<p>正在做一篇以股指为股货做套保，求最佳套保比率的小论文。其中实证部分是，是用Eviews做，由于不懂编程，弄了一天。还是不大明白。</p><p>这是我的程序，其中hss和sssp分别为个股和沪深300的收益率。求教的是，我最后要得到的最佳保值比率，该如何算：</p><p></p><p>smpl @all<br/>series y1 = hss<br/>series y2 = sssp</p><p><br/>sample s0 1 745<br/>sample s1 2 745<br/>smpl s0<br/>equation eq1.arch(m=100,c=1e-5) y1 c<br/>equation eq2.arch(m=100,c=1e-5) y2 c<br/>coef(2) mu<br/> mu(1) = eq1.c(1)<br/> mu(2)= eq2.c(1)<br/> <br/> coef(3) omega<br/> omega(1)=(eq1.c(2))^.5<br/> omega(2)=0<br/> omega(3)=eq2.c(2)^.5<br/> <br/>coef(2) alpha<br/> alpha(1) = (eq1.c(3))^.5<br/> alpha(2) = (eq2.c(3))^.5 </p><p>coef(2) beta <br/> beta(1)= (eq1.c(4))^.5 <br/> beta(2)= (eq2.c(4))^.5</p><p>!mlog2pi = 2*log(2*@acos(-1))</p><p>series cov_y1y2 = @cov(y1-mu(1), y2-mu(2))<br/>series var_y1 = @var(y1)<br/>series var_y2 = @var(y2)</p><p>series sqres1 = (y1-mu(1))^2<br/>series sqres2 = (y2-mu(2))^2<br/>series res1res2 = (y1-mu(1))*(y2-mu(2))</p><p><br/>logl bvgarch<br/>bvgarch.append @logl logl<br/>bvgarch.append sqres1 = (y1-mu(1))^2<br/>bvgarch.append sqres2 = (y2-mu(2))^2<br/>bvgarch.append res1res2 = (y1-mu(1))*(y2-mu(2))</p><p>bvgarch.append var_y1  =  omega(1)^2 + beta(1)^2*var_y1(-1) + alpha(1)^2*sqres1(-1)<br/>bvgarch.append var_y2  = omega(3)^2+omega(2)^2 + beta(2)^2*var_y2(-1) + alpha(2)^2*sqres2(-1)<br/>bvgarch.append cov_y1y2 = omega(1)*omega(2) + beta(2)*beta(1)*cov_y1y2(-1) + alpha(2)*alpha(1)*res1res2(-1)</p><p>bvgarch.append deth = var_y1*var_y2 - cov_y1y2^2</p><p>bvgarch.append invh1 = var_y2/deth<br/>bvgarch.append invh3 = var_y1/deth<br/>bvgarch.append invh2 = -cov_y1y2/deth</p><p>bvgarch.append logl =-0.5*(!mlog2pi + (invh1*sqres1+2*invh2*res1res2+invh3*sqres2) + log(deth))</p><p>smpl s1<br/>bvgarch.ml(showopts, m=100, c=1e-5)</p><p>show bvgarch.output<br/>graph varcov.line var_y1 var_y2 cov_y1y2<br/>show varcov</p><p>scalar lr = -2*( eq1.@logl + eq2.@logl - bvgarch.@logl )<br/>scalar lr_pval = 1 - @cchisq(lr,1)</p><p>请高手指点啊，我在在线等待，实在是万分火急。</p><p>其实根据程序，应该是cov_y1y2/ var_y2<br/><br/>只是同用最小二程法算出来的差别太大了一些，所以我有些不相信?</p><p>可惜没有人讲一下，高手都去哪里了？<br/> </p>

[此贴子已经被作者于2008-6-27 21:11:03编辑过]