Structural Break Diagnostics and Time-Since-Break Features intermediate

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Autoregressive, Moving-Average, and ARIMA Foundations for Feature Engineering Bayesian Inference and MCMC for Time Series Fractional Differencing: Keeping Memory Without Keeping the Unit Root Path Signatures and Log-Signatures for Financial Sequences Regime Models for Feature Engineering: HMMs, Markov Switching, and Distributional Clustering State-Space Models and Kalman Filtering for Feature Engineering Stationarity Tests: ADF, KPSS, and Rolling Stability Signals Uncertainty as a Feature Volatility Models as Feature Extractors: GARCH, EGARCH, and HAR Wavelets for Multi-Scale Diagnostics and Causal Feature Design