- 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.
View attachment 93
View attachment 94
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.
View attachment 93
View attachment 94
