my thesis eviews code.4_tables 2,3 figure 6

8/7/2019 My Thesis Eviews Code.4_Tables 2,3 Figure 6

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' *1:ARMA(1,1) ESTIMATION-FADS & TVER PARAMETERS CALCUALATIONS*create {%0}lo-arma11estimation u 1 2000 '986 observations!i=1for !m=1 to 4rowvector(5) fads_c!mrowvector(5) tver_c!mnext

group arma11paramfor !j=1 to 5equation arma11_!j.ls(n) beme{%0}::vs!iv!j c ar(1) ma(1)arma11_!j.makeresids res_arma11!j'____________________________________________ %sensitivity="lo" '<------------ blank, or up, or loscalar sign=0if %sensitivity="up" thensign=1endifif %sensitivity="lo" thensign=-1

endifseries c_original!j{%sensitivity}for !v=1 to 3c_original!j{%sensitivity}(!v)=c(!v)+sign*0.525*@stderrs(!v) '0.525 is mean+-0.5sigmac(!v)=c_original!j{%sensitivity}(!v)scalar c!v_!j=c(!v)nextc_original!j{%sensitivity}(4)=@se^2c_original!j{%sensitivity}(8)=@schwarzfor !v=5 to 7c_original!j{%sensitivity}(!v)=@stderrs(!v-4)next

'____________________________________________ fads_c1(!j)=c(1)/(1-c(2))fads_c2(!j)=c(2)fads_c3(!j)=(1-c(3))^2/(1-c(2))^2*c_original!j{%sensitivity}(4)fads_c4(!j)=(c(3)-c(2)*(1-c(3))^2/(1-c(2))^2)*c_original!j{%sensitivity}(4)tver_c1(!j)=c(1)tver_c2(!j)=c(2)tver_c3(!j)=c(3)*c_original!j{%sensitivity}(4)/c(2)tver_c4(!j)=(1+c(3)^2-c(3)*(1+c(2)^2))*c_original!j{%sensitivity}(4)arma11param.add c_original!j{%sensitivity}next'____________________________________________

for !m=1 to 4matrix(4,5) fadsrowplace(fads,fads_c!m,!m)matrix(4,5) tverrowplace(tver,tver_c!m,!m)next

' *2:MULTIPERIOD RETURN SIMULATIONS AND STATISTICS CALCULATION*for !j=1 to 5fetch beme{%0}::vs!iv!j

matrix(984,1) mats!iv!jmats!iv!j=res_arma11!j

matrix(984,1) matres!iv!jvector(984) vecres!iv!jseries random!j



!r=2000'<---------------r:number of repetitions to construct the sampling distributionfor !t=1 to !rmatres!iv!j=@permute(mats!iv!j)vecres!iv!j=matres!iv!j

smpl @first+1 985

mtos(vecres!iv!j,random!j)smpl @first+2 985series vs!iv!j=c1_!j+c2_!j*vs!iv!j(-1)+random!j+c3_!j*random!j(-1)smpl @allseries r1_vs!iv!j=vs!iv!j ' *no !t index so that they're overwritten*

'MULTIPERIOD RETURNSfor !k=2 to 120smpl @first+1 @first+1series p_vs!iv!j=10 ' *no !t index so that they're overwritten*smpl @first+2 985p_vs!iv!j=p_vs!iv!j(-1)+vs!iv!j

smpl @allseries r!k_vs!iv!j=p_vs!iv!j-p_vs!iv!j(-!k) ' *no !t index so that they're overwritten*'____________________________________________ 'VARIANCE RATIOscalar w1=1/(1*((984-1)-1)*(1-1/(984-1-1)))scalar w!k=1/(!k*((984-!k)-!k)*(1-!k/(984-1-!k)))series ink1i!ij!j=r1_vs!iv!j-1*@mean(vs!iv!j)series ink!ki!ij!j=r!k_vs!iv!j-!k*@mean(r1_vs!iv!j) ' *no !t index so that they're overwritten*series vr11_power!j_!kvr11_power!j_!k(!t)=(w!k*@sumsq(ink!ki!ij!j))/(w1*@sumsq(ink1i!ij!j))

