Long Memory and ARCH: Time Series

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Related lectures (31)

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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.

Linear Regression Basics

Covers the basics of linear regression, instrumental variables, heteroskedasticity, autocorrelation, and Maximum Likelihood Estimation.

Univariate time series: Analysis & Modeling

Covers the analysis and modeling of univariate time series, focusing on stationarity, ARMA processes, and forecasting.

Count Data Models & Univariate Time Series Analysis

Covers count data models and Poisson regression, then transitions to univariate time series analysis for forecasting economic variables.

Integrated and Seasonal Processes: Time Series

Explores parametric estimation, integrated processes, seasonal modeling, and ARIMA model building in time series analysis.

Vector Autoregression (VAR): Sampling Properties and Examples

Covers Vector Autoregression (VAR) in time series analysis, including sampling properties and examples of VAR processes.

Parametric Signal Models: Matlab Practice

Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.

Univariate Time Series Analysis

Explores univariate time series analysis, covering stationarity, ARMA processes, model selection, and unit root tests.

Time Series: Common Models

Covers common time series models, trend removal, and seasonality adjustment techniques.

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.