Hurst指数的Matlab实现.doc

% The Hurst exponent
%
% The first 20 lines of code are a small test driver.
% You can delete or comment out this part when you are done validating the % function to your satisfaction.
%
% Bill Davidson, ******@
% 13 Nov 2005
function []=hurst_exponent() disp('testing Hurst calculation');
n=100; data=rand(1,n);
plot(data);
hurst=estimate_hurst_exponent(data);
[s,err]=sprintf('Hurst exponent = %.2f',hurst);disp(s);
%
% This function does dispersional analysis on a data series, then does a
% Matlab polyfit to a log-log plot to estimate the Hurst exponent of the
% series.
%
% This algorithm is far faster than a full-blown implementation of Hurst's % algorithm. I got the idea from a 2000 PhD dissertation by Hendrik J % Blok, and I make no guarantees whatsoever about the rigor of this approach % or the accuracy of results. Use it at your own risk.
%
% Bill Davidson
% 21 Oct 2003
function [hurst] = estimate_hurst_exponent(data0) % data set
data=data0; % make a local copy
[M,npoints]=size(data0);
yvals=zeros(1,npoints); xvals=zeros(1,npoints);
data2=zeros(1,npoints);
index=0;
binsize=1;
whi