* POWER Utility with rolling window cond variance estimator * Stationary Bootstrap of Calhoun (2011), White-style stat i.e. no standard errors * R+P=1024 all 2100 source H:\m1mwm01\Research\Valente\code\fcasterr2.src * ** set simulation constants * com NOBS = 512 * com R = 256 * com P = NOBS-R+1 com burn = 500 com endsmpl = burn + nobs com simreps = 2000 * ** set bootstrap constants * com bsreps = 499 * com blength = 80 * ** set DGP constants * com RRA = 5.0 com rho = 0.5 com volT = 60 com alpha = 0.0 decl symmetric Sigma(2,2) com Sigma(1,1) = 0.00171610471 com Sigma(2,1) = -0.00003830269 com Sigma(2,2) = 0.000063*(1.0-rho**2.0) com eye = %decomp(Sigma) ********** ********** Start do-loop for alphas ********** do count=1,3 com R = 128*count com P = NOBS-R+1 com blength = 160-(count*40) seed 41467 * ** bookkeeping for simulation * set PHIhat 1 simreps = 0.0 set PHIcntr 1 simreps = 0.0 com count90 = 0.0 com count95 = 0.0 com count99 = 0.0 ****** ****** START SIMULATION: j = 1 to simreps ****** infobox(action=define,progress,lower=1,upper=simreps) 'This is taking forever' do j=1,simreps infobox(current=j) * ** simulate model with 2 predictors * clear er dy rf fcer0 fcer1 volER GR0 GR1 GR0cntr GR1cntr bser bsdy bsrf bsfcer0 bsfcer1 bsvolER bsGR0 bsGR1 w0 w1 set er 1 endsmpl = 0.0 set dy 1 endsmpl = 0.03 set rf 1 endsmpl = 0.0036 com dd = 2.5 com aa = -0.03*dd + (1.0-0.0591*dd^2.0)^0.5 dec ser[vec] errdraw gset errdraw 2 endsmpl = %ranmvnormal(eye) set dy 2 endsmpl = 0.032*(1.0-rho) + rho*dy{1} + errdraw(t)(2) set er 2 endsmpl = (0.00252 - alpha*0.032) + alpha*dy{1} + errdraw(t)(1)*abs(aa + dd*dy{1}) * ** carry out out-of-sample forecasting on simulated data * equation 1 er # constant equation 2 er # constant dy{1} com temp0 = fcasterr2(er,1,1,burn,burn+R+1,endsmpl,0) com temp1 = fcasterr2(er,2,1,burn,burn+R+1,endsmpl,0) * ** Compute portfolio weights * set fcer0 burn+R+1 endsmpl = 0.0 set fcer1 burn+R+1 endsmpl = 0.0 set volER burn+R+1 endsmpl = 0.00172 + 0.000063*(alpha**2.0) do jj=burn+R+1,endsmpl com fcer0(jj) = temp0(jj,1) com fcer1(jj) = temp1(jj,1) end do jj * ** Compute performance fees * set w0 burn+R+1 endsmpl = -(fcer0-er)/(RRA*volER) + (1.0/(2.0*rra)) set w1 burn+R+1 endsmpl = -(fcer1-er)/(RRA*volER) + (1.0/(2.0*rra)) set GR0 burn+R+1 endsmpl = 1.0 + rf + er*(%if(w0<-1.0,-1.0,0.0) + %if(w0>2.0,2.0,0.0) + %if(w0>-1.0.and.w0<2.0,w0,0.0)) set GR1 burn+R+1 endsmpl = 1.0 + rf + er*(%if(w1<-1.0,-1.0,0.0) + %if(w1>2.0,2.0,0.0) + %if(w1>-1.0.and.w1<2.0,w1,0.0)) nonlin B1 com b1 = 0.0 declare real value find(noprint,method=simplex) root value set phidiff burn+R+1 endsmpl = (GR1 - b1)**(1.0-rra) - (GR0)**(1.0-rra) sstats(mean) burn+R+1 endsmpl phidiff>>value end find com PHIhat(j) = %beta(1) * ** Compute Calhoun (2011) recentering constant * ** no predictability equation linreg(noprint) er burn endsmpl-1 # constant set w0cntr burn+R+1 endsmpl = %beta(1)/(RRA*volER) + (1.0/(2.0*rra)) set GR0cntr burn+R+1 endsmpl = 1.0 + rf + er*(%if(w0cntr<-1.0,-1.0,0.0) + %if(w0cntr>2.0,2.0,0.0) + %if(w0cntr>-1.0.and.w0cntr<2.0,w0cntr,0.0)) ** predictability equation linreg(noprint) er burn endsmpl-1 # constant dy{1} set w1cntr burn+R+1 endsmpl = (%beta(1) + %beta(2)*dy{1})/(RRA*volER) + (1.0/(2.0*rra)) set GR1cntr burn+R+1 endsmpl = 1.0 + rf + er*(%if(w1cntr<-1.0,-1.0,0.0) + %if(w1cntr>2.0,2.0,0.0) + %if(w1cntr>-1.0.and.w1cntr<2.0,w1cntr,0.0)) nonlin B1 com b1 = 0.0 declare real value find(noprint,method=simplex) root value set phidiff burn+R+1 endsmpl = (GR1cntr - b1)**(1.0-rra) - (GR0cntr)**(1.0-rra) sstats(mean) burn+R+1 endsmpl phidiff>>value end find com PHIcntr(j) = %beta(1) *** **** START Bootstrap simulation: bb = 1 to bsreps *** set bsPHIhat 1 bsreps = 0.0 do bb=1,bsreps boot(method=stationary,block=blength) entries burn endsmpl set bser burn endsmpl = er(entries(t)) set bsdy burn endsmpl = dy(entries(t)) set bsvolER burn+R+1 endsmpl = 0.00172 + 0.000063*(alpha**2.0) * ** carry out out-of-sample forecasting on BOOTSTRAPPED data * equation 3 bser # constant equation 4 bser # constant bsdy{1} com bstemp0 = fcasterr2(bser,3,1,burn,burn+R+1,endsmpl,0) com bstemp1 = fcasterr2(bser,4,1,burn,burn+R+1,endsmpl,0) * ** Compute portfolio weights * set bsfcer0 burn+R+1 endsmpl = 0.0 set bsfcer1 burn+R+1 endsmpl = 0.0 do jj=burn+R+1,endsmpl com bsfcer0(jj) = bstemp0(jj,1) com bsfcer1(jj) = bstemp1(jj,1) end do jj * ** Compute performance fees * set bsw0 burn+R+1 endsmpl = -(bsfcer0-bser)/(RRA*bsvolER) + (1.0/(2.0*rra)) set bsw1 burn+R+1 endsmpl = -(bsfcer1-bser)/(RRA*bsvolER) + (1.0/(2.0*rra)) set bsGR0 burn+R+1 endsmpl = 1.0 + rf + bser*(%if(bsw0<-1.0,-1.0,0.0) + %if(bsw0>2.0,2.0,0.0) + %if(bsw0>-1.0.and.bsw0<2.0,bsw0,0.0)) set bsGR1 burn+R+1 endsmpl = 1.0 + rf + bser*(%if(bsw1<-1.0,-1.0,0.0) + %if(bsw1>2.0,2.0,0.0) + %if(bsw1>-1.0.and.bsw1<2.0,bsw1,0.0)) nonlin B1 com b1 = 0.0 declare real value find(noprint,method=simplex) root value set phidiff burn+R+1 endsmpl = (bsGR1 - b1)**(1.0-rra) - (bsGR0)**(1.0-rra) sstats(mean) burn+R+1 endsmpl phidiff>>value end find com bsPHIhat(j) = %beta(1) * *** End of bootstrap do loop * end do bb * *** Bookkeeping: Is TRUE (simulated) PHIhat greater than the delta-percentile of (centered)-BS distribution? * set bsPHIhat_cntr 1 bsreps = bsPHIhat - PHIcntr(j) statistics(noprint,fractiles) bsPHIhat_cntr 1 bsreps com CV90 = %fract90 com CV95 = %fract95 com CV99 = %fract99 com count90 = count90 + %if(PHIhat(j)>CV90,1.0,0.0) com count95 = count95 + %if(PHIhat(j)>CV95,1.0,0.0) com count99 = count99 + %if(PHIhat(j)>CV99,1.0,0.0) * *** End of simulation do loop * end do j infobox(action=remove) * **** Bookkeeping: Report % of Simreps that PHIhat greater than (centered)BS delta-percentile * com size10 = count90/simreps com size5 = count95/simreps com size1 = count99/simreps statistics(noprint,fractiles) PHIhat com mu_PHIhat = %mean com md_Phihat = %median disp 'blength =' blength 'size1 =' size1 'size5 =' size5 'size10 =' size10 'mu_PHIhat =' mu_PHIhat 'md_PHIhat =' md_PHIhat *** ***** end of alpha do-loop *** end do count /* table */