求R/S中hurst指数的计算程序
各位高手，小妹最近要做R/S分析，需要求解hurst指数，望各位高手能给一个直接运行的程序ps:小妹不懂matlab
[ 本帖最后由 咕噜噜 于 2007-6-14 19:00 编辑 ] http://forum.vibunion.com/forum/viewthread.php?tid=32137
回复 #2 gghhjj 的帖子
这个程序如何输入数据，运行这个.m文件后出现
??? Error using ==> RSana123
You should provide a time series.
还有就是输出的logRS is the log(R/S)应该不是最后的hurst指数吧
附程序：
RS分形算法matlab代码实现,既利用RS方法计算时间序列的分形hurst指数
[ - ]CODE:
function =RSana(x,n,method,q)
%Syntax: =RSana(x,n,method,q)
%____________________________________________
%
% Performs R/S analysis on a time series.
%
% logRS is the log(R/S).
% logERS is the Expectation of log(R/S).
% V is the V statistic.
% x is the time series.
% n is the vector with the sub-periods.
% method can take one of the following values
%'Hurst' for the Hurst-Mandelbrot variation.
%'Lo' for the Lo variation.
%'MW' for the Moody-Wu variation.
%'Parzen' for the Parzen variation.
% q can be either
%a (non-negative) integer.
%'auto' for the Lo's suggested value.
%
%
% References:
%
% Peters E (1991): Chaos and Order in the Capital Markets. Willey
%
% Peters E (1996): Fractal Market Analysis. Wiley
%
% Lo A (1991): Long term memory in stock market prices. Econometrica
% 59: 1279-1313
%
% Moody J, Wu L (1996): Improved estimates for Rescaled Range and Hurst
% exponents. Neural Networks in Financial Engineering, eds. Refenes A-P
% Abu-Mustafa Y, Moody J, Weigend A: 537-553, Word Scientific
%
% Hauser M (1997): Semiparametric and nonparametric testing for long
% memory: A Monte Carlo study. Empirical Economics 22: 247-271
%
%
% Alexandros Leontitsis
% Department of Education
% University of Ioannina
% 45110 - Dourouti
% Ioannina
% Greece
%
% University e-mail: me00743@cc.uoi.gr
% Lifetime e-mail: leoaleq@yahoo.com
% Homepage: http://www.geocities.com/CapeCanaveral/Lab/1421
%
% 1 Jan 2004.
if nargin<1 | isempty(x)==1
error('You should provide a time series.');
else
% x must be a vector
if min(size(x))>1
error('Invalid time series.');
end
x=x(:);
% N is the time series length
N=length(x);
end
if nargin<2 | isempty(n)==1
n=1;
else
% n must be either a scalar or a vector
if min(size(n))>1
error('n must be either a scalar or a vector.');
end
% n must be integer
if n-round(n)~=0
error('n must be integer.');
end
% n must be positive
if n<=0
error('n must be positive.');
end
end
if nargin<4 | isempty(q)==1
q=0;
else
if q=='auto'
t=autocorr(x,1);
t=t(2);
q=((3*N/2)^(1/3))*(2*t/(1-t^2))^(2/3);
else
% q must be a scalar
if sum(size(q))>2
error('q must be scalar.');
end
% q must be integer
if q-round(q)~=0
error('q must be integer.');
end
% q must be positive
if q<0
error('q must be positive.');
end
end
end
for i=1:length(n)
% Calculate the sub-periods
a=floor(N/n(i));
% Make the sub-periods matrix
X=reshape(x(1:a*n(i)),n(i),a);
% Estimate the mean of each sub-period
