econometrics-toolbox介绍

Econometrics Toolbox 2.0 Model and analyze financial and economic systems using statistical methods Econometrics Toolbox provides functions for modeling economic data. You can select and calibrate economic models for simulation and forecasting. Time series capabilities include univariate ARMAX/GARCH composite models with several GARCH variants, multivariate VARMAX models, and cointegration analysis. The toolbox provides Monte Carlo methods for simulating systems of linear and nonlinear stochastic differential equations and a variety of diagnostics for model selection, including hypothesis, unit root, and stationarity tests. Key Features Univariate ARMAX/GARCH composite models, including EGARCH, GJR, and other variants Multivariate simulation and forecasting of VAR, VEC, and cointegrated models Monte Carlo simulation of stochastic differential equations (SDEs), including Brownian motion, CEV, CIR, Hull-White, Vasicek, Heston stochastic volatility, and user-defined SDEs Tests for unit root (Dickey-Fuller, Phillips-Perron) and stationarity (Leybourne-McCabe, KPSS) Statistical tests, including likelihood ratio, LM, Wald, Engle’s ARCH, and Ljung-Box Q Cointegration tests, including Engle-Granger and Johansen Diagnostics and utilities, including AIC/BIC model selection and partial-, auto-, and cross-correlations Hodrick-Prescott filter for business-cycle analysis

Plot of forecasts from a multivariate VARMAX model, produced by the vgxplot function.

Time-Series Modeling Econometrics Toolbox facilitates the multistep process of identifying and testing univariate and multivariate time-series models for financial and econometric data. The toolbox supports the full model development and analysis workflow: Data analysis and preprocessing Model identification Parameter estimation

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