavior are compiled into an orthogonalized signal library. Redundant information between inputs is removed before any model touches the data.
Volatility Regime Classification
The Hurst exponent and realized variance metrics classify the prior session's close into one of three states: low, normal, or elevated. This classification is the single most consequential variable in the system, it determines which model architecture is most relevant for the coming session.
Regime-Conditional Model Weighting
LSTM, GRU, Transformer, XGBoost, and Ridge regression outputs are generated independently and then weighted according to each model's historical accuracy within the current regime. Trending models receive higher weight in trending regimes; mean-reversion architectures are upweighted in compressed, low-volatility states.
High and Low Band Generation
The weighted ensemble produces a calibrated high and low band, not a point estimate. The output carries a confidence score reflecting the degree of model agreement, along with the regime tag so subscribers see the market context the system scored the session on.
Pre-Session Delivery
The forecast is delivered to the subscriber dashboard before the London open, when institutional order flow begins positioning for the day's range. Full methodology documentation is available in the Eaglics research framework.