08 - Chapter8 IndexModels Pages246 256 269 Observation 1 2...

Info iconThis preview shows pages 1–4. Sign up to view the full content.

View Full Document Right Arrow Icon
7/16/2011 1 Chapter 8 Index Models Pages 246 – 256 + 269 Observation 1 2 3 4 5 6 Return on M .04 .06 .08 .10 .12 .14 Return on i .05 0 .10 .20 .15 .22 24 i r 24 i r 10 12 14 16 18 20 22 10 12 14 16 18 20 22 0 2 4 6 8 0 2 4 6 8 10 12 14 16 M r 0 2 4 6 8 0 2 4 6 8 10 12 14 16 M r
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
7/16/2011 2 Consider the following (OLS) partitioning of a stock’s return: Index Models rs a r s s   Where: recall from our discussion in Chapter 7 that covariance is connected to regression slope       ii i M i    2 , 0 ,0 iM i M i Cov r r E Cov r The regression line equation will be: 0.06 2 rr  Observation 1 2 3 4 5 6 Mean Variance Return on M .04 .06 .08 .10 .12 .14 .09 .0070/5 = .0014 Return on i .05 0 .10 .20 .15 .22 .12 Regression Line .02 .06 .10 .14 .18 .22 .12 Residual .03 -.06 0 .06 -.03 0 0 i r 12 14 16 18 20 22 24 0.06 2    2 , 2 M Cov r r 0.06 M  M r 0 2 4 6 8 10 024681 0 1 21 4 1 6
Background image of page 2
7/16/2011 3 Applying the expectation operator: Now remember our equation for variance: Index Models     ii i M E ra E r        2 2 ps rs Er
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 4
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 02/02/2012 for the course ECON 442 taught by Professor Grahamlemke during the Spring '11 term at Binghamton.

Page1 / 7

08 - Chapter8 IndexModels Pages246 256 269 Observation 1 2...

This preview shows document pages 1 - 4. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online