Time Series Analysis: ARIMA and Seasonal Models

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Multivariate Time Series: Cointegration & Forecasting

Explores multivariate time series analysis, cointegration, forecasting with ARMA models, and practical applications in interest rates analysis.

Demand Forecasting: Methods and Models

Explores demand forecasting methods, time series analysis, trend forecasting, and the application of the Holt-Winter model.

Vector Autoregression: Modeling Vector-Valued Time Series

Explores Vector Autoregression for modeling vector-valued time series, covering stability, reverse characteristic polynomials, Yule-Walker equations, and autocorrelations.

Time Series: Linear Filtering and Spectral Estimation

Explores linear filtering, spectral estimation, and second-order stationarity in time series analysis.

Time Series

Explores Time Series, covering model specification, diagnostics, and forecasting methods.

Vector Autoregression

Explores Vector Autoregression for modeling vector-valued time series, covering stability, Yule-Walker equations, and spectral representation.

Residuals & Forecasting: MATH-342 Time Series

Covers residuals, diagnostics, overfitting, and forecasting methods in time series analysis.

Long Memory and ARCH: Time Series Math 342

Explores long memory in time series and Autoregressive Conditional Heteroskedasticity processes in financial data.

Time Series Forecasting: ARMA Models

Covers ARMA models for time series forecasting, discussing implications, properties of forecast error, challenges with predictions, and covariance models.

Structural Modelling and the Kalman Filter: Time Series

Explores structural modelling in time series and introduces the Kalman filter for prediction and estimation.