Examples and How To
- Detect ARCH Effects Using Econometric Modeler App
Interactively assess whether a series has volatility clustering by inspecting correlograms of the squared residuals and by testing for significant ARCH lags.
- Detect ARCH Effects
Test for autocorrelation in the squared residuals, or conduct Engle’s ARCH test.
- Detect Autocorrelation
Estimate the ACF and PACF, or conduct the Ljung-Box Q-test.
- Time Series Regression X: Generalized Least Squares and HAC Estimators
This example shows how to estimate multiple linear regression models of time series data in the presence of heteroscedastic or autocorrelated (nonspherical) innovations.
- Plot a Confidence Band Using HAC Estimates
Plot corrected confidence bands using Newey-West robust standard errors.
- Change the Bandwidth of a HAC Estimator
Change the bandwidth when estimating a HAC coefficient covariance, and compare estimates over varying bandwidths and kernels.
- Alternative ARIMA Model Representations
Convert between ARMAX and regression models with ARMA errors.
- Specify Conditional Mean and Variance Models
Create a composite conditional mean and variance model.
- Select Regression Model with ARIMA Errors
Learn how to select an appropriate regression model with ARIMA errors.
- Nonspherical Models
Learn about innovations that exhibit autocorrelation and heteroscedasticity.