ave=mean(X);
% Remove the mean from each sub-period
cumdev=X-ones(n(i),1)*ave;
% Estimate the cumulative deviation from the mean
cumdev=cumsum(cumdev);
% Estimate the standard deviation
switch method
case 'Hurst'
% Hurst-Mandelbrot variation
stdev=std(X);
case 'Lo'
% Lo variation
for j=1:a
sq=0;
for k=0:q
v(k+1)=sum(X(k+1:n(i),j)'*X(1:n(i)-k,j))/(n(i)-1);
if k>0
sq=sq+(1-k/(q+1))*v(k+1);
end
end
stdev(j)=sqrt(v(1)+2*sq);
end
case 'MW'
% Moody-Wu variation
for j=1:a
sq1=0;
sq2=0;
for k=0:q
v(k+1)=sum(X(k+1:n(i),j)'*X(1:n(i)-k,j))/(n(i)-1);
if k>0
sq1=sq1+(1-k/(q+1))*(n(i)-k)/n(i)/n(i);
sq2=sq2+(1-k/(q+1))*v(k+1);
end
end
stdev(j)=sqrt((1+2*sq1)*v(1)+2*sq2);
end
case 'Parzen'
% Parzen variation
if mod(q,2)~=0
error('For the "Parzen" variation q must be dived by 2.');
end
for j=1:a
sq1=0;
sq2=0;
for k=0:q
v(k+1)=sum(X(k+1:n(i),j)'*X(1:n(i)-k,j))/(n(i)-1);
if k>0 & k<=q/2
sq1=sq1+(1-6*(k/q)^2+6*(k/q)^3)*v(k+1);
elseif k>0 & k>q/2
sq2=sq2+(1-(k/q)^3)*v(k+1);
end
end
stdev(j)=sqrt(v(1)+2*sq1+2*sq2);
end
otherwise
error('You should provide another value for "method".');
end
% Estiamte the rescaled range
rs=(max(cumdev)-min(cumdev))./stdev;
clear stdev
% Take the logarithm of the mean R/S
logRS(i,1)=log10(mean(rs));
if nargout>1
% Initial calculations fro the log(E(R/S))
j=1:n(i)-1;
s=sqrt((n(i)-j)./j);
s=sum(s);
% The estimation of log(E(R/S))
logERS(i,1)=log10(s/sqrt(n(i)*pi/2));
% Other estimations of log(E(R/S))
%logERS(i,1)=log10((n(i)-0.5)/n(i)*s/sqrt(n(i)*pi/2));
%logERS(i,1)=log10(sqrt(n(i)*pi/2));
end
if nargout>2
% Estimate V
V(i,1)=mean(rs)/sqrt(n(i));
end
end 你没输入变量x,n,method,q，怎么运行？
真晕，居然会犯这样的错误
看看matlab的function该怎么用吧，别人帮不了你 原帖由 lavender25 于 2007-5-29 17:49 发表 http://www.chinavib.com/forum/images/common/back.gif
各位高手，小妹最近要做R/S分析，需要求解hurst指数，望各位高手能给一个直接运行的程序
ps:小妹不懂matlab
看看基础的书
回复 #4 gghhjj 的帖子
请问method和q应该输入什么值？% method can take one of the following values
%'Hurst' for the Hurst-Mandelbrot variation.
%'Lo' for the Lo variation.
%'MW' for the Moody-Wu variation.
%'Parzen' for the Parzen variation.
% q can be either
%a (non-negative) integer.
%'auto' for the Lo's suggested value. 原帖由 无水1324 于 2007-5-31 08:34 发表 http://www.chinavib.com/forum/images/common/back.gif
看看基础的书
回复 #7 无水1324 的帖子
时间紧迫，来不及重新学matlab,望高手指点迷津 在调用的时候写为：q= ；x= ； n= ；method= ；
=RSana(x,n,method,q)
就可以了
% q
回复 #9 无水1324 的帖子
谢谢！已经计算出来了但是最后的ans是hurst指数吗？ 最后的ans应该有三个
回复 #11 无水1324 的帖子
好奇怪,只有一个值啊 只有一个，那就是你需要的了 结果是什么要看你怎么调用RSana了把调用部分贴出来看看
回复 #14 gghhjj 的帖子
>> x=x =
Columns 1 through 9
0.2100 0.3250 0.2510 0.2550 0.2350 0.2640 0.2410 0.2180 0.2520
Columns 10 through 18
0.2870 0.2980 0.2820 0.3260 0.3090 0.3700 0.4920 0.5610 0.6310
Columns 19 through 22
0.4530 0.6850 0.6960 0.6650
>> RSana(x,5,'Hurst',6)
ans =
0.1965
页:
[1]
2