i am building a platform for portfolio analytics, part of which is a performance attribution module. Given that most individual portfolio's can never have the same number of stocks as say, a mutual fund, i was wondering how do i perform a stock weighting attribution for a portfolio. For instance if my portfolio had 6 stocks from 3 sectors (Energy , Utilities and Telecom) which have a split of 30-40-30 in my portfolio how do i compare it to the market weightage? These sectors have a weight of 8%, 3% and 2.4% in the S&P 500 ..i don't get anything by comparing 30-40-30 with 8-3-2.4 instantly ..but if i normalize 8-3-2.4 into 60-22-18 i can tell that my pf did better / worse because i was over/under weight one of the sectors. Can i use a normalized method for comparison ? most online sources and papers give a plain vanila approach assuming this can only be used by fund managers et al .. kindly correct me if i am wrong.

Regards, vikram

• I would recommend reading through the two papers given in the second answer to this question: quant.stackexchange.com/questions/2903/… – Dr_Be Feb 10 '16 at 14:39
• Hi BerndH ..thanks for pointing the papers out but i had already read the morningstar paper ..the second one follows pretty much the same track, but both these papers assume a portfolio with a lot of sectors / diversity ..my problem is if i have half as many or lesser .. i am pretty sure we can still benefit from PA but the methodology is what is keeping me a little twisted – Vikram Murthy Feb 10 '16 at 15:10
• OK, I see your point now. Apart from the pure technique (applying Brinson-like methods) your main question is: What is my benchmark? From what you've written it is apparently not the S&P500. You can restrict it to the three sectors (or maybe some more if you have chosen an active weight of 0 % for them in your portfolio). In this case your bm would be a linear combination of the respective S&P500 sector indices with the "normalized" weights. But your free in the first place and can also apply 33.33% to each of them. – Dr_Be Feb 10 '16 at 16:01
• Thanks so much for responding BerndH .. yeah, let me give that a shot and see how the users interpret the comparisons :) ..thanks again – Vikram Murthy Feb 11 '16 at 2:23