0001 cd('..');
0002 boot;
0003 cd(cgmm_config.directories.plot);
0004
0005 load(cgmm_config.estimates.pcsv);
0006
0007 n = 2
0008 p = 2
0009
0010
0011 mu = mu_cgmm
0012 A = A_cgmm
0013 lambda_0 = lambda_0_cgmm
0014 kappa = kappa_cgmm
0015 theta = theta_cgmm
0016 sigma = sigma_cgmm
0017 rho = rho_cgmm
0018
0019 S_0 = repmat(100,1,n);
0020 y_0 = log(S_0);
0021 kappa = 2*kappa
0022 disp('Feller condition');
0023 2*kappa.*theta >= sigma.^2
0024
0025 t = 0:1/250:1;
0026 [y, lambda] = sim_pcsv(y_0, mu, A, lambda_0, kappa, theta, sigma, rho, t);
0027
0028 v = zeros(size(lambda,1),2);
0029 c = zeros(size(lambda,1),1);
0030 for k=1:length(c)
0031 M = A(:,1:p)*diag(lambda(k,:))*A(:,1:p)';
0032 v(k,:) = [sqrt(M(1,1)) sqrt(M(2,2))];
0033 c(k) = M(2,1) / (sqrt(M(1,1)*M(2,2)));
0034 end
0035
0036
0037 subplot(3,1,1);
0038 plot(exp(y));
0039 title('Stock Price');
0040 subplot(3,1,2);
0041 plot(v);
0042 title('Volatility');
0043 subplot(3,1,3);
0044 plot(c);
0045 title('Correlation');
0046
0047