- Symbol
-
XAUUSD
- Timeframe
- M15 (ANY)
Built on my unique feature engineering:
Time series are transformed with Fourier analysis to extract dominant frequencies, tested for stationarity (Dickey-Fuller), and enriched with nonlinear metrics (higher-order moments, entropy characteristics).
This allows the model to operate not on raw quotes but on abstract multidimensional patterns.
To improve robustness and reduce prediction variance, outputs are filtered through a cascade of meta-models (logistic regression, SVM), performing Bayesian regularization of the final signal.
Time series are transformed with Fourier analysis to extract dominant frequencies, tested for stationarity (Dickey-Fuller), and enriched with nonlinear metrics (higher-order moments, entropy characteristics).
This allows the model to operate not on raw quotes but on abstract multidimensional patterns.
To improve robustness and reduce prediction variance, outputs are filtered through a cascade of meta-models (logistic regression, SVM), performing Bayesian regularization of the final signal.
