% Load time series (2847 values of the French stock index: cac40)

CACechel;

% Compute Gauss-pseudo-wavelet transforms for the first 2048 values 
% of the time series (from 1988 to 1996). 

b=cac40(1:2048);
b_cwt=cwt1(b,6,'Gauss');
s=1:2048;

%Display somes transforms

subplot(611);
plot(b,'r');
axis([1 2048 890 2356]);
axis('off');
text(2120,1850,'Cac40');
title('2048 daily values');

subplot(612);
plot(b_cwt(:,36),'b');
axis([1 2048 970 2289]);
axis('off');
text(2120,1500,'Wtf 36');

subplot(613);
plot(b_cwt(:,24),'b');
axis([1 2048 1115 2225]);
axis('off');
text(2120,1600,'Wtf 24');

subplot(614);
plot(b_cwt(:,18),'b');
axis([1 2048 1251 2169]);
axis('off');
text(2120,1600,'Wtf 18');

subplot(615);
plot(b_cwt(:,12),'b');
axis([1 2048 1428 2081]);
axis('off');
text(2120,1600,'Wtf 12');

subplot(616);
plot(b_cwt(:,1),'b');
axis([1 2048 1728 1883]);
axis('off');
text(2120,1750,'Wtf 1');
%xlabel('5 transforms at octaves ')

% Revised on 3 sept 2010

% "Complex and Chaotic Nonlinear Dynamics. 
% Advances in Economics and Finance, 
% Mathematics and Statistics" 
% T.Vialar, Springer 2009.
% Copyright(c).