Rafael Garza, CFA, is considering the purchase of ABC stock for a client’s portfolio. His analysis includes calculating the covariance between the returns of ABC stock and the equity market index. Which of the following statements regarding Garza’s analysis is most accurate? A) The actual value of the covariance is not very meaningful because the measurement is very sensitive to the scale of the two variables. B) The covariance of two variables is an easier measure to interpret than the correlation coefficient. C) A covariance of +1 indicates a perfect positive covariance between the two variables. D) The covariance measures the strength of the linear relationship between two variables.
A, me thinks. Might be wrong though. Just started revising quants again.
A). The others are just messing with you getting confused with correlation and covariance.
Is “me thinks” one word or two?
A
JoeyDVivre Wrote: ------------------------------------------------------- > Is “me thinks” one word or two? Google tells me that I should have typed “methinks” instead of “me thinks”. Thank God it’s not tested on the exam.
Except now it would be freebie points. Edit: Methinks
I’m not only picking A because Joey says it’s A. I really think it’s A.
D is the correlation coefficient so no. C no. I would’ve leaned toward A over B, but seeing everyone else choose A…woohoo! lucky guess! My study tactics with quant so far- ignore it and maybe it’ll go away. I can’t ignore it forever, but I’m really trying.
Everybody wins! It is A. Which is what I picked too. But the explanation from schweser for part D said covariance measures the strength of the linear relationship between two variables. This is exactly what D said in the question. I know A is the better answer but what is wrong about D. Covariance does measure the linear relationship between, it is just hard to interpret without standardizing it correct? My guess is the word strenght is what is throwing D off. Thoughts?
Yep^
mwvt9 Wrote: ------------------------------------------------------- > Everybody wins! > > It is A. Which is what I picked too. But the > explanation from schweser for part D said > covariance measures the strength of the linear > relationship between two variables. > > This is exactly what D said in the question. I > know A is the better answer but what is wrong > about D. Covariance does measure the linear > relationship between, it is just hard to interpret > without standardizing it correct? > > My guess is the word strenght is what is throwing > D off. > > Thoughts? Covariance measures the degree to which two variables “move together”. I always associate correlation with the “strength of the linear relationship”.
Great. Thanks for the confirmation.