下面贴的是主程序,附件里是主程序里的函数
在运行的时候先要在主程序里输入y_t, x_t。我没有数据,所以也没法debug,可能要调整初始值和温度,但是思路应该是对的
clc;
clear;
% 退火算法估计GARCH(1,1)
% 用退火算法找出使MLE最大的参数组合
c = 0.001;
phi = 0.001;
zeta = 0.001;
a = 0.001;
delta = 0.001;
% GARCH(1,1) model
% y_t = c+phi*x_t+u_t
% u_t = sqrt(h_t)*v_t
% h_t = zeta+delta*h_t-1+a*u_t-1^2
% 设置GARCH model初始值
y_t = [];
x_t = [];
% 输入要回归的时间序列
theta=[c;phi;zeta;a;delta];
y_old = llf_garch1(theta,y_t,x_t);
T = 100;
T_min = 0.01;
r = 0.9;
% 设置初始温度,最终温度,降温速率
while( T > T_min )
theta1=[c+0.001;phi;zeta;a;delta];
y_new1 = llf_garch1(theta1,y_t,x_t);
theta2=[c;phi+0.001;zeta;a;delta];
y_new2 = llf_garch1(theta2,y_t,x_t);
theta3=[c;phi;zeta+0.001;a;delta];
y_new3 = llf_garch1(theta3,y_t,x_t);
theta4=[c;phi;zeta;a+0.001;delta];
y_new4 = llf_garch1(theta4,y_t,x_t);
theta5=[c;phi;zeta;a;delta+0.001];
y_new5 = llf_garch1(theta5,y_t,x_t);
% 向5个维度上各迈一小步
dE = min(y_new1,y_new2,y_new3,y_new4,y_new5)-y_old ;
if ( dE <= 0 )
% 如果新值变小,接受新值
if dE == y_new1-y_old
theta = theta1;
y_old = y_new1;
elseif dE == y_new2-y_old
theta = theta2;
y_old = y_new2;
elseif dE == y_new3-y_old
theta = theta3;
y_old = y_new3;
elseif dE == y_new4-y_old
theta = theta4;
y_old = y_new4;
else
theta = theta5;
y_old = y_new5;
end
elseif exp( -dE/T ) > rand
% 如果新值变大,有一定概率接受新值
if dE == y_new1-y_old
theta = theta1;
y_old = y_new1;
elseif dE == y_new2-y_old
theta = theta2;
y_old = y_new2;
elseif dE == y_new3-y_old
theta = theta3;
y_old = y_new3;
elseif dE == y_new4-y_old
theta = theta4;
y_old = y_new4;
else
theta = theta5;
y_old = y_new5;
end
end
T = r*T;
% 降温
end
display('The GARCH(1,1) conditional MLE parameter estimates are:');
display([theta'])



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