'REGRESSION BETAequation ff!k_!ts!iv!j.ls(n) r!k_vs!iv!j c r!k_vs!iv!j(-!k)!sum=0for !s=1 to 2*!k-1if !s<2*!k-1 then!sum=!sum+!s/(984-!s)else!sum=!sum+(2*!k-!s)/(984-!s)endifnext '!s!sum2=0for !s=1 to !k-1!sum2=!sum2+2*(!k-!s)/(984-!s)next '!sseries ff11_power!j_!kff11_power!j_!k(!t)=c(2)+!sum/(!k+!sum2)delete ff!k_!ts!iv!jnext '!knext '!tfor !k=2 to 120delete w!k ink!ki!ij!j r!k_vs!iv!jnextdelete p_vs!iv!j vs!iv!j ink1i!ij!j r1_vs!iv!j w1next '!j

subroutine typeii(string %s, scalar !a, scalar !b)for !j=1 to 5series error2{%sensitivity}11{%s}!j_!b



series {%s}_null!jmeanseries {%s}11_power!jmeanfor !k=2 to 120fetch beme{%0}::{%s}_null!j_!k!typeii=0for !t=1 to !rif {%s}11_power!j_!k(!t)<@quantile({%s}_null!j_!k,!a) then

!typeii=!typeii+1endifif {%s}11_power!j_!k(!t)>@quantile({%s}_null!j_!k,1-!a) then!typeii=!typeii+1endifnexterror2{%sensitivity}11{%s}!j_!b(!k)=(!r-!typeii)/!r{%s}_null!jmean(!k)=@mean({%s}_null!j_!k){%s}11_power!jmean(!k)=@mean({%s}11_power!j_!k)if %sensitivity="" thenstore beme{%0}::{%s}11_power!j_!kendif

nextstore beme{%0}::error2{%sensitivity}11{%s}!j_!bif %sensitivity="" thenstore beme{%0}::{%s}11_power!jmean beme{%0}::{%s}_null!jmeanendifnext '!jendsubcall typeii("vr", 0.0025, 95)call typeii("ff", 0.0025, 95)call typeii("vr", 0.05, 90)call typeii("ff", 0.05, 90)for !j=1 to 5for !k=2 to 120

delete vr11_power!j_!k ff11_power!j_!k vr_null!j_!k ff_null!j_!knextnext'close {%0}lo-arma11estimation

' *2:POWER GRAPHS*create {%0}lo-arma11powercalculation u 1 120subroutine powergraphs (scalar !b)for !j=1 to 5fetch beme{%0}::error2{%sensitivity}11vr!j_!b beme{%0}::error2{%sensitivity}11ff!j_!b 'THE WHOLE PROGRAM SHOULD BE RUN-THESE OBJECTS ARE COMMON WITH ARMA(2,2)smpl @first+1 @lastgraph gr_!j_ffvr_!b.line error2{%sensitivity}11ff!j_!b error2{%sensitivity}11vr!j_!bgr_!j_ffvr_!b.name(1) regression beta error IIgr_!j_ffvr_!b.name(2) rariance ratio error IIgr_!j_ffvr_!b.legend font(11) -inbox position(1.91, 2.54) columns(1)gr_!j_ffvr_!b.options -colorgr_!j_ffvr_!b.axis(all) font(11)gr_!j_ffvr_!b.scale(left) range(0,1)smpl @allnextgraph gr_{%0}arma11_!b.merge gr_1_ffvr_!b gr_2_ffvr_!b gr_3_ffvr_!b gr_4_ffvr_!bgr_5_ffvr_!bgr_{%0}arma11_!b.align(1,0.3,0.3)

for !j=1 to 5delete error2{%sensitivity}11vr!j_!b error2{%sensitivity}11ff!j_!b gr_!j_ffvr_!bnext



endsub

call powergraphs(95)call powergraphs(90)'close {%0}lo-arma11powercalculation

my thesis eviews code.4_tables 2,3 figure 6

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