Error using barrier. Objective function is undefined at initial point. Fmincon cannot continue.
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Error using barrier. Objective function is undefined at initial point. Fmincon cannot continue.
Anyone can give me an idea how to solve it? Running code as attach. Thank you very much.
fit_S_powerAGARCH_N
%=========================================================================
% Estimating the standard AGARCH-X Models by QMLE
%=========================================================================
function fit_S_powerAGARCH_N( )
clear all
clc
addpath D:\work\Econometrics\econ
%ss = RandStream('mt19937ar','Seed',1);
%RandStream.setGlobalStream(ss);
rand('seed',00);
%data=xlsread('taux1.xlsx');
data=xlsread('empirics.xlsx');
y1=data(:,7);
%n=size(y1)
x1=data(:,8);
x2=data(:,9);
%n=size(x2)
x3=data(:,10);
%nn=size(x3)
delta=1.0;
%r1=100*price2ret(y1); r1=r1-mean(r1);
%r2=100*price2ret(y2);r2=r2-mean(r2);
%print -deps D:\Recherches\Log_PGarch\Gmail\plot9.eps
r=y1;
%options=optimset('MaxFunEvals',500,'Maxiter',500,'Display','iter');
ops = optimset( 'LargeScale','off','Display','off');
start=rand(1,7);%.25*[0.019 0.0450 0.115 0.872 2.943 0.051 0.028];%20.9*
[theta,lf1,~,~,~,hess]=fminunc(@(b) neglog(b,r,x1,x2,x3),start,ops)
a=real(theta)
h(1)=r(1);%2;%*sqrt(var(r));
%mu=mean(abs(r));
nobs=length(r);
for j = 2:nobs
%h(j)=exp(0.5*a(1))*(abs(r(j-1)))^a(2)*h(j-1)^a(3);
h(j) = a(1)+a(2)*(max(r(j-1),0)).^delta+a(3)*(max(-r(j-1),0)).^delta+a(4)*h(j-1)+a(5)*x1(j-1)+a(6)*x2(j-1)+a(7)*x3(j-1);
%h(j) = a(1)+(a(2)+a(3))*abs(r(j-1)).^delta+a(4)*h(j-1)+a(5)*x1(j-1)+a(6)*x2(j-1)+a(7)*x3(j-1);
end
plot(h)
hold on
plot(0.11*r.^2)
%print -deps D:\Recherches\Log_PGarch\Gmail\plot10.eps
%pause
%save('egarch100_d1.mat','theta1')
end
%-------------------------------------------------------------------------
% Likelihood function for a logGARCH(1,1) model
%-------------------------------------------------------------------------
function logt = neglog(b,y,m1,m2,m3)
%b = abs(b);
nobs = length(y);
%yy=yy';
delta=1.0;
v = y;
u1=m1;
u2=m2;
u3=m3;
h = abs(v)+log(2*abs(v)+1)+exp(2.5)*ones(nobs,1);
%h = 4*ones(nobs,1);
for j = 2:nobs
%h(j)=exp(0.5*b(1))*(abs(v(j-1)))^b(2)*h(j-1)^b(3);
h(j) = b(1)+b(2)*(max(v(j-1),0)).^delta+b(3)*(max(-v(j-1),0)).^delta+b(4)*h(j-1)+b(5)*m1(j-1)+b(6)*m2(j-1)+b(7)*m3(j-1);
%h(j) = b(1)+0.5*(b(2)+b(3))*abs(v(j-1)).^delta+b(4)*h(j-1)+b(5)*m1(j-1)+b(6)*m2(j-1)+b(7)*m3(j-1);
end
%logl= - 0.5*log(2*pi) - 0.5*log(h.^2) - 0.5*(v./h).^2;
logl = - 0.5.*log(2.*pi) -(1./delta).*log(h) - 0.5.*(v./(h).^(1./delta)).^2;
logt = -mean(logl);
end
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