Model and analyze financial and economic systems using statistical methods
Time Series Modeling
- Perform modeling tasks, including data preprocessing, data visualization, model identification, and parameter estimations.
- Compare econometric models to ensure the best fit to the data.
- Share results and generate MATLAB code for repeat use.
Supported models include AR, MA, ARMA, ARIMA, SARIMA, and ARIMAX.
Markov Chain Models
- Create and simulate discrete-time Markov chains.
- Determine Markov chain asymptotic behavior.
- Compute state redistributions, hitting probabilities, and expected hitting times.
- Create and simulate time-invariant or time-varying state-space models.
- Estimate model parameters from full data sets or from data sets with missing data using the Kalman filter.
Markov Switching Models
- Analyze multivariate time series data with structural breaks and unobserved latent states.