| 所在主题: | |
| 文件名: mmm.xls | |
| 资料下载链接地址: https://bbs.pinggu.org/a-1759715.html | |
| 附件大小: | |
|
大家好,目前我需要用matlab做garch-bekk模型,求两组金融高频数据的方差和协方差,以求套保比率。
现在,我已经找到了bekk的工具包,里面的程序如下,是一个m文件,我想知道,我怎样将我的两组数据带入,调用m文件,run出结果。 因为之前都没用过这个软件,想知道详细步骤,万分感谢,比较急,论坛币不多,希望能得到回复~或者用其它软件怎么做,有人知道么? function [ll,lls,Ht] = bekk_likelihood(parameters,data,dataAsym,p,o,q,backCast,backCastAsym,type) % Likelihood for BEKK(p,q) multivarate volatility model estimation % % USAGE: %[LL,LLS,HT] = bekk_likelihood(PARAMETERS,DATA,P,O,Q,BACKCAST,TYPE) % % INPUTS: % PARAMETERS - Vector of parameters required to compute the (negative) of the log-likelihood % DATA - K by K by T array of data % DATAASYM - K by K by T array of asymmetric data % P - Positive, scalar integer representing the number of symmetric innovations % O - Non-negative, scalar integer representing the number of asymmetric innovations % Q - Non-negative, scalar integer representing the number of conditional covariance lags % BACKCAST - K by K matrix to use for back casting % TYPE - Number indicating type: % 1 - Scalar % 2 - Diagonal % 3 - Full % % OUTPUTS: % LL - The log likelihood evaluated at the PARAMETERS % LLS - A T by 1 vector of log-likelihoods % HT - A [K K T] dimension matrix of conditional covariances % % COMMENTS: % % See also BEKK % Copyright: Kevin Sheppard % kevin.sheppard@economics.ox.ac.uk % Revision: 1 Date: 3/27/2012 % Get the parameters together T = size(data,3); k = size(data,2); [C,A,G,B] = bekk_parameter_transform(parameters,p,o,q,k,type); Ht = zeros(k,k,T); lls = zeros(T,1); logLikConst = k*log(2*pi); for i=1:T Ht(:,:,i) = C; for j=1:p if (i-j)<=0 Ht(:,:,i) = Ht(:,:,i) + A(:,:,j)'*backCast*A(:,:,j); else Ht(:,:,i) = Ht(:,:,i) + A(:,:,j)'*data(:,:,i-j)*A(:,:,j); end end for j=1:o if (i-j)<=0 Ht(:,:,i) = Ht(:,:,i) + G(:,:,j)'*backCastAsym*G(:,:,j); else Ht(:,:,i) = Ht(:,:,i) + G(:,:,j)'*dataAsym(:,:,i-j)*G(:,:,j); end end for j=1:q if (i-j)<=0 Ht(:,:,i) = Ht(:,:,i) + B(:,:,j)'*backCast*B(:,:,j); else Ht(:,:,i) = Ht(:,:,i) + B(:,:,j)'*Ht(:,:,i-j)*B(:,:,j); end end lls(i) = 0.5*(logLikConst + log(det(Ht(:,:,i))) + sum(diag(Ht(:,:,i)^(-1)*data(:,:,i)))); end ll = sum(lls); if isnan(ll) || isinf(ll) || ~isreal(ll) ll = 1e7; end |
|
熟悉论坛请点击新手指南
|
|
| 下载说明 | |
|
1、论坛支持迅雷和网际快车等p2p多线程软件下载,请在上面选择下载通道单击右健下载即可。 2、论坛会定期自动批量更新下载地址,所以请不要浪费时间盗链论坛资源,盗链地址会很快失效。 3、本站为非盈利性质的学术交流网站,鼓励和保护原创作品,拒绝未经版权人许可的上传行为。本站如接到版权人发出的合格侵权通知,将积极的采取必要措施;同时,本站也将在技术手段和能力范围内,履行版权保护的注意义务。 (如有侵权,欢迎举报) |
|
京ICP备16021002号-2 京B2-20170662号
京公网安备 11010802022788号
论坛法律顾问:王进律师
知识产权保护声明
免责及隐私声明