The Model | Regressors in the Mean Equation (ARMAX) | Which convention should I use? | Stationarity and Invertibility | Diagnostic helpers and the "ARMA(1,1) trap" | Why near-cancellation matters | Demo

Introduction | GOGARCH Dynamics | Model Specification and Estimation | Filtering | Conditional Co-moments | Weighted Portfolio Distribution | DCC Dynamics | Filtering | Copula with DCC Dynamics | Conditional Mean Dynamics | Method 1: Conditional Mean Re-centering | Method 2: Innovation Distribution Injection | Method Comparison | First Stage ARMA-GARCH

Introduction | Covariance Decomposition Models (dcc and cgarch) | Constant Correlation | Dynamic Conditional Correlation | Estimation | Standard Errors | Distributions | Multivariate Student Distribution (mvt) | Copula Distribution (cgarch) | Generalized Dynamics | Forecasting and Simulation | Weighted Distribution | News Impact Surface | Critique | Generalized Orthogonal GARCH Model (gogarch) | Estimation | Co-Moments | Weighted Distribution | Factor News Impact Surface | Methods and Classes | Appendix | Correlation and Kendall's $\tau$ | Notes on Selected Methods | References

Introduction | Advanced Retail Sales | Model Selection | Prediction and Ensembling | Conclusion

Estimation | Simulation and Prediction | Conclusion

Introduction | Usage

Introduction | Problem Statement | Inequalities | Slack Variable Embedding | Optimization via Augmented Lagrangian | No Stationarity-Based KKT Step | Why Higher Tolerances Are Not Preferred | C++ Version | Multi-Start Solver | Test Suite | Differences with full Active-Set/SQP solvers | Conclusion | References

Introduction | Data Investigation | Naive Approach (Irregular Time Base) | Correct Approach (Regular Time Base with Missing Values) | Re-estimating with Regularized Calendar Time | Evaluation | Conclusion

Introduction | Demonstration | Estimation | Rolling Forecasts via Online Filtering | Filtering vs Forecasting at Horizon ( h = 1 ) | Visual Comparison | Conclusion

Introduction | SPY Closing Price | Model Summary | Visuals | Conclusion | References

Introduction | Anomaly Generation and Detection | Data Transformations | Metrics | Simulation | Calendar/Time Utilities | Miscellaneous | References

Background | Demo | Conclusion | References

Introduction | Goodness of Fit Tests | GMM Orthogonality | Non Parametric Density Test | Parameter Constancy | Sign Bias | Forecast Evaluation Tests | Density Forecast | Directional Accuracy | Forecast Unbiasedness | Expected Shortfall | The Unconditional Test | The Conditional Test | Example | Value at Risk: Coverage and Duration | Proportion of Failures (UC) | Independence of Failures (CCI) | Conditional Coverage (CC) | Duration between Failures (D) | References

Introduction | Implemented Distributions | Normal Distribution ($\mu$, $\sigma$) | Student's t Distribution ($\mu$, $\sigma$, $\nu$) | Generalized Error Distribution ($\mu$, $\sigma$, $\nu$) | Skewed Distributions by Inverse Scale Factors | Johnson's SU Distribution ($\mu$, $\sigma$, $\xi$, $\nu$) | The Generalized Hyperbolic Distribution ($\mu$, $\sigma$, $\xi$, $\nu$, $\lambda$) | The Generalized Hyperbolic Skew Student Distribution ($\mu$, $\sigma$, $\xi$, $\nu$) | References

Introduction | Model Specification | Fitting | Filtering | Forecasting and the GARCH Bootstrap | Simulation | Rolling Estimation | Simulated Parameter Distribution and RMSE | The ARFIMAX Model with constant variance | Mispecification and Other Tests | FAQs and Guidelines

Introduction | Implementation | BesselK (bessel_k) | Description | Inputs | Output | Example | BesselI (bessel_i) | BesselJ (bessel_j) | BesselY (bessel_y) | BesselH (bessel_h) | AiryA (airy_a) | AiryB (airy_b) | An Example with RcppArmadillo Conversion | Timing Tests

Introduction | Uncertainty and Scenario Based Allocation | Risk and Deviation Measures | General Problem Formulation | Optimal Portfolios | Smooth Approximations to Non-Continuous Functions | Custom Constraints | FAQ's and Misc Notes

Introduction | Multivariate GARCH Models | Miscellaneous | Appendices