Advanced Temporal Modeling in Foreign Exchange Markets
A Technical Analysis of Long Short-Term Memory Architectures and the Aurum Implementation
Dual neural network architecture trained on 59,000+ hours of gold price data.
Traditional gold trading relies on lagging indicators and rigid rules. This AI trading bot takes a different approach—deploying an LSTM-CNN hybrid model that captures temporal dependencies across 30 bars while extracting local patterns from the feature matrix.
The model processes 51 distinct features every hour: price dynamics, volatility regimes, market microstructure, regime detection, and cross-asset correlations. Only high-confidence setups pass the internal threshold.
Real execution. Real capital. Verifiable results.





Trained using gap validation methodology on data spanning 2015-2026. This AI trading bot learns patterns invisible to traditional technical analysis while maintaining strict risk controls through ATR-based position management.
0.7845
R-Squared
Price prediction accuracy on test data
1.58
Profit Factor
Backtest results 2018-2025 H1
8.35%
Max Drawdown
Controlled risk through dynamic sizing
+14.0%
3M ROI
2.27
Sharpe Ratio
7.3%
Max Drawdown
Investment
$599
Lifetime License
Account Protection
Instant Deployment
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