Last answered:

10 May 2023

Posted on:

08 May 2023

0

Why we are solving for (weight*covariance)^2 to calculate portfolio variance

Video - 1:10

Can anyone explain why we are solving for (weight*covariance)^2 to calculate portfolio variance?

isn't the portfolio variance (w1σ1 + w2σ2)^2

2 answers ( 0 marked as helpful)
Posted on:

09 May 2023

0

Hi Ryan!

Great to have you in the course and thanks for reaching out!


Can you please confirm that you are referring to the notation that appears in, for example, minute 1:22 of the video? If that's the one, then portfolio variance is exactly how you say it is; we are just using matrix notation to represent it. Please feel free to refer to an explanation/definition of matrix multiplication or reply to this message should you need a clarification on this subject matter. Thank you!


Looking forward to your answer.
Best,
Martin

Posted on:

10 May 2023

0

Hi Martin,

I have been really enjoying your style of teaching in the python courses so far and thanks for taking the time to answer! 


If i understand you correctly, you're saying:

(w·Cov)^2 = the minute 1:22 econometric matrix notation = single number = portfolio variance = (w1σ1 + w2σ2)^2


I understand the mechanics of it, that squaring (w·Cov)^2 in matrix form is represented by WT * (Covariance Matrix) * W and other online sources have confirmed that Expected portfolio variance = WT * (Covariance Matrix) * W


What I don't quite understand is why this equation, (w·Cov)^2, represents portfolio variance. What does using the weight multiplied by covariance and then squaring it have to do with portfolio variance?



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