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1) a) > muhat.vals VBLTX FMAGX SBUX 0.0058961 -0.0008077 0.0004890 > sigma2hat.vals VBLTX FMAGX SBUX 0.0008655 0.0045108 0.0107429 > sigmahat.vals VBLTX FMAGX SBUX 0.02942 0.06716 0.10365 > cov.mat VBLTX FMAGX SBUX VBLTX 0.0008655 0.0003675 -0.0004141 FMAGX 0.0003675 0.0045108 0.0042671 SBUX -0.0004141 0.0042671 0.0107429 CORR MATRIX VBLTX FMAGX SBUX VBLTX 1.0000 0.1860 -0.1358 FMAGX 0.1860 1.0000 0.6130 SBUX -0.1358 0.6130 1.0000 b) VBLTX FMAGX SBUX muhat.vals 0.005896 -0.0008077 0.000489 se.muhat 0.003798 0.0086707 0.013381 SE defect for the estimates ar large sexual intercourse to muhat. SBUX, for example, pattern computer error is really big, way big than muhat. Magnitudes of standard error tell that they are poor estimates for genuine value. VBLTX FMAGX SBUX sigma2hat.vals 0.0008655 0.0045108 0.010743 se.sigma2hat 0.0001580 0.0008236 0.001961 Standard error for sigma2 seem small compare to the sigma2hat. In fact, they are really small. This tells us that estimates are quite precise. VBLTX FMAGX SBUX sigmahat.vals 0.029420 0.067163 0.103648 se.sigmahat 0.002686 0.006131 0.

009462 uniform explanation as that for sigma2. Standard errors are small comparative to sigmahat.vals. Look at SBUX, SE is 0.009 when sigmahat is 0.103. This tells that estimates are quite precise. 0.000367468108649433 -0.0004140782601! 06599 rhohat.vals 0.1860 -0.1358 se.rhohat 0.1246 0.1267 0.00426709684264575 rhohat.vals 0.61298 se.rhohat 0.08059 rhohat for VBLTX and FMAGX and for FMAGX and SBUX are moderately well(p) estimates, though one could argue against it. Rhohat for SBUX and VBLTX may snuff it judgement that it is not a good estimate,...If you want to propose a full essay, order it on our website: OrderCustomPaper.com

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