high R square issue-schweser V1 third afternoon Q24

Schweser practice V1 third afternoon, p185 Q24, provider A got six independent variable,

Provider B got three variable, the answer says regression for provider A has high R square and provider B got low R square, why more variable can have higher value, anyone can clarify?


return based analysis is a multi variable regression.

regressed return of portfolio to factor exposures such as size of capitalization, value style, growth sttyle.

the more variables the the better the explanation power of the regression, therefore the higher the R squared, generally speaking. (if you randomly include many variables, adjusted R squared will actually decrease).

R2 - higher means the high style fit ( the returns of the protfolio are more explained by the regression model)

(1 - Style fit) is attributed to manager’s skill.

If the variables are less or non exhaustive, the R2 will be low…(1-R2 ) would be high…so we may wrongly consider that manager is generating excess return…