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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 be large relative to muhat. SBUX, for example, bod computer error is real big, way bigger than muhat. Magnitudes of well-worn error tell that they atomic number 18 poor estimates for true value. VBLTX FMAGX SBUX sigma2hat.vals 0.0008655 0.0045108 0.010743 se.sigma2hat 0.0001580 0.0008236 0.001961 metre error for sigma2 seem humble comp argon to the sigma2hat. In fact, they be really small. This tells us that estimates ar quite precise. VBLTX FMAGX SBUX sigmahat.vals 0.029420 0.067163 0.103648 se.sigmahat 0.002686 0.006131 0.

009462 Same translation as that for sigma2. Standard errors are small relative to sigmahat.vals. play at SBUX, SE is 0.009 when sigmahat is 0.103. This tells that estimates are quite precise. 0.000367468108649433 -0.000414078260106599 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 passably well(p) estimates, though one could struggle against it. Rhohat for SBUX and VBLTX may give discernment that it is not a darling estimate,...If you want to get a full essay, order it on our website: Ordercustompaper.com

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