Econometrics Toolbox

State-Space Modeling and Parameter Estimation

Econometrics Toolbox includes functions for creating state-space models and tools for estimating parameters based on these and other model types.

State-Space Modeling

Econometrics Toolbox provides functions for modeling time-invariant or time-varying, linear, Gaussian state-space models. You can create state-space models with known parameter values, perform Monte-Carlo simulations, and generate forecasts from the model. For models with unknown parameter values, you can perform parameter estimation from full data sets or data sets with missing data using the Kalman filter.

Implementing the Diebold Li model, including estimating the parameters of the model with a Kalman filter using the ssm model.
Implementing the Diebold Li model, including estimating the parameters of the model with a Kalman filter using the ssm model.

Parameter Estimation

With Econometrics Toolbox, you can perform parameter estimation (also known as model calibration) of univariate ARMAX/GARCH composite models, multivariate VAR/VARX models, multivariate VEC models, and state-space models.

Interactively developing a GARCH(1,1) model and estimating the model parameters for NASDAQ daily returns in the command window.

Developing a GARCH(1,1) model and estimating the model parameters for NASDAQ daily returns in the command window.

Estimating state-space model parameters using a Kalman filter.
Estimating state-space model parameters using a Kalman filter.
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