www.gusucode.com > econ 案例源码程序 matlab代码 > econ/EstimateGARCHModelParametersWithoutInitialValuesExample.m
%% Estimate GARCH Model Parameters Without Initial Values % Fit a GARCH(1,1) model to simulated data. % Copyright 2015 The MathWorks, Inc. %% % Simulate 500 data points from the GARCH(1,1) model % % $${y_t} = {\varepsilon _t},$$ % % where $\varepsilon_t = \sigma_tz_t$ and % % $$\sigma _t^2 = 0.0001 + 0.5\sigma _{t - 1}^2 + 0.2\varepsilon _{t - 1}^2.$$ % % Use the default Gaussian innovation distribution for $z_{t}$. Mdl = garch('Constant',0.0001,'GARCH',0.5,... 'ARCH',0.2); rng default; % For reproducibility [v,y] = simulate(Mdl,500); %% % The output |v| contains simulated conditional variances. |y| is a column % vector of simulated responses (innovations). %% % Specify a GARCH(1,1) model with unknown coefficients, and fit it to the % series |y|. ToEstMdl = garch(1,1); EstMdl = estimate(ToEstMdl,y) %% % The result is a new |garch| model called |EstMdl|. The parameter estimates % in |EstMdl| resemble the parameter values that generated the simulated data.