流動(dòng)性信息與資產(chǎn)收益分析-資料下載頁(yè)
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【正文】 _r lagr}。close amp。dataset。sort amp。dataset out=data_set by trd。use data_set。read all into u1 var{trd}。n=nrow(x)。x1=j(n,1,1)。x=x1||x。xx=x1||xx。/*initiziation begin*/yy=j(n,4,0)。/*du=j(n,4,0)。*/s=j(n,n,0)。h=。a1=j(n,1,0)。a2=j(n,1,0)。e=j(n,2,0)。I=i(n)。 /*w=j(n,n,0)。*//*initiziation end*//*DEFINE KERNEL FUNCTION*/start kde(o)。kernel=*(1o2)(abs(o=1))。return(kernel)。finish。/*define the estimation bhat*/start sm。do j=1 to n。yy[j,]=x[j,]||j(1,2,0)。k0=(uu1[j,])/h。w0=(1/h)kde(k0)。w=diag(w0)。hx=(uu1[j,])/h。hhx=hxx。du=x||hhx。l=yy[j,]*inv(t(du)*w*du)*t(du)*w。 /*estimate matric S*/s[j,]=l[1,]。 end。finish。run sm。bhat=inv(t(z)*t(Is)*(Is)*z)*t(z)*t(Is)*(Is)*y。/*define the varyingcoefficient named e*/start semi。do i=1 to n。k1=(uu1[i,])/h。w0=(1/h)exp(k1)。w=diag(w0)。hx=(uu1[i,])/h。hhx=hxx。du=x||hhx。ahat=inv(t(du)*w*du)*t(du)*w*(yz*bhat)。a1[i,]=ahat[1,]。a2[i,]=ahat[2,]。e[i,]=a1[i,]||a2[i,]。varname=39。func_liqui39。||39。b_lagr239。end。finish。run semi。create bhat from bhat[colname=39。bhat39。]。append from bhat。create b_liquout from e[colname=varname]。append from e。/*Hypothesis testing:Generalized Likelihood Ratio Test(PLR)*/start Plr。/*parametric part*/m=s*(yz*bhat)。raw_rss1=ymz*bhat。rss1=raw_rss1[,]。A=1。bhat0=bhatinv(t((Is)*z)*(Is)*z)*inv(inv(t((Is)*z)*(Is)*z))*bhat。m0=s*(yz*bhat0)。raw_rss0=ym0z*bhat0。rss0=raw_rss0[,]。PLR=(n/2)log(rss0/rss1)。finish。run Plr。create PLR from plr[colname=39。PLR39。]。append from plr。/*Hypothesis testing:Generalized Likelihood Ratio Test(GLR)*//*Nonparametric part*/start GLR。bhat2=inv(t(xx)*xx)*(t(xx)*y)。raw_rss01=yxx*bhat2。rss01=raw_rss01[,]。GLR=(n/2)log(rss01/rss1)。finish。run glr。create gLR from glr[colname=39。gLR39。]。append from glr。data sort_b_liqui。merge b_liquout amp。dataset。keep func_liqui b_lagr depth1。proc sort。by depth1。run。quit。proc univariate data=b_liquout。run。%let data=新黃浦。proc export data=b_liquoutoutfile=D:\path\非參數(shù)\經(jīng)濟(jì)研究\學(xué)院組織參賽\data_code\amp。data\dbms=csv。run。proc export data=data_setoutfile=D:\path\非參數(shù)\經(jīng)濟(jì)研究\學(xué)院組織參賽\data_code\amp。data\dbms=csv。run。proc export data=depth_finaloutfile=D:\path\非參數(shù)\經(jīng)濟(jì)研究\學(xué)院組織參賽\data_code\amp。data\dbms=csv。run。proc export data=Sort_b_liquioutfile=D:\path\非參數(shù)\經(jīng)濟(jì)研究\學(xué)院組織參賽\data_code\amp。data\ dbms=csv。run。conditional bootstrapdata bootsamp。 do sampnum = 1 to 1000。 /* To create 1000 bootstrap replications */ do i = 1 to nobs。 y = round(ranuni(0) * nobs)。 set a nobs = nobs point = y。 output。 end。 end。 stop。 run。 data a。set a。 r1=log(clo_p)log(lag(clo_p))。 if r1=39。.39。 then r1=0。 sampnum=0。run。data final。 set bootsamp。 by sampnum。 if then r1=0。 else r1=log(open)log(lag(open))。if r1=39。.39。 then r1=0。run。data final2。set a final。run。proc iml。use final2。read all into r var{r1}。read all into x var{sampnum}。n=nrow(r)。sum=rr。sum=x||sum。create aa from sum。append from sum。quit。proc means data=aa noprint nway。class col1。var col2。output out=bb mean=mean。run。data bb。set bb。sum=_FREQ_*mean。run。data c。set bb。if sum then output c。run。/然后重復(fù)上面部分/定向加權(quán)部分codedensity部分：table()rtable$rwtable$wgtw1table$wgt1w2table$wgt2w3table$wgt3w4table$wgt4plot(density(r,weight=w2),xlim=c(,),lty=2,xlab=圖2 交通設(shè)施板塊,main=)lines(density(r))arrows(,10,length=) text(,12,benchmark density) arrows(,14,16,length=) text(,17,liquidityweighted density)影響分析部分：ffunction(x){table()pltable$plt1:length(pl)hn*sd(t)*length(t)^()vltable$vls1function(x,j){exp(*((t[j]x)/hn)^2)}s0for(j in 1:length(t))ss+s1(x,j)w1function(x,j){(exp(*((t[j]x)/hn)^2))*(t[j]x)/hn^2}w0for(j in 1:length(t))ww+w1(x,j)p1function(x,i){(exp(*((t[i]x)/hn)^2))*((t[i]x)/hn^2*sw)*pl[i]}p0for(i in 1:length(t))pp+p1(x,i)v1function(x,i){(exp(*((t[i]x)/hn)^2))*((t[i]x)/hn^2*sw)*vl[i]}v0for(i in 1:length(t))vv+v1(x,i)weight=p/vweight}
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